From 11c0f4d2b3c89490b8b422295549fc976dab95ec Mon Sep 17 00:00:00 2001
From: Andrey Velichkevich <andrey.velichkevich@gmail.com>
Date: Thu, 11 Jan 2024 17:53:06 +0000
Subject: [PATCH] Add Kubeflow Website links to README

---
 README.md              | 23 +++++++-----
 docs/quick-start-v1.md | 82 ------------------------------------------
 2 files changed, 15 insertions(+), 90 deletions(-)
 delete mode 100644 docs/quick-start-v1.md

diff --git a/README.md b/README.md
index 2dee21f2b1..9fc735ef54 100644
--- a/README.md
+++ b/README.md
@@ -6,8 +6,9 @@
 
 ## Overview
 
-Starting from v1.3, this training operator provides Kubernetes custom resources that makes it easy to
-run distributed or non-distributed TensorFlow/PyTorch/Apache MXNet/XGBoost/MPI jobs on Kubernetes.
+Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and
+scalable distributed training of machine learning (ML) models created with various ML frameworks
+such as PyTorch, Tensorflow, XGBoost, MPI, Paddle and others.
 
 > Note: Before v1.2 release, Kubeflow Training Operator only supports TFJob on Kubernetes.
 
@@ -23,7 +24,7 @@ run distributed or non-distributed TensorFlow/PyTorch/Apache MXNet/XGBoost/MPI j
 
 ## Prerequisites
 
-- Version >= 1.23 of Kubernetes cluster and `kubectl`
+- Version >= 1.25 of Kubernetes cluster and `kubectl`
 
 ## Installation
 
@@ -36,7 +37,7 @@ kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/stand
 ### Stable Release
 
 ```bash
-kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/standalone?ref=v1.5.0"
+kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/standalone?ref=v1.7.0"
 ```
 
 ### TensorFlow Release Only
@@ -49,7 +50,8 @@ kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/stand
 
 ### Python SDK for Kubeflow Training Operator
 
-Training Operator provides Python SDK for the custom resources. More docs are available in [sdk/python](sdk/python) folder.
+Training Operator provides Python SDK for the custom resources. For the APIs check
+[the SDK `TrainingClient`](sdk/python/kubeflow/training/api/training_client.py).
 
 Use `pip install` command to install the latest release of the SDK:
 
@@ -57,9 +59,12 @@ Use `pip install` command to install the latest release of the SDK:
 pip install kubeflow-training
 ```
 
-## Quick Start
+Training Operator controller and Python SDK have the same release versions.
 
-Please refer to the [quick-start-v1.md](docs/quick-start-v1.md) and [Kubeflow Training User Guide](https://www.kubeflow.org/docs/guides/components/tftraining/) for more information.
+## Quickstart
+
+Please refer to the [getting started guide](https://www.kubeflow.org/docs/components/training/overview/#getting-started)
+to quickly create your first Training Operator Job.
 
 ## API Documentation
 
@@ -97,7 +102,9 @@ The following table lists the most recent few versions of the operator.
 | `v1.3.x`               | `v1`        | 1.18+              |
 | `v1.4.x`               | `v1`        | 1.23+              |
 | `v1.5.x`               | `v1`        | 1.23+              |
-| `latest` (master HEAD) | `v1`        | 1.23+              |
+| `v1.6.x`               | `v1`        | 1.23+              |
+| `v1.7.x`               | `v1`        | 1.25+              |
+| `latest` (master HEAD) | `v1`        | 1.25+              |
 
 ## Acknowledgement
 
diff --git a/docs/quick-start-v1.md b/docs/quick-start-v1.md
deleted file mode 100644
index 17f687c4cb..0000000000
--- a/docs/quick-start-v1.md
+++ /dev/null
@@ -1,82 +0,0 @@
-# Testing v1
-
-TFJob is currently in v1. The quick start shows an example of TFJob.
-For more details please refer to [developer_guide.md](development/developer_guide.md).
-
-## Create a TFJob
-
-Please see the [example](../examples/tensorflow/dist-mnist/README.md) to create a TFJob.
-
-## Monitor your job
-
-To get the status of your job
-
-```
-kubectl get -o yaml tfjobs $JOB
-```
-
-Here is sample output for an example job
-
-```yaml
-apiVersion: kubeflow.org/v1
-kind: TFJob
-metadata:
-  creationTimestamp: 2019-03-06T09:50:49Z
-  generation: 1
-  name: dist-mnist-for-e2e-test
-  namespace: kubeflow
-  resourceVersion: "16575458"
-  selfLink: /apis/kubeflow.org/v1/namespaces/kubeflow/tfjobs/dist-mnist-for-e2e-test
-  uid: 526545f8-3ff5-11e9-a818-0016ac101ba4
-spec:
-  cleanPodPolicy: Running
-  tfReplicaSpecs:
-    PS:
-      replicas: 2
-      restartPolicy: Never
-      template:
-        metadata:
-          creationTimestamp: null
-        spec:
-          containers:
-            - image: kubeflow/tf-dist-mnist-test:1.0
-              name: tensorflow
-              ports:
-                - containerPort: 2222
-                  name: tfjob-port
-              resources: {}
-    Worker:
-      replicas: 4
-      restartPolicy: Never
-      template:
-        metadata:
-          creationTimestamp: null
-        spec:
-          containers:
-            - image: kubeflow/tf-dist-mnist-test:1.0
-              name: tensorflow
-              ports:
-                - containerPort: 2222
-                  name: tfjob-port
-              resources: {}
-status:
-  conditions:
-    - lastTransitionTime: 2019-03-06T09:50:36Z
-      lastUpdateTime: 2019-03-06T09:50:36Z
-      message: TFJob dist-mnist-for-e2e-test is created.
-      reason: TFJobCreated
-      status: "True"
-      type: Created
-    - lastTransitionTime: 2019-03-06T09:50:57Z
-      lastUpdateTime: 2019-03-06T09:50:57Z
-      message: TFJob dist-mnist-for-e2e-test is running.
-      reason: TFJobRunning
-      status: "True"
-      type: Running
-  replicaStatuses:
-    PS:
-      active: 2
-    Worker:
-      active: 4
-  startTime: 2019-03-06T09:50:48Z
-```