From 5fe6ec56cc9750de73ff1e126b68705247ac0041 Mon Sep 17 00:00:00 2001 From: Dennis Trautwein Date: Fri, 20 Oct 2023 08:28:40 +0200 Subject: [PATCH] Add Helia support by making website plots IPFS implementation agnostic (#80) * feat: update queries to agnostic IPFS impl schema * feat: update queries to agnostic IPFS impl schema * update website content * Add plot data * fix helia kubo http comparison graph --- .../website-snapshot-http-ratio.yaml | 5 +- .../website-snapshot-metric-cdf.yaml | 13 +- .../website-snapshot-performance-gauge.yaml | 16 +- .../website-snapshot-probes-count.yaml | 11 +- .../website-snapshot-retrieval-errors.yaml | 8 +- .../website-snapshot-web-vitals-barchart.yaml | 8 +- .../website-trend-metrics.yaml | 10 +- .../website-trend-retrieval-errors.yaml | 10 +- .../websites-http-comparison.yaml | 22 +- .../websites-web-vitals-heatmap.yaml | 8 +- config/profiles.yaml | 550 +- ...t-http-ratio-blog.ipfs.tech-KUBO-ttfb.json | 673 ++ ...t-http-ratio-blog.libp2p.io-KUBO-ttfb.json | 673 ++ ...tp-ratio-consensuslab.world-KUBO-ttfb.json | 673 ++ ...t-http-ratio-docs.ipfs.tech-KUBO-ttfb.json | 673 ++ ...t-http-ratio-docs.libp2p.io-KUBO-ttfb.json | 673 ++ ...pshot-http-ratio-drand.love-KUBO-ttfb.json | 673 ++ .../wiki-KUBO-ttfb.json | 673 ++ ...snapshot-http-ratio-fil.org-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-filecoin.io-KUBO-ttfb.json | 673 ++ ...ttp-ratio-green.filecoin.io-KUBO-ttfb.json | 673 ++ ...apshot-http-ratio-ipfs.tech-KUBO-ttfb.json | 673 ++ ...snapshot-http-ratio-ipld.io-KUBO-ttfb.json | 673 ++ ...apshot-http-ratio-libp2p.io-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-n0.computer-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-probelab.io-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-protocol.ai-KUBO-ttfb.json | 673 ++ ...-ratio-research.protocol.ai-KUBO-ttfb.json | 673 ++ ...p-ratio-singularity.storage-KUBO-ttfb.json | 673 ++ ...-http-ratio-specs.ipfs.tech-KUBO-ttfb.json | 673 ++ ...hot-http-ratio-strn.network-KUBO-ttfb.json | 673 ++ ...hot-http-ratio-web3.storage-KUBO-ttfb.json | 673 ++ ...tric-cdf-blog.ipfs.tech-IPFS-KUBO-fcp.json | 7768 ++++++++++++++++ ...tric-cdf-blog.ipfs.tech-IPFS-KUBO-lcp.json | 7540 ++++++++++++++++ ...ric-cdf-blog.ipfs.tech-IPFS-KUBO-ttfb.json | 7550 ++++++++++++++++ ...tric-cdf-blog.libp2p.io-IPFS-KUBO-fcp.json | 7742 ++++++++++++++++ ...tric-cdf-blog.libp2p.io-IPFS-KUBO-lcp.json | 6698 ++++++++++++++ ...ric-cdf-blog.libp2p.io-IPFS-KUBO-ttfb.json | 7312 +++++++++++++++ ...-cdf-consensuslab.world-IPFS-KUBO-fcp.json | 7850 ++++++++++++++++ ...-cdf-consensuslab.world-IPFS-KUBO-lcp.json | 7852 ++++++++++++++++ ...cdf-consensuslab.world-IPFS-KUBO-ttfb.json | 7294 +++++++++++++++ ...tric-cdf-docs.ipfs.tech-IPFS-KUBO-fcp.json | 7814 ++++++++++++++++ ...tric-cdf-docs.ipfs.tech-IPFS-KUBO-lcp.json | 7812 ++++++++++++++++ ...ric-cdf-docs.ipfs.tech-IPFS-KUBO-ttfb.json | 7430 ++++++++++++++++ ...tric-cdf-docs.libp2p.io-IPFS-KUBO-fcp.json | 7756 ++++++++++++++++ ...tric-cdf-docs.libp2p.io-IPFS-KUBO-lcp.json | 7756 ++++++++++++++++ ...ric-cdf-docs.libp2p.io-IPFS-KUBO-ttfb.json | 7322 +++++++++++++++ ...t-metric-cdf-drand.love-IPFS-KUBO-fcp.json | 7782 ++++++++++++++++ ...t-metric-cdf-drand.love-IPFS-KUBO-lcp.json | 7832 ++++++++++++++++ ...-metric-cdf-drand.love-IPFS-KUBO-ttfb.json | 7492 ++++++++++++++++ .../wiki-IPFS-KUBO-fcp.json | 7838 ++++++++++++++++ .../wiki-IPFS-KUBO-lcp.json | 7838 ++++++++++++++++ .../wiki-IPFS-KUBO-ttfb.json | 7602 ++++++++++++++++ ...shot-metric-cdf-fil.org-IPFS-KUBO-fcp.json | 6998 +++++++++++++++ ...shot-metric-cdf-fil.org-IPFS-KUBO-lcp.json | 6796 ++++++++++++++ ...hot-metric-cdf-fil.org-IPFS-KUBO-ttfb.json | 3984 +++++++++ ...-metric-cdf-filecoin.io-IPFS-KUBO-fcp.json | 7828 ++++++++++++++++ ...-metric-cdf-filecoin.io-IPFS-KUBO-lcp.json | 7876 ++++++++++++++++ ...metric-cdf-filecoin.io-IPFS-KUBO-ttfb.json | 7422 ++++++++++++++++ ...c-cdf-green.filecoin.io-IPFS-KUBO-fcp.json | 7766 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...-metric-cdf-probelab.io-IPFS-KUBO-fcp.json | 7754 ++++++++++++++++ ...-metric-cdf-probelab.io-IPFS-KUBO-lcp.json | 7754 ++++++++++++++++ ...metric-cdf-probelab.io-IPFS-KUBO-ttfb.json | 7426 ++++++++++++++++ ...-metric-cdf-protocol.ai-IPFS-KUBO-fcp.json | 7814 ++++++++++++++++ ...-metric-cdf-protocol.ai-IPFS-KUBO-lcp.json | 7912 +++++++++++++++++ ...metric-cdf-protocol.ai-IPFS-KUBO-ttfb.json | 7244 +++++++++++++++ ...df-research.protocol.ai-IPFS-KUBO-fcp.json | 7780 ++++++++++++++++ ...df-research.protocol.ai-IPFS-KUBO-lcp.json | 7898 ++++++++++++++++ ...f-research.protocol.ai-IPFS-KUBO-ttfb.json | 7416 +++++++++++++++ ...cdf-singularity.storage-IPFS-KUBO-fcp.json | 7846 ++++++++++++++++ ...cdf-singularity.storage-IPFS-KUBO-lcp.json | 7864 ++++++++++++++++ ...df-singularity.storage-IPFS-KUBO-ttfb.json | 7584 ++++++++++++++++ ...ric-cdf-specs.ipfs.tech-IPFS-KUBO-fcp.json | 7702 ++++++++++++++++ ...ric-cdf-specs.ipfs.tech-IPFS-KUBO-lcp.json | 6342 +++++++++++++ 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...nce-gauge-green.filecoin.io-IPFS-KUBO.json | 1061 +++ ...performance-gauge-ipfs.tech-IPFS-KUBO.json | 1061 +++ ...t-performance-gauge-ipld.io-IPFS-KUBO.json | 1061 +++ ...performance-gauge-libp2p.io-IPFS-KUBO.json | 1061 +++ ...rformance-gauge-n0.computer-IPFS-KUBO.json | 1061 +++ ...rformance-gauge-probelab.io-IPFS-KUBO.json | 1061 +++ ...rformance-gauge-protocol.ai-IPFS-KUBO.json | 1061 +++ ...-gauge-research.protocol.ai-IPFS-KUBO.json | 1061 +++ ...e-gauge-singularity.storage-IPFS-KUBO.json | 1061 +++ ...mance-gauge-specs.ipfs.tech-IPFS-KUBO.json | 1061 +++ ...formance-gauge-strn.network-IPFS-KUBO.json | 1061 +++ ...formance-gauge-web3.storage-IPFS-KUBO.json | 1061 +++ ...shot-probes-count-blog.ipfs.tech-KUBO.json | 63 + ...shot-probes-count-blog.libp2p.io-KUBO.json | 63 + ...-probes-count-consensuslab.world-KUBO.json | 63 + ...shot-probes-count-docs.ipfs.tech-KUBO.json | 63 + ...shot-probes-count-docs.libp2p.io-KUBO.json | 63 + ...snapshot-probes-count-drand.love-KUBO.json | 63 + .../wiki-KUBO.json | 63 + ...te-snapshot-probes-count-fil.org-KUBO.json | 63 + ...napshot-probes-count-filecoin.io-KUBO.json | 63 + ...t-probes-count-green.filecoin.io-KUBO.json | 63 + ...-snapshot-probes-count-ipfs.tech-KUBO.json | 63 + ...te-snapshot-probes-count-ipld.io-KUBO.json | 63 + ...-snapshot-probes-count-libp2p.io-KUBO.json | 63 + ...napshot-probes-count-n0.computer-KUBO.json | 63 + ...napshot-probes-count-probelab.io-KUBO.json | 63 + ...napshot-probes-count-protocol.ai-KUBO.json | 63 + ...robes-count-research.protocol.ai-KUBO.json | 63 + ...probes-count-singularity.storage-KUBO.json | 63 + ...hot-probes-count-specs.ipfs.tech-KUBO.json | 63 + ...apshot-probes-count-strn.network-KUBO.json | 63 + ...apshot-probes-count-web3.storage-KUBO.json | 63 + ...-retrieval-errors-blog.ipfs.tech-KUBO.json | 235 + ...-retrieval-errors-blog.libp2p.io-KUBO.json | 235 + ...rieval-errors-consensuslab.world-KUBO.json | 235 + ...-retrieval-errors-docs.ipfs.tech-KUBO.json | 235 + ...-retrieval-errors-docs.libp2p.io-KUBO.json | 235 + ...shot-retrieval-errors-drand.love-KUBO.json | 235 + .../wiki-KUBO.json | 235 + ...napshot-retrieval-errors-fil.org-KUBO.json | 235 + ...hot-retrieval-errors-filecoin.io-KUBO.json | 235 + ...trieval-errors-green.filecoin.io-KUBO.json | 235 + ...pshot-retrieval-errors-ipfs.tech-KUBO.json | 235 + ...napshot-retrieval-errors-ipld.io-KUBO.json | 235 + ...pshot-retrieval-errors-libp2p.io-KUBO.json | 235 + ...hot-retrieval-errors-n0.computer-KUBO.json | 235 + ...hot-retrieval-errors-probelab.io-KUBO.json | 235 + ...hot-retrieval-errors-protocol.ai-KUBO.json | 235 + ...eval-errors-research.protocol.ai-KUBO.json | 235 + ...ieval-errors-singularity.storage-KUBO.json | 235 + ...retrieval-errors-specs.ipfs.tech-KUBO.json | 235 + ...ot-retrieval-errors-strn.network-KUBO.json | 235 + ...ot-retrieval-errors-web3.storage-KUBO.json | 235 + ...blog.ipfs.tech-IPFS-KUBO-eu-central-1.json | 173 + ...blog.libp2p.io-IPFS-KUBO-eu-central-1.json | 173 + ...ensuslab.world-IPFS-KUBO-eu-central-1.json | 173 + ...docs.ipfs.tech-IPFS-KUBO-eu-central-1.json | 173 + ...docs.libp2p.io-IPFS-KUBO-eu-central-1.json | 173 + ...art-drand.love-IPFS-KUBO-eu-central-1.json | 173 + .../wiki-IPFS-KUBO-eu-central-1.json | 173 + ...rchart-fil.org-IPFS-KUBO-eu-central-1.json | 173 + ...rt-filecoin.io-IPFS-KUBO-eu-central-1.json | 173 + ...en.filecoin.io-IPFS-KUBO-eu-central-1.json | 173 + ...hart-ipfs.tech-IPFS-KUBO-eu-central-1.json | 173 + ...rchart-ipld.io-IPFS-KUBO-eu-central-1.json | 173 + ...hart-libp2p.io-IPFS-KUBO-eu-central-1.json | 173 + ...rt-n0.computer-IPFS-KUBO-eu-central-1.json | 173 + ...rt-probelab.io-IPFS-KUBO-eu-central-1.json | 173 + ...rt-protocol.ai-IPFS-KUBO-eu-central-1.json | 173 + ...ch.protocol.ai-IPFS-KUBO-eu-central-1.json | 173 + ...larity.storage-IPFS-KUBO-eu-central-1.json | 173 + ...pecs.ipfs.tech-IPFS-KUBO-eu-central-1.json | 173 + ...t-strn.network-IPFS-KUBO-eu-central-1.json | 173 + ...t-web3.storage-IPFS-KUBO-eu-central-1.json | 173 + ...rend-metrics-blog.ipfs.tech-IPFS-KUBO.json | 322 + ...rend-metrics-blog.libp2p.io-IPFS-KUBO.json | 322 + ...