feat(k8s): Extract helm charts into a separate repo

datahub-kubernetes/README.md

@@ -1,135 +1,14 @@
----
-title: "Deploying with Kubernetes"
----
-
-# Deploying Datahub with Kubernetes
-
-## Introduction
-[This directory](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes) provides 
-the Kubernetes [Helm](https://helm.sh/) charts for deploying [Datahub](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/datahub) and it's [dependencies](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/prerequisites) 
-(Elasticsearch, optionally Neo4j, MySQL, and Kafka) on a Kubernetes cluster.
-
-## Setup
-1. Set up a kubernetes cluster
-   - In a cloud platform of choice like [Amazon EKS](https://aws.amazon.com/eks), 
-     [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine), 
-     and [Azure Kubernetes Service](https://azure.microsoft.com/en-us/services/kubernetes-service/) OR
-   - In local environment using [Minikube](https://minikube.sigs.k8s.io/docs/). 
-     Note, more than 7GB of RAM is required to run Datahub and it's dependencies 
-2. Install the following tools: 
-   - [kubectl](https://kubernetes.io/docs/tasks/tools/) to manage kubernetes resources
-   - [helm](https://helm.sh/docs/intro/install/) to deploy the resources based on helm charts. 
-     Note, we only support Helm 3.
-
-## Components
-Datahub consists of 4 main components: [GMS](https://datahubproject.io/docs/gms), 
-[MAE Consumer](https://datahubproject.io/docs/metadata-jobs/mae-consumer-job), 
-[MCE Consumer](https://datahubproject.io/docs/metadata-jobs/mce-consumer-job), and 
-[Frontend](https://datahubproject.io/docs/datahub-frontend). Kubernetes deployment 
-for each of the components are defined as subcharts under the main 
-[Datahub](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/datahub) 
-helm chart.
-
-The main components are powered by 4 external dependencies:
-- Kafka
-- Local DB (MySQL, Postgres, MariaDB)
-- Search Index (Elasticsearch)
-- Graph Index (Supports either Neo4j or Elasticsearch)
-
-The dependencies must be deployed before deploying Datahub. We created a separate 
-[chart](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/prerequisites) 
-for deploying the dependencies with example configuration. They could also be deployed 
-separately on-prem or leveraged as managed services. To remove your dependency on Neo4j,
-set enabled to false in the `datahub-kubernetes/prerequisites/values.yaml` file.
-Then, override the `graph_service_impl` field in `datahub-kubernetes/datahub/values.yaml` to
-have the value `elasticsearch` instead of `neo4j`.
-
-## Quickstart
-Assuming kubectl context points to the correct kubernetes cluster, first create kubernetes secrets that contain MySQL and Neo4j passwords. 
-
-```(shell)
-kubectl create secret generic mysql-secrets --from-literal=mysql-root-password=datahub
-kubectl create secret generic neo4j-secrets --from-literal=neo4j-password=datahub
-```
-
-The above commands sets the passwords to "datahub" as an example. Change to any password of choice. 
-
-Second, deploy the dependencies by running the following
-
-```(shell)
-(cd prerequisites && helm dep update)
-helm install prerequisites prerequisites/
-```
-
-Note, after changing the configurations in the values.yaml file, you can run 
-
-```(shell)
-helm upgrade prerequisites prerequisites/
-```
-
-To just redeploy the dependencies impacted by the change. 
-
-Run `kubectl get pods` to check whether all the pods for the dependencies are running. 
-You should get a result similar to below.
-
-```
-NAME                                               READY   STATUS      RESTARTS   AGE
-elasticsearch-master-0                             1/1     Running     0          62m
-elasticsearch-master-1                             1/1     Running     0          62m
-elasticsearch-master-2                             1/1     Running     0          62m
-prerequisites-cp-schema-registry-cf79bfccf-kvjtv   2/2     Running     1          63m
-prerequisites-kafka-0                              1/1     Running     2          62m
-prerequisites-mysql-0                              1/1     Running     1          62m
-prerequisites-neo4j-community-0                    1/1     Running     0          52m
-prerequisites-zookeeper-0                          1/1     Running     0          62m
-```
-
-deploy Datahub by running the following
-
-```(shell)
-helm install datahub datahub/
-```
-
-Values in [values.yaml](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/datahub/values.yaml) 
-have been preset to point to the dependencies deployed using the [prerequisites](https://github.com/linkedin/datahub/tree/master/datahub-kubernetes/prerequisites) 
-chart with release name "prerequisites". If you deployed the helm chart using a different release name, update the quickstart-values.yaml file accordingly before installing. 
-
-Run `kubectl get pods` to check whether all the datahub pods are running. You should get a result similar to below.
-
-```
-NAME                                               READY   STATUS      RESTARTS   AGE
-datahub-datahub-frontend-84c58df9f7-5bgwx          1/1     Running     0          4m2s
-datahub-datahub-gms-58b676f77c-c6pfx               1/1     Running     0          4m2s
-datahub-datahub-mae-consumer-7b98bf65d-tjbwx       1/1     Running     0          4m3s
-datahub-datahub-mce-consumer-8c57d8587-vjv9m       1/1     Running     0          4m2s
-datahub-elasticsearch-setup-job-8dz6b              0/1     Completed   0          4m50s
-datahub-kafka-setup-job-6blcj                      0/1     Completed   0          4m40s
-datahub-mysql-setup-job-b57kc                      0/1     Completed   0          4m7s
-elasticsearch-master-0                             1/1     Running     0          97m
-elasticsearch-master-1                             1/1     Running     0          97m
-elasticsearch-master-2                             1/1     Running     0          97m
-prerequisites-cp-schema-registry-cf79bfccf-kvjtv   2/2     Running     1          99m
-prerequisites-kafka-0                              1/1     Running     2          97m
-prerequisites-mysql-0                              1/1     Running     1          97m
-prerequisites-neo4j-community-0                    1/1     Running     0          88m
-prerequisites-zookeeper-0                          1/1     Running     0          97m
-```
-
-You can run the following to expose the frontend locally. Note, you can find the pod name using the command above. 
-In this case, the datahub-frontend pod name was `datahub-datahub-frontend-84c58df9f7-5bgwx`. 
-
-```(shell)
-kubectl port-forward <datahub-frontend pod name> 9002:9002
-```
-
-You should be able to access the frontend via http://localhost:9002. 
-
-Once you confirm that the pods are running well, you can set up ingress for datahub-frontend 
-to expose the 9002 port to the public.  
-## Other useful commands
-
-| Command | Description | 
-|-----|------|
-| helm uninstall datahub | Remove DataHub |
-| helm ls | List of Helm charts |
-| helm history | Fetch a release history | 
+DataHub Helm Charts
+==============================================================================
+
+> **Notice**: As of July 2021, we have migrated the helm charts to a separate [repo](https://github.com/acryldata/datahub-helm)
+> to allow automatic releases and better control over the discoverability of the charts.
+>
+> We have also published the helm charts to `https://helm.datahubproject.io`. You can deploy without referring to the codebase by running the following commands.
+> 
+> ```
+> helm repo add datahub https://helm.datahubproject.io
+> helm install datahub datahub/datahub
+>```
+>
+> Please contribute any changes to the new repo.