This image is using Fabric8's great work around the kubernetes plugin for elasticsearch and their image as parent
Elasticsearch best-practices recommend to separate nodes in three roles:
- Master nodes - intended for clustering management only, no data, no HTTP API
- Client nodes - intended for client usage, no data, with HTTP
- API Data nodes - intended for storing and indexing your data, no HTTP API
We use 2 services as well:
- One to target the client pods so that all requests to the cluster go through the client nodes
- A headless service to list all cluster endpoints managed by RC's and petset
Changes for PetSet
Handle downscales so that no data loss occurs (using lifecycle hooks). For more info click pre-stop-hook
This uses Cinder volumes to mount to the data nodes. You can change the storage of cinder volumes as needed in es-petset.yaml in the section storage: "100Gi"
Given this, I'm going to demonstrate how to provision a production grade ES consisting of 3 master, 2 client and 3 data nodes
kubectl create -f es-client.yaml
kubectl create -f es-client-svc.yaml
kubectl create -f es-headless-svc.yaml
kubectl create -f es-master.yaml
kubectl create -f es-petset.yaml
Wait for all the pods to be in Running state.
To get the http end point of elasticsearch cluster, run
kubectl get services es-client --namespace=<namespace>
EXTERNAL-IP is the http endpoint for elasticsearch cluster and can be accessed from outside the cluster as well
If you have to scale master/client/petset, just increase the replicas to the desired number
kubectl scale petset es-data --replicas=4 --namespace=kchitta