-metrics-consensuslab.world-IPFS-KUBO.json | 322 + ...rend-metrics-docs.ipfs.tech-IPFS-KUBO.json | 322 + ...rend-metrics-docs.libp2p.io-IPFS-KUBO.json | 322 + ...te-trend-metrics-drand.love-IPFS-KUBO.json | 322 + .../wiki-IPFS-KUBO.json | 322 + ...bsite-trend-metrics-fil.org-IPFS-KUBO.json | 322 + ...e-trend-metrics-filecoin.io-IPFS-KUBO.json | 322 + ...d-metrics-green.filecoin.io-IPFS-KUBO.json | 322 + ...ite-trend-metrics-ipfs.tech-IPFS-KUBO.json | 322 + ...bsite-trend-metrics-ipld.io-IPFS-KUBO.json | 322 + ...ite-trend-metrics-libp2p.io-IPFS-KUBO.json | 322 + ...e-trend-metrics-n0.computer-IPFS-KUBO.json | 322 + ...e-trend-metrics-probelab.io-IPFS-KUBO.json | 322 + ...e-trend-metrics-protocol.ai-IPFS-KUBO.json | 322 + ...etrics-research.protocol.ai-IPFS-KUBO.json | 322 + ...metrics-singularity.storage-IPFS-KUBO.json | 322 + ...end-metrics-specs.ipfs.tech-IPFS-KUBO.json | 322 + ...-trend-metrics-strn.network-IPFS-KUBO.json | 322 + ...-trend-metrics-web3.storage-IPFS-KUBO.json | 322 + ...ieval-errors-blog.ipfs.tech-IPFS-KUBO.json | 203 + ...ieval-errors-blog.libp2p.io-IPFS-KUBO.json | 203 + ...l-errors-consensuslab.world-IPFS-KUBO.json | 203 + ...ieval-errors-docs.ipfs.tech-IPFS-KUBO.json | 203 + ...ieval-errors-docs.libp2p.io-IPFS-KUBO.json | 203 + ...retrieval-errors-drand.love-IPFS-KUBO.json | 203 + .../wiki-IPFS-KUBO.json | 203 + ...nd-retrieval-errors-fil.org-IPFS-KUBO.json | 203 + ...etrieval-errors-filecoin.io-IPFS-KUBO.json | 203 + ...al-errors-green.filecoin.io-IPFS-KUBO.json | 203 + ...-retrieval-errors-ipfs.tech-IPFS-KUBO.json | 203 + ...nd-retrieval-errors-ipld.io-IPFS-KUBO.json | 203 + ...-retrieval-errors-libp2p.io-IPFS-KUBO.json | 203 + ...etrieval-errors-n0.computer-IPFS-KUBO.json | 203 + ...etrieval-errors-probelab.io-IPFS-KUBO.json | 203 + ...etrieval-errors-protocol.ai-IPFS-KUBO.json | 203 + ...errors-research.protocol.ai-IPFS-KUBO.json | 203 + ...-errors-singularity.storage-IPFS-KUBO.json | 203 + ...eval-errors-specs.ipfs.tech-IPFS-KUBO.json | 203 + ...trieval-errors-strn.network-IPFS-KUBO.json | 203 + ...trieval-errors-web3.storage-IPFS-KUBO.json | 203 + .../19/websites-http-comparison-ttfb-p90.json | 134 +- ...-web-vitals-heatmap-IPFS-KUBO-fcp-p50.json | 1891 ++++ ...-web-vitals-heatmap-IPFS-KUBO-fcp-p90.json | 1891 ++++ ...-web-vitals-heatmap-IPFS-KUBO-lcp-p50.json | 1891 ++++ ...-web-vitals-heatmap-IPFS-KUBO-lcp-p90.json | 1891 ++++ ...web-vitals-heatmap-IPFS-KUBO-ttfb-p50.json | 1891 ++++ ...web-vitals-heatmap-IPFS-KUBO-ttfb-p90.json | 1891 ++++ ...t-http-ratio-blog.ipfs.tech-KUBO-ttfb.json | 673 ++ ...t-http-ratio-blog.libp2p.io-KUBO-ttfb.json | 673 ++ ...tp-ratio-consensuslab.world-KUBO-ttfb.json | 673 ++ ...t-http-ratio-docs.ipfs.tech-KUBO-ttfb.json | 673 ++ ...t-http-ratio-docs.libp2p.io-KUBO-ttfb.json | 673 ++ ...pshot-http-ratio-drand.love-KUBO-ttfb.json | 673 ++ .../wiki-KUBO-ttfb.json | 673 ++ ...snapshot-http-ratio-fil.org-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-filecoin.io-KUBO-ttfb.json | 673 ++ ...ttp-ratio-green.filecoin.io-KUBO-ttfb.json | 673 ++ ...apshot-http-ratio-ipfs.tech-KUBO-ttfb.json | 673 ++ ...snapshot-http-ratio-ipld.io-KUBO-ttfb.json | 673 ++ ...apshot-http-ratio-libp2p.io-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-n0.computer-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-probelab.io-KUBO-ttfb.json | 673 ++ ...shot-http-ratio-protocol.ai-KUBO-ttfb.json | 673 ++ ...-ratio-research.protocol.ai-KUBO-ttfb.json | 673 ++ ...p-ratio-singularity.storage-KUBO-ttfb.json | 673 ++ ...-http-ratio-specs.ipfs.tech-KUBO-ttfb.json | 673 ++ ...hot-http-ratio-strn.network-KUBO-ttfb.json | 673 ++ ...hot-http-ratio-web3.storage-KUBO-ttfb.json | 673 ++ ...tric-cdf-blog.ipfs.tech-IPFS-KUBO-fcp.json | 7768 ++++++++++++++++ ...tric-cdf-blog.ipfs.tech-IPFS-KUBO-lcp.json | 7540 ++++++++++++++++ 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a/config/plotdefs-website/website-snapshot-http-ratio.yaml b/config/plotdefs-website/website-snapshot-http-ratio.yaml index 4fa4126f8..1abf50b04 100644 --- a/config/plotdefs-website/website-snapshot-http-ratio.yaml +++ b/config/plotdefs-website/website-snapshot-http-ratio.yaml @@ -13,7 +13,7 @@ datasets: select r.region, percentiles.val::float/100 percentile, - coalesce(extract('epoch' from percentile_disc(percentiles.val::float/100) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'KUBO' )) / + coalesce(extract('epoch' from percentile_disc(percentiles.val::float/100) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'IPFS' )) / extract('epoch' from percentile_disc(percentiles.val::float/100) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'HTTP' )), -1) ratio from measurements m inner join runs r on r.id = m.run_id @@ -22,6 +22,7 @@ datasets: and m.website = '{{ .Params.website }}' and m.status_code >= 200 and m.status_code < 400 + and r.ipfs_impl = '{{ .Params.impl }}' group by r.region ) data; @@ -34,7 +35,7 @@ tables: values: "ratio" colorbar: title: - text: "← Kubo faster | HTTP faster →" + text: "← {{ .Params.impl }} faster | HTTP faster →" side: "right" layout: diff --git a/config/plotdefs-website/website-snapshot-metric-cdf.yaml b/config/plotdefs-website/website-snapshot-metric-cdf.yaml index 8265d3ab1..ab1d13795 100644 --- a/config/plotdefs-website/website-snapshot-metric-cdf.yaml +++ b/config/plotdefs-website/website-snapshot-metric-cdf.yaml @@ -8,7 +8,8 @@ datasets: r.region, m.{{ .Params.metric }}, cume_dist() over (partition by r.region order by m.{{ .Params.metric }}) as cumedist - from measurements m inner join runs r on r.id = m.run_id + from measurements m + inner join runs r on r.id = m.run_id where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' @@ -16,6 +17,7 @@ datasets: and m.{{ .Params.metric }} is not null and m.status_code >= 200 and m.status_code < 400 + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') ) select cdf.region as region, @@ -35,7 +37,12 @@ series: groupfield: "region" groupvalue: "*" -# {{ $xrange_max := 0 }} +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} + +# {{ $xrange_max := 0 }} # {{ if eq .Params.metric "ttfb" }} # {{ $xrange_max = 2 }} # {{ else if eq .Params.metric "cls" }} @@ -57,7 +64,7 @@ layout: title: font: size: 10 - text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} ({{ .Params.type }}, {{ .Params.website }}). Source: Tiros.' + text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} ({{ $title_label }}, {{ .Params.website }}). Source: Tiros.' x: 1 xanchor: "right" y: 0.01 diff --git a/config/plotdefs-website/website-snapshot-performance-gauge.yaml b/config/plotdefs-website/website-snapshot-performance-gauge.yaml index 93127b981..ea4f529b6 100644 --- a/config/plotdefs-website/website-snapshot-performance-gauge.yaml +++ b/config/plotdefs-website/website-snapshot-performance-gauge.yaml @@ -19,7 +19,8 @@ datasets: extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'ap-southeast-2' and m.fcp is not null )) p90_fcp_ap_southeast_2, extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'af-south-1' and m.fcp is not null )) p90_fcp_af_south_1, extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'sa-east-1' and m.fcp is not null )) p90_fcp_sa_east_1 - from measurements m inner join runs r on r.id = m.run_id + from measurements m + inner join runs r on r.id = m.run_id where m.created_at >= {{ .StartOfWeek | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfWeek | timestamptz }} and m.website = '{{ .Params.website }}' @@ -27,6 +28,7 @@ datasets: and m.ttfb is not null and m.status_code >= 200 and m.status_code < 400 + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') - name: "previous" source: "tiros" query: > @@ -46,7 +48,8 @@ datasets: extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'ap-southeast-2' and m.fcp is not null )) p90_fcp_ap_southeast_2, extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'af-south-1' and m.fcp is not null )) p90_fcp_af_south_1, extract('epoch' from percentile_disc(0.9) within group ( order by m.fcp ) filter ( where r.region = 'sa-east-1' and m.fcp is not null )) p90_fcp_sa_east_1 - from measurements m inner join runs r on r.id = m.run_id + from measurements m + inner join runs r on r.id = m.run_id where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' @@ -54,6 +57,13 @@ datasets: and m.ttfb is not null and m.status_code >= 200 and m.status_code < 400 + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') + + +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} ttfbScalar: &ttfbScalar type: "gauge" @@ -168,7 +178,7 @@ layout: title: font: size: 10 - text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} (p90, {{ .Params.type }}, {{ .Params.website }}). Source: Tiros.' + text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} (p90, {{ $title_label }}, {{ .Params.website }}). Source: Tiros.' x: 1 xanchor: "right" y: 0.103 diff --git a/config/plotdefs-website/website-snapshot-probes-count.yaml b/config/plotdefs-website/website-snapshot-probes-count.yaml index 9d4e5de37..2355720aa 100644 --- a/config/plotdefs-website/website-snapshot-probes-count.yaml +++ b/config/plotdefs-website/website-snapshot-probes-count.yaml @@ -12,20 +12,21 @@ datasets: where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' + and r.ipfs_impl = '{{ .Params.impl }}' and (m.error is null or m.error not like '%ERR_CONNECTION_REFUSED%') -- this is a measurement error and not a website error ) select - sum(1) filter ( where cte.type = 'KUBO' and not cte.has_error) successful_kubo, + sum(1) filter ( where cte.type = 'IPFS' and not cte.has_error) successful_ipfs, sum(1) filter ( where cte.type = 'HTTP' and not cte.has_error) successful_http, - sum(1) filter ( where cte.type = 'KUBO' ) total_kubo, + sum(1) filter ( where cte.type = 'IPFS' ) total_ipfs, sum(1) filter ( where cte.type = 'HTTP' ) total_http from cte scalars: - type: "number" - name: "Kubo" + name: "{{ .Params.impl }}" dataset: "current" - value: "successful_kubo" + value: "successful_ipfs" - type: "number" name: "HTTP" dataset: "current" @@ -38,7 +39,7 @@ layout: title: font: size: 10 - text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} ({{ .Params.website }}). Source: Tiros.' + text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} ({{ .Params.impl }}, {{ .Params.website }}). Source: Tiros.' x: 1 xanchor: "right" y: 0.01 diff --git a/config/plotdefs-website/website-snapshot-retrieval-errors.yaml b/config/plotdefs-website/website-snapshot-retrieval-errors.yaml index d57ea115c..5c8e7efac 100644 --- a/config/plotdefs-website/website-snapshot-retrieval-errors.yaml +++ b/config/plotdefs-website/website-snapshot-retrieval-errors.yaml @@ -8,14 +8,18 @@ datasets: *, (m.ttfb is null and m.lcp is null and m.fcp is null and m.tti is null and m.cls is null) or m.status_code >= 400 or m.status_code < 200 has_error from measurements m - inner join runs r on r.id = m.run_id + inner join runs r on r.id = m.run_id where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' + and r.ipfs_impl = '{{ .Params.impl }}' and (m.error is null or m.error not like '%ERR_CONNECTION_REFUSED%') -- this is a measurement error and not a website error ) select cte.region, - cte.type, + case + when cte.type::text = 'IPFS' then '{{ .Params.impl }}' + else cte.type::text + end as type, 100 * coalesce(sum(1) filter ( where cte.has_error), 0)::FLOAT / coalesce(sum(1), 0) pct_errors, 100 * coalesce(sum(1) filter ( where not cte.has_error), 0)::FLOAT / coalesce(sum(1), 0) pct_success, count(*) total diff --git a/config/plotdefs-website/website-snapshot-web-vitals-barchart.yaml b/config/plotdefs-website/website-snapshot-web-vitals-barchart.yaml index 9e02d7cd9..fa77b866f 100644 --- a/config/plotdefs-website/website-snapshot-web-vitals-barchart.yaml +++ b/config/plotdefs-website/website-snapshot-web-vitals-barchart.yaml @@ -17,6 +17,7 @@ datasets: where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and r.region = '{{ .Params.region }}' + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') and m.type = '{{ .Params.type }}' and m.website = '{{ .Params.website }}' and (m.error is null or m.error not like '%ERR_CONNECTION_REFUSED%') -- this is a measurement error and not a website error @@ -105,10 +106,15 @@ series: color: "red" hovertemplate: "%{x} %{y:.1f}%" +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} + layout: barmode: "stack" title: - text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }}
({{ .Params.type }}, {{ .Params.region }}, {{ .Params.website }}). Source: Tiros.' + text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }}
({{ $title_label }}, {{ .Params.region }}, {{ .Params.website }}). Source: Tiros.' font: size: 10 x: 1 diff --git a/config/plotdefs-website/website-trend-metrics.yaml b/config/plotdefs-website/website-trend-metrics.yaml index 132c1d30f..a7f7c3ed5 100644 --- a/config/plotdefs-website/website-trend-metrics.yaml +++ b/config/plotdefs-website/website-trend-metrics.yaml @@ -15,7 +15,8 @@ datasets: where m.created_at >= {{ .StartOfDay | timestamptz }} - '30d'::interval and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' - and m.type = 'KUBO' + and m.type = '{{ .Params.type }}' + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') and ((m.status_code >= 200 and m.status_code < 400) or m.status_code is null) group by date_trunc('day', m.created_at) ) @@ -50,6 +51,11 @@ series: labels: "date" values: "p90_tti_rolling" +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} + layout: yaxis: autorange: true @@ -65,7 +71,7 @@ layout: title: font: size: 10 - text: "(p90, {{ .Params.website }}). Source: Tiros." + text: "(p90, {{ $title_label }}, {{ .Params.website }}). Source: Tiros." x: 1 xanchor: "right" y: 0.01 diff --git a/config/plotdefs-website/website-trend-retrieval-errors.yaml b/config/plotdefs-website/website-trend-retrieval-errors.yaml index 7fa365f5f..8433a01cd 100644 --- a/config/plotdefs-website/website-trend-retrieval-errors.yaml +++ b/config/plotdefs-website/website-trend-retrieval-errors.yaml @@ -14,6 +14,7 @@ datasets: and m.created_at < {{ .StartOfDay | timestamptz }} and m.website = '{{ .Params.website }}' and m.type = '{{ .Params.type }}' + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') and (m.error is null or m.error not like '%ERR_CONNECTION_REFUSED%') -- this is a measurement error and not a website error ), series as ( select @@ -35,7 +36,7 @@ datasets: series: - type: "bar" - name: "Kubo" + name: "{{ .Params.impl }}" dataset: "current" color: "blue" labels: "date" @@ -48,6 +49,11 @@ series: color: "black" yaxis: "y2" +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} + layout: legend: orientation: "h" @@ -66,7 +72,7 @@ layout: title: font: size: 10 - text: "({{ .Params.type }}, {{ .Params.website }}). Source: Tiros." + text: "({{ .Params.website }}). Source: Tiros." x: 1 xanchor: "right" y: 0.01 diff --git a/config/plotdefs-website/websites-http-comparison.yaml b/config/plotdefs-website/websites-http-comparison.yaml index 5f5d5e10b..a19850687 100644 --- a/config/plotdefs-website/websites-http-comparison.yaml +++ b/config/plotdefs-website/websites-http-comparison.yaml @@ -5,22 +5,30 @@ datasets: query: > select r.region, - percentile_cont(0.{{ .Params.percentile }}) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'KUBO' ) p{{ .Params.percentile }}_kubo, - percentile_cont(0.{{ .Params.percentile }}) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'HTTP' ) p{{ .Params.percentile }}_http + coalesce(percentile_cont(0.{{ .Params.percentile }}) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'IPFS' and r.ipfs_impl = 'KUBO' ), '0 seconds'::interval) p{{ .Params.percentile }}_kubo, + coalesce(percentile_cont(0.{{ .Params.percentile }}) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'IPFS' and r.ipfs_impl = 'HELIA' ), '0 seconds'::interval) p{{ .Params.percentile }}_helia, + coalesce(percentile_cont(0.{{ .Params.percentile }}) within group ( order by m.{{ .Params.metric }} ) filter ( where m.type = 'HTTP' ), '0 seconds'::interval) p{{ .Params.percentile }}_http from measurements m - inner join runs r on r.id = m.run_id - where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval - and m.created_at < {{ .StartOfDay | timestamptz }} - and m.status_code >= 200 - and m.status_code < 400 + inner join runs r on r.id = m.run_id + where m.created_at >= {{ .StartOfDay | timestamptz }} - '1 week'::interval + and m.created_at < {{ .StartOfDay | timestamptz }} + and m.status_code >= 200 + and m.status_code < 400 group by r.region series: + - type: "bar" + name: "Helia" + dataset: "current" + labels: "region" + values: "p{{ .Params.percentile }}_helia" + color: "red" - type: "bar" name: "Kubo" dataset: "current" labels: "region" values: "p{{ .Params.percentile }}_kubo" + color: "blue" - type: "bar" name: "HTTP" dataset: "current" diff --git a/config/plotdefs-website/websites-web-vitals-heatmap.yaml b/config/plotdefs-website/websites-web-vitals-heatmap.yaml index 3b7f5cc68..40eea4533 100644 --- a/config/plotdefs-website/websites-web-vitals-heatmap.yaml +++ b/config/plotdefs-website/websites-web-vitals-heatmap.yaml @@ -14,6 +14,7 @@ datasets: and m.type = '{{ .Params.type }}' and m.status_code >= 200 and m.status_code < 400 + and (r.ipfs_impl = '{{ .Params.impl }}' or '{{ .Params.type }}' = 'HTTP') group by r.region, m.website; tables: @@ -28,6 +29,11 @@ tables: text: "Latency in s" side: "right" +# {{ $title_label := .Params.type }} +# {{ if eq .Params.type "IPFS" }} +# {{ $title_label = .Params.impl }} +# {{ end }} + layout: automargin: true margin: @@ -35,7 +41,7 @@ layout: title: font: size: 10 - text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} (p{{ .Params.percentile }}, {{ .Params.metric }}, {{ .Params.type }}). Source: Tiros.' + text: 'Data: {{ .EndOfPreviousDay | dayModify "-7" | simpledate}} - {{ .EndOfPreviousDay | simpledate }} (p{{ .Params.percentile }}, {{ .Params.metric }}, {{ $title_label }}). Source: Tiros.' x: 0.99 xanchor: "right" y: 0.01 diff --git a/config/profiles.yaml b/config/profiles.yaml index 1e8f5548b..467cce497 100644 --- a/config/profiles.yaml +++ b/config/profiles.yaml @@ -2,52 +2,74 @@ output: '{{.PlotDefFilename}}.json' - source: ./plotdefs-website/website-snapshot-performance-gauge.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.impl }}.json" variants: - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: drand.love - type: KUBO + type: IPFS + impl: KUBO - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO - website: strn.network - type: KUBO + type: IPFS + impl: KUBO - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO - website: fil.org - type: KUBO + type: IPFS + impl: KUBO - source: ./plotdefs-website/website-trend-hosters.yaml output: "{{.PlotDefFilename}}-{{ .Params.website }}.json" @@ -76,30 +98,74 @@ - website: fil.org - source: ./plotdefs-website/website-trend-metrics.