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quick-start

README.md

Quick-start Navigator - Elasticsearch

Here we're going to deploy a distributed and scalable Elasticsearch cluster using the examples provided in this repository. This will involve first deploying Navigator, and then creating an ElasticsearchCluster resource. All management of the Elasticsearch cluster will be through changes to the ElasticsearchCluster manifest.

  1. Install Navigator using Helm
$ helm install contrib/charts/navigator --name navigator --namespace navigator --wait

You should see the Navigator service start in the navigator namespace:

$ kubectl get pod -n navigator
NAME                        READY     STATUS         RESTARTS   AGE
navigator-745449320-dcgms   1/1       Running        0          30s
  1. We can now create a new ElasticsearchCluster:
$ kubectl create -f docs/quick-start/es-cluster-demo.yaml

This will deploy a multi-node Elasticsearch cluster, split into nodes of 3 roles: master, client (ingest) and data. There will be 4 data nodes, each with a 10GB PV, 2 client nodes, and 3 master nodes. All of the options you may need for configuring your cluster are documented on the supported types page.

$ kubectl get pod
NAME                              READY     STATUS    RESTARTS   AGE
es-demo-client-3995124321-5rc6g   1/1       Running   0          7m
es-demo-client-3995124321-9zrv9   1/1       Running   0          7m
es-demo-data-0                    1/1       Running   0          7m
es-demo-data-1                    1/1       Running   0          5m
es-demo-data-2                    1/1       Running   0          3m
es-demo-data-3                    1/1       Running   0          1m
es-demo-master-554549909-00162    1/1       Running   0          7m
es-demo-master-554549909-pp557    1/1       Running   0          7m
es-demo-master-554549909-vjgrt    1/1       Running   0          7m
  1. Scale the data nodes:

Scaling the nodes can be done by modifying your ElasticsearchCluster manifest. Currently this is only possible using kubectl replace, due to bugs with the way ThirdPartyResource's are handled in kubectl 1.5.

Edit your manifest & increase the number of replicas in the data node pool, then run:

$ kubectl replace -f examples/es-cluster-example.yaml
$ kubectl get pod
NAME                              READY     STATUS    RESTARTS   AGE
es-demo-client-3995124321-5rc6g   1/1       Running   0          9m
es-demo-client-3995124321-9zrv9   1/1       Running   0          9m
es-demo-data-0                    1/1       Running   0          9m
es-demo-data-1                    1/1       Running   0          7m
es-demo-data-2                    1/1       Running   0          5m
es-demo-data-3                    1/1       Running   0          3m
es-demo-data-4                    0/1       Running   0          29s
es-demo-master-554549909-00162    1/1       Running   0          9m
es-demo-master-554549909-pp557    1/1       Running   0          9m
es-demo-master-554549909-vjgrt    1/1       Running   0          9m

You should see new data nodes being added into your cluster gradually. Once all are in the Running state, we can try a scale down. Do the same as before, but instead reduce the number of replicas in the data node pool. Then run a kubectl replace again:

$ kubectl replace -f examples/es-cluster-example.yaml
$ kubectl get pod
NAME                              READY     STATUS        RESTARTS   AGE
es-demo-client-3995124321-5rc6g   1/1       Running       0          10m
es-demo-client-3995124321-9zrv9   1/1       Running       0          10m
es-demo-data-0                    1/1       Running       0          10m
es-demo-data-1                    1/1       Running       0          8m
es-demo-data-2                    1/1       Running       0          6m
es-demo-data-3                    1/1       Running       0          4m
es-demo-data-4                    1/1       Terminating   0          2m
es-demo-master-554549909-00162    1/1       Running       0          10m
es-demo-master-554549909-pp557    1/1       Running       0          10m
es-demo-master-554549909-vjgrt    1/1       Running       0          10m

Upon scale-down, the Elasticsearch nodes will mark themselves as non-allocatable. This will trigger Elasticsearch to re-allocate any shards currently on the nodes being scaled down, meaning your data will be safely relocated within the cluster.