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Clean up SHL case study
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*Nicolas Seymour-Smith, February 2024*

### 3.1 Context ###
[SHL Digital](https://sussexhumanitieslab.wordpress.com/) is a multi-disciplinary digital humanities lab that relies on digital infrastructure to support research and collaboration. In many cases the requirements of these infrastructure requirements cannot be met by running software on personal computers, e.g. because the computational processing power required is too high, or the hosted service requires a permanent online presence.
[SHL Digital](https://sussexhumanitieslab.wordpress.com/) is a multi-disciplinary digital humanities lab that relies on digital infrastructure to support research and collaboration. In many cases these infrastructure requirements cannot be met by running software on personal computers, e.g. because the computational processing power required is too high, or the hosted service requires a permanent online presence.

To meet these needs so far, the SHL Digital has been relying on its own servers and staff to run 'containers' that provide researchers with isolated platforms to run their software. These containers can manage most computational tasks (short of machine-learning applications that require high amounts of GPU power), and can run any custom software that runs on the Linux operating system. In late 2023 and early 2024 we carried out a review, including estimates of carbon impacts.
To meet these needs so far, the SHL Digital has been relying on its own servers and staff to provide researchers with a platform to run their software. This platform can manage most computational tasks (short of machine-learning applications that require high amounts of GPU power), and can run any custom software that runs on the Linux operating system. In late 2023 and early 2024 we carried out a review, including estimates of carbon impacts.

### 3.2 Hardware and basic CO2 estimates ###
SHL Digital servers are three high-power computers which were bought together in 2018. These were fairly standard commercial servers for the time, and Dell provides their own estimates of the CO2 impact of these servers based on a 4 year life span:
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* [CO2.js](https://github.com/thegreenwebfoundation/co2.js), which can help us calculate the emissions associated with the number of bytes transmitted from our websites to visitors across internet infrastructure that has its own CO2 impact.

### 3.4 Monitoring real computational usage ###
Plenty of tools and services exist for aggregating CPU usage over long periods. netdata.cloud provides one such free tool that is very simple to install on all platforms and provides a simple web based user interface that can be accessed either locally or through the netdata.cloud website.
Plenty of tools and services exist for aggregating CPU usage over long periods. [netdata.cloud](http://netdata.cloud) provides one such free tool that is very simple to install on all platforms and provides a simple web based user interface that can be accessed either locally or through the netdata.cloud website.

Using this tool to monitor the CPU load of our servers for 2 weeks, we got average values of 7.65%, and 1% for our R440 servers, and 1% for our R750xd server. Entering this and other relevant details into [http://calculator.green-algorithms.org/](http://calculator.green-algorithms.org/), we got 945g and 891g of CO2 per day for our R440s and 450g for our R750xd server.

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All told, the total CO2 impact based on ’real usage’ of processing power is estimated at 2.3 kg/day or 834 kg/year.

### 3.5 Monitoring real data transmission ###
It’s also possible to get the total data transmission values from the netdata.cloud service, but it’s a little more difficult to coax out the value as a total rather than a rate, and so instead I used a separate tool called goaccess. There’s a handy tutorial for setting this up for long term monitoring here: [https://arnaudr.io/2020/08/10/goaccess-14-a-detailed-tutorial/](https://arnaudr.io/2020/08/10/goaccess-14-a-detailed-tutorial/)
It’s also possible to get the total data transmission values from the netdata.cloud service, but it’s a little more difficult to coax out the value as a total rather than a rate, and so instead I used a separate tool called [goaccess](https://goaccess.io/). There’s a handy tutorial for setting this up for long term monitoring [here](https://arnaudr.io/2020/08/10/goaccess-14-a-detailed-tutorial/).

This provided a monthly data transmission value of 4 GB over a period of a month. A handy tutorial for using CO2.js to calculate CO2 impact from this number can be found here: [https://developers.thegreenwebfoundation.org/co2js/tutorials/getting-started-browser/](https://developers.thegreenwebfoundation.org/co2js/tutorials/getting-started-browser/)
This provided a monthly data transmission value of 4 GB over a period of a month. A handy tutorial for using CO2.js to calculate CO2 impact from this number can be found [here](https://developers.thegreenwebfoundation.org/co2js/tutorials/getting-started-browser/).

This calculation gave us a value of 1.4 kg/month, or 17kg/year. There’s a possibility that adding this value to the 834 kg/year from computational usage involves some double-counting. We’d have to look into the algorithm that co2.js is using to work out the breakdown of CO2 impact in terms of internet infrastructure and computational power to work out how much, if any.

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### 3.7 Conclusion

This work was undertaken as part of a broader analysis of SHL Digital's resources and needs, in order to plan for efficient provision of these services in the future. This analysis allowed us to weigh sustainability as a factor into those plans. From this perspective, we can ask the following question:
This work was undertaken as part of a broader analysis of SHL Digital's resources and needs, in order to plan for efficient provision of these services in the future. This analysis allowed us to weigh sustainability as a factor into those plans. From this perspective, we can ask the following questions:

* Could downsizing our server infrastructure to more closely match our real-terms usage and traffic reduce our carbon impact (by reducing manufacturing related CO2 and basic power requirements) without running us into issues of procesing power? At first glance this seems likely.
* Whether downsizing could also be accompanied by migration to externally hosted and or shared services could be an interesting follow on.

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