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.impl }}.json" variants: - website: protocol.ai + type: IPFS + impl: KUBO - website: filecoin.io + type: IPFS + impl: KUBO - website: docs.libp2p.io + type: IPFS + impl: KUBO - website: drand.love + type: IPFS + impl: KUBO - website: libp2p.io + type: IPFS + impl: KUBO - website: ipld.io + type: IPFS + impl: KUBO - website: green.filecoin.io + type: IPFS + impl: KUBO - website: web3.storage + type: IPFS + impl: KUBO - website: consensuslab.world + type: IPFS + impl: KUBO - website: strn.network + type: IPFS + impl: KUBO - website: research.protocol.ai + type: IPFS + impl: KUBO - website: ipfs.tech + type: IPFS + impl: KUBO - website: blog.ipfs.tech + type: IPFS + impl: KUBO - website: docs.libp2p.io + type: IPFS + impl: KUBO - website: blog.libp2p.io + type: IPFS + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki + type: IPFS + impl: KUBO - website: specs.ipfs.tech + type: IPFS + impl: KUBO - website: probelab.io + type: IPFS + impl: KUBO - website: docs.ipfs.tech + type: IPFS + impl: KUBO - website: singularity.storage + type: IPFS + impl: KUBO - website: n0.computer + type: IPFS + impl: KUBO - website: fil.org + type: IPFS + impl: KUBO - source: ./plotdefs-website/website-trend-providers.yaml output: "{{.PlotDefFilename}}-{{ .Params.website }}.json" @@ -128,452 +194,642 @@ - website: fil.org - source: ./plotdefs-website/website-trend-retrieval-errors.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.impl }}.json" variants: - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: drand.love - type: KUBO + type: IPFS + impl: KUBO - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO - website: strn.network - type: KUBO + type: IPFS + impl: KUBO - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO - website: fil.org - type: KUBO + type: IPFS + impl: KUBO - source: ./plotdefs-website/website-snapshot-probes-count.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.impl }}.json" variants: - website: protocol.ai + impl: KUBO - website: filecoin.io + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: drand.love + impl: KUBO - website: protocol.ai + impl: KUBO - website: filecoin.io + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: drand.love + impl: KUBO - website: libp2p.io + impl: KUBO - website: ipld.io + impl: KUBO - website: green.filecoin.io + impl: KUBO - website: web3.storage + impl: KUBO - website: consensuslab.world + impl: KUBO - website: strn.network + impl: KUBO - website: research.protocol.ai + impl: KUBO - website: ipfs.tech + impl: KUBO - website: blog.ipfs.tech + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: blog.libp2p.io + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki + impl: KUBO - website: specs.ipfs.tech + impl: KUBO - website: probelab.io + impl: KUBO - website: docs.ipfs.tech + impl: KUBO - website: singularity.storage + impl: KUBO - website: n0.computer + impl: KUBO - website: fil.org + impl: KUBO - source: ./plotdefs-website/website-snapshot-web-vitals-barchart.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.region }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.impl }}-{{ .Params.region }}.json" variants: - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: drand.love - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: strn.network - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - website: fil.org - type: KUBO + type: IPFS + impl: KUBO region: eu-central-1 - source: ./plotdefs-website/website-snapshot-retrieval-errors.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.impl }}.json" variants: - website: protocol.ai + impl: KUBO - website: filecoin.io + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: drand.love + impl: KUBO - website: protocol.ai + impl: KUBO - website: filecoin.io + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: drand.love + impl: KUBO - website: libp2p.io + impl: KUBO - website: ipld.io + impl: KUBO - website: green.filecoin.io + impl: KUBO - website: web3.storage + impl: KUBO - website: consensuslab.world + impl: KUBO - website: strn.network + impl: KUBO - website: research.protocol.ai + impl: KUBO - website: ipfs.tech + impl: KUBO - website: blog.ipfs.tech + impl: KUBO - website: docs.libp2p.io + impl: KUBO - website: blog.libp2p.io + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki + impl: KUBO - website: specs.ipfs.tech + impl: KUBO - website: probelab.io + impl: KUBO - website: docs.ipfs.tech + impl: KUBO - website: singularity.storage + impl: KUBO - website: n0.computer + impl: KUBO - website: fil.org + impl: KUBO - source: ./plotdefs-website/website-snapshot-metric-cdf.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.metric }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.type }}-{{ .Params.impl }}-{{ .Params.metric }}.json" variants: - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: drand.love - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: drand.love - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: drand.love - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: ipld.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: green.filecoin.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: web3.storage - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: consensuslab.world - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: strn.network - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: strn.network - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: strn.network - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: research.protocol.ai - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: blog.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: docs.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: blog.libp2p.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: en.wikipedia-on-ipfs.org/wiki - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: specs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: probelab.io - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: docs.ipfs.tech - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: singularity.storage - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: n0.computer - type: KUBO + type: IPFS + impl: KUBO metric: lcp - website: fil.org - type: KUBO + type: IPFS + impl: KUBO metric: ttfb - website: fil.org - type: KUBO + type: IPFS + impl: KUBO metric: fcp - website: fil.org - type: KUBO + type: IPFS + impl: KUBO metric: lcp - source: ./plotdefs-website/website-snapshot-http-ratio.yaml - output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.metric }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.website }}-{{ .Params.impl }}-{{ .Params.metric }}.json" variants: - website: protocol.ai metric: ttfb + impl: KUBO - website: filecoin.io metric: ttfb + impl: KUBO - website: docs.libp2p.io metric: ttfb + impl: KUBO - website: drand.love metric: ttfb + impl: KUBO - website: libp2p.io metric: ttfb + impl: KUBO - website: ipld.io metric: ttfb + impl: KUBO - website: green.filecoin.io metric: ttfb + impl: KUBO - website: web3.storage metric: ttfb + impl: KUBO - website: consensuslab.world metric: ttfb + impl: KUBO - website: strn.network metric: ttfb + impl: KUBO - website: research.protocol.ai metric: ttfb + impl: KUBO - website: ipfs.tech metric: ttfb + impl: KUBO - website: blog.ipfs.tech metric: ttfb + impl: KUBO - website: docs.libp2p.io metric: ttfb + impl: KUBO - website: blog.libp2p.io metric: ttfb + impl: KUBO - website: en.wikipedia-on-ipfs.org/wiki metric: ttfb + impl: KUBO - website: specs.ipfs.tech metric: ttfb + impl: KUBO - website: probelab.io metric: ttfb + impl: KUBO - website: docs.ipfs.tech metric: ttfb + impl: KUBO - website: singularity.storage metric: ttfb + impl: KUBO - website: n0.computer metric: ttfb + impl: KUBO - website: fil.org metric: ttfb + impl: KUBO - source: ./plotdefs-website/websites-web-vitals-heatmap.yaml - output: "{{.PlotDefFilename}}-{{ .Params.type }}-{{ .Params.metric }}-p{{ .Params.percentile }}.json" + output: "{{.PlotDefFilename}}-{{ .Params.type }}-{{ .Params.impl }}-{{ .Params.metric }}-p{{ .Params.percentile }}.json" variants: - - type: KUBO + - type: IPFS + impl: KUBO percentile: 50 metric: ttfb - - type: KUBO + - type: IPFS + impl: KUBO percentile: 90 metric: ttfb - - type: KUBO + - type: IPFS + impl: KUBO percentile: 50 metric: fcp - - type: KUBO + - type: IPFS + impl: KUBO percentile: 90 metric: fcp - - type: KUBO + - type: IPFS + impl: KUBO percentile: 50 metric: lcp - - type: KUBO + - type: IPFS + impl: KUBO percentile: 90 metric: lcp diff --git a/content.en/plots/2023/10/19/website-snapshot-http-ratio-blog.ipfs.tech-KUBO-ttfb.json b/content.en/plots/2023/10/19/website-snapshot-http-ratio-blog.ipfs.tech-KUBO-ttfb.json new file mode 100644 index 000000000..8870f17b1 --- /dev/null +++ b/content.en/plots/2023/10/19/website-snapshot-http-ratio-blog.ipfs.tech-KUBO-ttfb.json @@ -0,0 +1,673 @@ +{ + "data": [ + { + "type": "heatmap", + "colorbar": { + "title": { + "side": "right", + "text": "← KUBO faster | HTTP faster →" + } + }, + "colorscale": "Viridis", + "name": "name", + "reversescale": true, + "x": [ + "af-south-1", + 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Source: Tiros.", + "x": 0.99, + "xanchor": "right", + "y": 0.01, + "yanchor": "bottom" + }, + "xaxis": { + "automargin": true, + "side": "top", + "title": { + "text": "AWS Region" + } + }, + "yaxis": { + "automargin": true, + "title": { + "text": "Website" + } + } + }, + "params": null, + "dynamicLayout": null, + "config": null +} diff --git a/content.en/websites/_index.md b/content.en/websites/_index.md