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| .. | ||
| production_cluster | ||
| es-rc.yaml | ||
| es-svc.yaml | ||
| README.md | ||
| service-account.yaml | ||
Elasticsearch for Kubernetes
Kubernetes makes it trivial for anyone to easily build and scale Elasticsearch clusters. Here, you'll find how to do so.
Current Elasticsearch version is 1.7.1.
Current pod descriptors use an emptyDir for storing data in each data node container. This is meant to be for the sake of simplicity and should be adapted according to your storage needs.
Docker image
The pre-built image used in this example will not be supported. Feel free to fork to fit your own needs, but keep in mind that you will need to change Kubernetes descriptors accordingly.
Deploy
Let's kickstart our cluster with 1 instance of Elasticsearch.
kubectl create -f examples/elasticsearch/service-account.yaml
kubectl create -f examples/elasticsearch/es-svc.yaml
kubectl create -f examples/elasticsearch/es-rc.yaml
Let's see if it worked:
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
es-kfymw 1/1 Running 0 7m
kube-dns-p3v1u 3/3 Running 0 19m
$ kubectl logs es-kfymw
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
[2015-08-30 10:01:31,946][INFO ][node ] [Hammerhead] version[1.7.1], pid[7], build[b88f43f/2015-07-29T09:54:16Z]
[2015-08-30 10:01:31,946][INFO ][node ] [Hammerhead] initializing ...
[2015-08-30 10:01:32,110][INFO ][plugins ] [Hammerhead] loaded [cloud-kubernetes], sites []
[2015-08-30 10:01:32,153][INFO ][env ] [Hammerhead] using [1] data paths, mounts [[/data (/dev/sda9)]], net usable_space [14.4gb], net total_space [15.5gb], types [ext4]
[2015-08-30 10:01:37,188][INFO ][node ] [Hammerhead] initialized
[2015-08-30 10:01:37,189][INFO ][node ] [Hammerhead] starting ...
[2015-08-30 10:01:37,499][INFO ][transport ] [Hammerhead] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/10.244.48.2:9300]}
[2015-08-30 10:01:37,550][INFO ][discovery ] [Hammerhead] myesdb/n2-6uu_UT3W5XNrjyqBPiA
[2015-08-30 10:01:43,966][INFO ][cluster.service ] [Hammerhead] new_master [Hammerhead][n2-6uu_UT3W5XNrjyqBPiA][es-kfymw][inet[/10.244.48.2:9300]]{master=true}, reason: zen-disco-join (elected_as_master)
[2015-08-30 10:01:44,010][INFO ][http ] [Hammerhead] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/10.244.48.2:9200]}
[2015-08-30 10:01:44,011][INFO ][node ] [Hammerhead] started
[2015-08-30 10:01:44,042][INFO ][gateway ] [Hammerhead] recovered [0] indices into cluster_state
So we have a 1-node Elasticsearch cluster ready to handle some work.
Scale
Scaling is as easy as:
kubectl scale --replicas=3 rc es
Did it work?
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
es-78e0s 1/1 Running 0 8m
es-kfymw 1/1 Running 0 17m
es-rjmer 1/1 Running 0 8m
kube-dns-p3v1u 3/3 Running 0 30m
Let's take a look at logs:
$ kubectl logs es-kfymw
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
log4j:WARN No such property [maxBackupIndex] in org.apache.log4j.DailyRollingFileAppender.
[2015-08-30 10:01:31,946][INFO ][node ] [Hammerhead] version[1.7.1], pid[7], build[b88f43f/2015-07-29T09:54:16Z]
[2015-08-30 10:01:31,946][INFO ][node ] [Hammerhead] initializing ...
[2015-08-30 10:01:32,110][INFO ][plugins ] [Hammerhead] loaded [cloud-kubernetes], sites []
[2015-08-30 10:01:32,153][INFO ][env ] [Hammerhead] using [1] data paths, mounts [[/data (/dev/sda9)]], net usable_space [14.4gb], net total_space [15.5gb], types [ext4]
[2015-08-30 10:01:37,188][INFO ][node ] [Hammerhead] initialized
[2015-08-30 10:01:37,189][INFO ][node ] [Hammerhead] starting ...
[2015-08-30 10:01:37,499][INFO ][transport ] [Hammerhead] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/10.244.48.2:9300]}
[2015-08-30 10:01:37,550][INFO ][discovery ] [Hammerhead] myesdb/n2-6uu_UT3W5XNrjyqBPiA
[2015-08-30 10:01:43,966][INFO ][cluster.service ] [Hammerhead] new_master [Hammerhead][n2-6uu_UT3W5XNrjyqBPiA][es-kfymw][inet[/10.244.48.2:9300]]{master=true}, reason: zen-disco-join (elected_as_master)
[2015-08-30 10:01:44,010][INFO ][http ] [Hammerhead] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/10.244.48.2:9200]}
[2015-08-30 10:01:44,011][INFO ][node ] [Hammerhead] started
[2015-08-30 10:01:44,042][INFO ][gateway ] [Hammerhead] recovered [0] indices into cluster_state
[2015-08-30 10:08:02,517][INFO ][cluster.service ] [Hammerhead] added {[Tenpin][2gv5MiwhRiOSsrTOF3DhuA][es-78e0s][inet[/10.244.54.4:9300]]{master=true},}, reason: zen-disco-receive(join from node[[Tenpin][2gv5MiwhRiOSsrTOF3DhuA][es-78e0s][inet[/10.244.54.4:9300]]{master=true}])
[2015-08-30 10:10:10,645][INFO ][cluster.service ] [Hammerhead] added {[Evilhawk][ziTq2PzYRJys43rNL2tbyg][es-rjmer][inet[/10.244.33.3:9300]]{master=true},}, reason: zen-disco-receive(join from node[[Evilhawk][ziTq2PzYRJys43rNL2tbyg][es-rjmer][inet[/10.244.33.3:9300]]{master=true}])
So we have a 3-node Elasticsearch cluster ready to handle more work.
Access the service
Don't forget that services in Kubernetes are only acessible from containers in the cluster. For different behavior you should configure the creation of an external load-balancer. While it's supported within this example service descriptor, its usage is out of scope of this document, for now.
$ kubectl get service elasticsearch
NAME LABELS SELECTOR IP(S) PORT(S)
elasticsearch component=elasticsearch component=elasticsearch 10.100.108.94 9200/TCP
9300/TCP
From any host on your cluster (that's running kube-proxy), run:
$ curl 10.100.108.94:9200
You should see something similar to the following:
{
"status" : 200,
"name" : "Hammerhead",
"cluster_name" : "myesdb",
"version" : {
"number" : "1.7.1",
"build_hash" : "b88f43fc40b0bcd7f173a1f9ee2e97816de80b19",
"build_timestamp" : "2015-07-29T09:54:16Z",
"build_snapshot" : false,
"lucene_version" : "4.10.4"
},
"tagline" : "You Know, for Search"
}
Or if you want to check cluster information:
curl 10.100.108.94:9200/_cluster/health?pretty
You should see something similar to the following:
{
"cluster_name" : "myesdb",
"status" : "green",
"timed_out" : false,
"number_of_nodes" : 3,
"number_of_data_nodes" : 3,
"active_primary_shards" : 0,
"active_shards" : 0,
"relocating_shards" : 0,
"initializing_shards" : 0,
"unassigned_shards" : 0,
"delayed_unassigned_shards" : 0,
"number_of_pending_tasks" : 0,
"number_of_in_flight_fetch" : 0
}