index 7ff9cd75b..5442c1f62 100644 --- a/content.en/websites/_index.md +++ b/content.en/websites/_index.md @@ -28,45 +28,46 @@ combined dataset. By focusing on these overall trends, we can gain valuable insights into the performance of Kubo TTFB performance as a whole, making it easier to identify any notable deviations or improvements in that metric over time. -## Kubo vs HTTP (90th percentile) {#websites-http-comparison-ttfb-p90} +## Helia vs Kubo vs HTTP (90th percentile) {#websites-http-comparison-ttfb-p90} {{< plotly json="../../plots/latest/websites-http-comparison-ttfb-p90.json" height="350px" >}} The graph shows the 90th percentile of the Time to First Byte (TTFB) metric for -both HTTP and Kubo protocols across seven distinct regions. The horizontal axis -represents the seven regions, while the vertical axis indicates TTFB in seconds. +retrievals via HTTP, through Helia, and through Kubo across seven distinct +regions. The horizontal axis represents the seven regions, while the vertical +axis indicates TTFB in seconds. -By displaying separate bars for HTTP and Kubo in each region, the graph allows +By displaying separate bars for HTTP, Helia, and Kubo in each region, the graph allows for a direct comparison of their TTFB performance. This comparison reveals performance differences and provides insights into the efficiency of each -protocol in different geographic areas. +protocol/implementation in different geographic areas. ## Time To First Byte using Kubo -### (50th percentile) {#websites-web-vitals-heatmap-KUBO-ttfb-p50} +### (50th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-ttfb-p50} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-ttfb-p50.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-ttfb-p50.json" height="700px" >}} -### (90th percentile) {#websites-web-vitals-heatmap-KUBO-ttfb-p90} +### (90th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-ttfb-p90} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-ttfb-p90.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-ttfb-p90.json" height="700px" >}} ## First Contentful Paint using Kubo -### (50th percentile) {#websites-web-vitals-heatmap-KUBO-fcp-p50} +### (50th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-fcp-p50} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-fcp-p50.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-fcp-p50.json" height="700px" >}} -### (90th percentile) {#websites-web-vitals-heatmap-KUBO-fcp-p90} +### (90th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-fcp-p90} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-fcp-p90.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-fcp-p90.json" height="700px" >}} ## Largest Contentful Paint using Kubo -### (50th percentile) {#websites-web-vitals-heatmap-KUBO-lcp-p50} +### (50th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-lcp-p50} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-lcp-p50.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-lcp-p50.json" height="700px" >}} -### (90th percentile) {#websites-web-vitals-heatmap-KUBO-lcp-p90} +### (90th percentile) {#websites-web-vitals-heatmap-IPFS-KUBO-lcp-p90} -{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-KUBO-lcp-p90.json" height="700px" >}} +{{< plotly json="../../plots/latest/websites-web-vitals-heatmap-IPFS-KUBO-lcp-p90.json" height="700px" >}} diff --git a/content.en/websites/blog.ipfs.tech.md b/content.en/websites/blog.ipfs.tech.md index a70b6b150..7cdf27e8e 100644 --- a/content.en/websites/blog.ipfs.tech.md +++ b/content.en/websites/blog.ipfs.tech.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-blog.ipfs.tech-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-blog.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-blog.ipfs.tech.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-blog.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-blog.ipfs.tech-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-blog.ipfs.tech-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-blog.ipfs.tech.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-blog.ipfs.tech-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-blog.ipfs.tech-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-blog.ipfs.tech-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-blog.ipfs.tech.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-blog.ipfs.tech-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.ipfs.tech-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-blog.ipfs.tech-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-blog.ipfs.tech-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/blog.libp2p.io.md b/content.en/websites/blog.libp2p.io.md index dfbced4d3..5188c8803 100644 --- a/content.en/websites/blog.libp2p.io.md +++ b/content.en/websites/blog.libp2p.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-blog.libp2p.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-blog.libp2p.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-blog.libp2p.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-blog.libp2p.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-blog.libp2p.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-blog.libp2p.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-blog.libp2p.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-blog.libp2p.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-blog.libp2p.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-blog.libp2p.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-blog.libp2p.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-blog.libp2p.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-blog.libp2p.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-blog.libp2p.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-blog.libp2p.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/consensuslab.world.md b/content.en/websites/consensuslab.world.md index 83dc5091c..5452f5fa1 100644 --- a/content.en/websites/consensuslab.world.md +++ b/content.en/websites/consensuslab.world.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-consensuslab.world-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-consensuslab.world-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-consensuslab.world.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-consensuslab.world-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-consensuslab.world-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-consensuslab.world-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-consensuslab.world.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-consensuslab.world-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-consensuslab.world-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-consensuslab.world-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-consensuslab.world.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-consensuslab.world-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-consensuslab.world-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-consensuslab.world-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-consensuslab.world-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/docs.ipfs.tech.md b/content.en/websites/docs.ipfs.tech.md index f3084a5e3..f1755fddd 100644 --- a/content.en/websites/docs.ipfs.tech.md +++ b/content.en/websites/docs.ipfs.tech.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-docs.ipfs.tech-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-docs.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-docs.ipfs.tech.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-docs.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-docs.ipfs.tech-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-docs.ipfs.tech-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-docs.ipfs.tech.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-docs.ipfs.tech-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-docs.ipfs.tech-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-docs.ipfs.tech-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-docs.ipfs.tech.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-docs.ipfs.tech-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.ipfs.tech-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-docs.ipfs.tech-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-docs.ipfs.tech-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/docs.libp2p.io.md b/content.en/websites/docs.libp2p.io.md index f20879528..4616ecb1c 100644 --- a/content.en/websites/docs.libp2p.io.md +++ b/content.en/websites/docs.libp2p.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-docs.libp2p.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-docs.libp2p.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-docs.libp2p.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-docs.libp2p.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-docs.libp2p.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-docs.libp2p.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-docs.libp2p.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-docs.libp2p.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-docs.libp2p.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-docs.libp2p.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-docs.libp2p.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-docs.libp2p.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-docs.libp2p.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-docs.libp2p.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-docs.libp2p.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/drand.love.md b/content.en/websites/drand.love.md index 2d9d4e765..7f04f80d8 100644 --- a/content.en/websites/drand.love.md +++ b/content.en/websites/drand.love.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-drand.love-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-drand.love-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-drand.love.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-drand.love-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-drand.love-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-drand.love-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-drand.love.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-drand.love-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-drand.love-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-drand.love-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-drand.love.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-drand.love-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-drand.love-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-drand.love-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-drand.love-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/fil.org.md b/content.en/websites/fil.org.md index 2195db012..3bb554ba3 100644 --- a/content.en/websites/fil.org.md +++ b/content.en/websites/fil.org.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-fil.org-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-fil.org-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-fil.org.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-fil.org-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-fil.org-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-fil.org-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-fil.org.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-fil.org-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-fil.org-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-fil.org-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-fil.org.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-fil.org-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-fil.org-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-fil.org-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-fil.org-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/filecoin.io.md b/content.en/websites/filecoin.io.md index 342f2a7d4..600d39fb0 100644 --- a/content.en/websites/filecoin.io.md +++ b/content.en/websites/filecoin.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-filecoin.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-filecoin.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-filecoin.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-filecoin.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-filecoin.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-filecoin.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-filecoin.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-filecoin.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-filecoin.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-filecoin.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-filecoin.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-filecoin.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-filecoin.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-filecoin.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-filecoin.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/gen.template b/content.en/websites/gen.template index d286ddc70..dff9eb611 100644 --- a/content.en/websites/gen.template +++ b/content.en/websites/gen.template @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-|| .Website ||-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-|| .Website ||-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-|| .Website ||.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-|| .Website ||-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-|| .Website ||-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-|| .Website ||-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-|| .Website ||.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-|| .Website ||-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-|| .Website ||-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-|| .Website ||-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-|| .Website ||.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-|| .Website ||-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-|| .Website ||-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-|| .Website ||-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-|| .Website ||-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/green.filecoin.io.md b/content.en/websites/green.filecoin.io.md index 8ae57647c..eac79531b 100644 --- a/content.en/websites/green.filecoin.io.md +++ b/content.en/websites/green.filecoin.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-green.filecoin.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-green.filecoin.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-green.filecoin.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-green.filecoin.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-green.filecoin.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-green.filecoin.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-green.filecoin.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-green.filecoin.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-green.filecoin.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-green.filecoin.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-green.filecoin.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-green.filecoin.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-green.filecoin.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-green.filecoin.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-green.filecoin.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/ipfs.tech.md b/content.en/websites/ipfs.tech.md index 0d5362d76..bc528e64b 100644 --- a/content.en/websites/ipfs.tech.md +++ b/content.en/websites/ipfs.tech.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-ipfs.tech-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-ipfs.tech-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-ipfs.tech.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-ipfs.tech-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-ipfs.tech-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-ipfs.tech-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-ipfs.tech.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-ipfs.tech-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-ipfs.tech-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-ipfs.tech-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-ipfs.tech.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-ipfs.tech-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipfs.tech-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-ipfs.tech-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-ipfs.tech-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/ipld.io.md b/content.en/websites/ipld.io.md index 60bd29dd9..52e5cce34 100644 --- a/content.en/websites/ipld.io.md +++ b/content.en/websites/ipld.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-ipld.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-ipld.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-ipld.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-ipld.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-ipld.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-ipld.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-ipld.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-ipld.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-ipld.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-ipld.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-ipld.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-ipld.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-ipld.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-ipld.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-ipld.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/libp2p.io.md b/content.en/websites/libp2p.io.md index f0d5164cc..a39bbf86c 100644 --- a/content.en/websites/libp2p.io.md +++ b/content.en/websites/libp2p.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-libp2p.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-libp2p.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-libp2p.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-libp2p.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-libp2p.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-libp2p.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-libp2p.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-libp2p.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-libp2p.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-libp2p.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-libp2p.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-libp2p.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-libp2p.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-libp2p.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-libp2p.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/n0.computer.md b/content.en/websites/n0.computer.md index aea84a55f..9fcfec621 100644 --- a/content.en/websites/n0.computer.md +++ b/content.en/websites/n0.computer.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-n0.computer-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-n0.computer-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-n0.computer.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-n0.computer-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-n0.computer-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-n0.computer-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-n0.computer.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-n0.computer-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-n0.computer-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-n0.computer-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-n0.computer.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-n0.computer-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-n0.computer-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-n0.computer-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-n0.computer-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/probelab.io.md b/content.en/websites/probelab.io.md index d5e57cd0a..18d527fd1 100644 --- a/content.en/websites/probelab.io.md +++ b/content.en/websites/probelab.io.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-probelab.io-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-probelab.io-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-probelab.io.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-probelab.io-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-probelab.io-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-probelab.io-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-probelab.io.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-probelab.io-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-probelab.io-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-probelab.io-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-probelab.io.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-probelab.io-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-probelab.io-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-probelab.io-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-probelab.io-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/protocol.ai.md b/content.en/websites/protocol.ai.md index ec34081d4..a6fbb057e 100644 --- a/content.en/websites/protocol.ai.md +++ b/content.en/websites/protocol.ai.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-protocol.ai-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-protocol.ai-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-protocol.ai.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-protocol.ai-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-protocol.ai-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-protocol.ai-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-protocol.ai.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-protocol.ai-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-protocol.ai-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-protocol.ai-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-protocol.ai.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-protocol.ai-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-protocol.ai-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-protocol.ai-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-protocol.ai-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/research.protocol.ai.md b/content.en/websites/research.protocol.ai.md index 86f097fbe..8bcacb838 100644 --- a/content.en/websites/research.protocol.ai.md +++ b/content.en/websites/research.protocol.ai.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-research.protocol.ai-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-research.protocol.ai-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-research.protocol.ai.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-research.protocol.ai-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-research.protocol.ai-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-research.protocol.ai-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-research.protocol.ai.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-research.protocol.ai-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-research.protocol.ai-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-research.protocol.ai-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-research.protocol.ai.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-research.protocol.ai-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-research.protocol.ai-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-research.protocol.ai-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-research.protocol.ai-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/singularity.storage.md b/content.en/websites/singularity.storage.md index fb867b2cb..8b146e6b1 100644 --- a/content.en/websites/singularity.storage.md +++ b/content.en/websites/singularity.storage.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-singularity.storage-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-singularity.storage-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-singularity.storage.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-singularity.storage-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-singularity.storage-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-singularity.storage-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-singularity.storage.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-singularity.storage-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-singularity.storage-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-singularity.storage-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-singularity.storage.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-singularity.storage-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-singularity.storage-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-singularity.storage-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-singularity.storage-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/specs.ipfs.tech.md b/content.en/websites/specs.ipfs.tech.md index 4856fb9a5..8c61c902a 100644 --- a/content.en/websites/specs.ipfs.tech.md +++ b/content.en/websites/specs.ipfs.tech.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-specs.ipfs.tech-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-specs.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-specs.ipfs.tech.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-specs.ipfs.tech-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-specs.ipfs.tech-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-specs.ipfs.tech-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-specs.ipfs.tech.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-specs.ipfs.tech-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-specs.ipfs.tech-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-specs.ipfs.tech-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-specs.ipfs.tech.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-specs.ipfs.tech-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-specs.ipfs.tech-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-specs.ipfs.tech-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-specs.ipfs.tech-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/strn.network.md b/content.en/websites/strn.network.md index 974342726..c59c3cb02 100644 --- a/content.en/websites/strn.network.md +++ b/content.en/websites/strn.network.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-strn.network-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-strn.network-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-strn.network.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-strn.network-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-strn.network-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-strn.network-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-strn.network.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-strn.network-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-strn.network-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-strn.network-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-strn.network.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-strn.network-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-strn.network-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-strn.network-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-strn.network-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster. diff --git a/content.en/websites/web3.storage.md b/content.en/websites/web3.storage.md index 196ad6ed0..74b0c06e0 100644 --- a/content.en/websites/web3.storage.md +++ b/content.en/websites/web3.storage.md @@ -11,9 +11,9 @@ We initially present an Overview of the performance, followed by Trends, i.e., t ## Overview -### Performance over Kubo {#website-snapshot-performance-gauge-kubo} +### Performance over Kubo {#website-snapshot-performance-gauge-ipfs-kubo} -{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-web3.storage-KUBO.json" height="300px" id="website-snapshot-performance-gauge-kubo" >}} +{{< plotly json="../../plots/latest/website-snapshot-performance-gauge-web3.storage-IPFS-KUBO.json" height="300px" id="website-snapshot-performance-gauge-ipfs-kubo" >}} The graph presents a comparison of two crucial Kubo web performance metrics (90th percentile): Time to First Byte (TTFB) and First Contentful Paint (FCP). The data displayed shows the 90th percentile of both metrics and was gathered during the previous week. @@ -26,9 +26,9 @@ The graph utilizes shaded areas in different colors to denote performance catego The website measurement data can be viewed from two distinct perspectives: as a snapshot of the most recent data points (see [Snapshot](#snapshot)) and as a progression over time. This section provides insights into the overall trends by presenting metrics over time. Analyzing data solely as a snapshot can offer a momentary glimpse into the current state, but it may lack context and fail to capture the bigger picture. However, by examining data over time, patterns and trends emerge, allowing for a deeper understanding of the data's trajectory and potential future outcomes. This section's focus on metrics over time enhances the ability to identify and interpret these trends, enabling informed decision-making and strategic planning. -### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics} +### Web-Vitals Metrics (90th Percentile) {#website-trend-metrics-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-metrics-web3.storage.json" height="300px" id="website-trend-metrics" >}} +{{< plotly json="../../plots/latest/website-trend-metrics-web3.storage-IPFS-KUBO.json" height="300px" id="website-trend-metrics-ipfs-kubo" >}} The [Web-Vitals](https://web.dev/vitals/) Metrics graph provides high-level insights into the websites' performance, allowing you to monitor key metrics over the past 30 days. @@ -64,9 +64,9 @@ For the above graph, we obtained the PeerIDs from two hosting providers/pinning More importantly, if both bars (for Fleek and the PL Cluster) are at zero, then this very likely means that the website has no stable providers on the IPFS DHT. -### IPFS Retrieval Errors {#website-trend-retrieval-errors-kubo} +### IPFS Retrieval Errors {#website-trend-retrieval-errors-ipfs-kubo} -{{< plotly json="../../plots/latest/website-trend-retrieval-errors-web3.storage-KUBO.json" height="350px" id="website-trend-retrieval-errors-kubo" >}} +{{< plotly json="../../plots/latest/website-trend-retrieval-errors-web3.storage-IPFS-KUBO.json" height="350px" id="website-trend-retrieval-errors-ipfs-kubo" >}} This graph shows error rates of website requests via Kubo over the past 30 days. It combines measurements from all our measurement regions. The x-axis represents days, while the y-axis displays error rates. Additionally, black markers indicate the actual number of requests (from our infrastructure) per day with the corresponding count shown on the right handside y-axis. This graph offers a concise overview of error rates and probing volume, aiding users in assessing website availability in IPFS. @@ -74,9 +74,9 @@ This graph shows error rates of website requests via Kubo over the past 30 days. This section presents a snapshot of the most recent week's data, offering a concise overview of the current state. By focusing on this specific timeframe, readers gain immediate insights into the prevailing metrics and performance indicators. While a single snapshot may lack the context of historical data, it serves as a valuable tool for assessing the present situation. Analyzing the data in this way allows for quick identification of key trends, patterns, and potential areas of concern or success. This section's emphasis on the snapshot of data enables decision-makers to make informed, real-time assessments and take immediate actions based on the current status. -### Website Probes {#website-snapshot-probes-count} +### Website Probes {#website-snapshot-probes-count-kubo} -{{< plotly json="../../plots/latest/website-snapshot-probes-count-web3.storage.json" height="150px" id="website-snapshot-probes-count" >}} +{{< plotly json="../../plots/latest/website-snapshot-probes-count-web3.storage-KUBO.json" height="150px" id="website-snapshot-probes-count-kubo" >}} We perform on average 500 requests per week from each of the seven AWS regions where our infrastructure is deployed using [Kubo](https://github.com/ipfs/kubo) @@ -84,17 +84,17 @@ and HTTP. Above is the number of requests for each of the request methods. The n vary depending on errors during the fetching process, which we look into more detail further down. -### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-kubo-eu-central-1} +### Web-Vitals Metrics measured from Europe using Kubo {#website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1} -{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-web3.storage-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-kubo-eu-central-1" >}} +{{< plotly json="../../plots/latest/website-snapshot-web-vitals-barchart-web3.storage-IPFS-KUBO-eu-central-1.json" height="400px" id="website-snapshot-web-vitals-barchart-ipfs-kubo-eu-central-1" >}} [What do `Fatal`, `Undefined`, `Poor` etc. mean?](#values) During the designated time period (indicated in the bottom right corner), we conducted multiple measurements for the five metrics shown along the x-axis. The y-axis represents the proportion of measurement outcomes from the total number of measurements specifically taken in the eu-central-1 region. This visual representation allows us to analyze the distribution of the metric ratings within the specified time frame for that particular region. -### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors} +### Website Probing Success rate from different Regions {#website-snapshot-retrieval-errors-kubo} -{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-web3.storage.json" height="350px" id="website-snapshot-retrieval-errors" >}} +{{< plotly json="../../plots/latest/website-snapshot-retrieval-errors-web3.storage-KUBO.json" height="350px" id="website-snapshot-retrieval-errors-kubo" >}} While the graph on [IPFS Retrieval Errors](#website-trend-retrieval-errors-kubo) further up shows the Kubo retrieval errors over time, this graph shows the retrieval errors as seen from different regions in the specified time interval (bottom right corner). Alongside the Kubo retrieval outcomes it also shows the HTTP results. The black markers again show the number of probes performed in each region with each request method (count shown on the right handside y-axis). @@ -104,21 +104,21 @@ This series of graphs presents a comprehensive analysis of latency performance a To provide context and aid interpretation, the graphs incorporate shaded background areas. These areas are color-coded, with green representing good performance, yellow indicating areas that require improvement, and red denoting poor performance. The thresholds are defined by [web-vitals](https://web.dev/vitals) (more info below in [Metrics](#metrics)). By analyzing the position of the CDF lines in relation to the shaded regions, one can quickly identify regions with superior, average, or subpar latency performance for TTFB, FCP, and LCP. -#### Time To First Byte {#website-snapshot-metric-cdf-kubo-ttfb} +#### Time To First Byte {#website-snapshot-metric-cdf-ipfs-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-kubo-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-IPFS-KUBO-ttfb.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-ttfb" >}} -#### First Contentful Paint {#website-snapshot-metric-cdf-kubo-fcp} +#### First Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-fcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-fcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-IPFS-KUBO-fcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-fcp" >}} -#### Largest Contentful Paint {#website-snapshot-metric-cdf-kubo-lcp} +#### Largest Contentful Paint {#website-snapshot-metric-cdf-ipfs-kubo-lcp} -{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-kubo-lcp" >}} +{{< plotly json="../../plots/latest/website-snapshot-metric-cdf-web3.storage-IPFS-KUBO-lcp.json" height="320px" id="website-snapshot-metric-cdf-ipfs-kubo-lcp" >}} -### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-ttfb} +### Kubo vs HTTP Latency Comparison (TTFB) {#website-snapshot-http-ratio-kubo-ttfb} -{{< plotly json="../../plots/latest/website-snapshot-http-ratio-web3.storage-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-ttfb" >}} +{{< plotly json="../../plots/latest/website-snapshot-http-ratio-web3.storage-KUBO-ttfb.json" height="500px" id="ebsite-snapshot-http-ratio-kubo-ttfb" >}} We calculated different percentiles for the Time To First Byte (TTFB) metric in different regions for website requests that were done via Kubo and via plain HTTP. Then we divided the values of Kubo by the ones from HTTP. A resulting number greater than `1` means that Kubo was slower than HTTP in that region for that percentile. Conversely, a number less than `1` means that Kubo was faster.