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Configure Elasticsearch Combined Cluster
In Elasticsearch combined cluster, every node can perform as master, data, and ingest nodes simultaneously. In this tutorial, we will see how to configure a combined cluster.
Before You Begin
At first, you need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. If you do not already have a cluster, you can create one by using kind.
Now, install the KubeDB operator in your cluster following the steps here.
To keep things isolated, this tutorial uses a separate namespace called demo throughout this tutorial.
$ kubectl create namespace demo
namespace/demo created
$ kubectl get namespace
NAME STATUS AGE
demo Active 9s
Note: YAML files used in this tutorial are stored in here in GitHub repository kubedb/docs.
Find Available StorageClass
We will have to provide StorageClass in Elasticsearch CR specification. Check available StorageClass in your cluster using the following command,
$ kubectl get storageclass
NAME PROVISIONER RECLAIMPOLICY VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE
standard (default) rancher.io/local-path Delete WaitForFirstConsumer false 1h
Here, we have standard StorageClass in our cluster from Local Path Provisioner.
Use Custom Configuration
Say we want to change the default log directory for our cluster and want to configure disk-based shard allocation. Let’s create the elasticsearch.yml file with our desire configurations.
elasticsearch.yml:
path:
logs: "/usr/share/elasticsearch/data/new-logs-dir"
# For 100gb node space:
# Enable disk-based shard allocation
cluster.routing.allocation.disk.threshold_enabled: true
# prevent Elasticsearch from allocating shards to the node if less than the 15gb of space is available
cluster.routing.allocation.disk.watermark.low: 15gb
# relocate shards away from the node if the node has less than 10gb of free space
cluster.routing.allocation.disk.watermark.high: 10gb
# enforce a read-only index block if the node has less than 5gb of free space
cluster.routing.allocation.disk.watermark.flood_stage: 5gb
Let’s create a k8s secret containing the above configuration where the file name will be the key and the file-content as the value:
apiVersion: v1
kind: Secret
metadata:
name: es-custom-config
namespace: demo
stringData:
elasticsearch.yml: |-
path:
logs: "/usr/share/elasticsearch/data/new-logs-dir"
cluster.routing.allocation.disk.threshold_enabled: true
cluster.routing.allocation.disk.watermark.low: 15gb
cluster.routing.allocation.disk.watermark.high: 10gb
cluster.routing.allocation.disk.watermark.flood_stage: 5gb
$ kubectl apply -f https://github.com/kubedb/docs/raw/v2023.01.17/docs/guides/elasticsearch/configuration/combined-cluster/yamls/config-secret.yaml
secret/es-custom-config created
Now that the config secret is created, it needs to be mention in the Elasticsearch object’s yaml:
apiVersion: kubedb.com/v1alpha2
kind: Elasticsearch
metadata:
name: es-multinode
namespace: demo
spec:
version: xpack-7.9.1-v1
enableSSL: true
replicas: 3
configSecret:
name: es-custom-config # mentioned here!
storageType: Durable
storage:
storageClassName: "standard"
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
terminationPolicy: WipeOut
Now, create the Elasticsearch object by the following command:
$ kubectl apply -f https://github.com/kubedb/docs/raw/v2023.01.17/docs/guides/elasticsearch/configuration/combined-cluster/yamls/es-combined.yaml
elasticsearch.kubedb.com/es-multinode created
Now, wait for the Elasticsearch to become ready:
$ kubectl get es -n demo -w
NAME VERSION STATUS AGE
es-multinode xpack-7.9.1-v1 Provisioning 18s
es-multinode xpack-7.9.1-v1 Provisioning 2m5s
es-multinode xpack-7.9.1-v1 Ready 2m5s
Verify Configuration
Let’s connect to the Elasticsearch cluster that we have created and check the node settings to verify whether our configurations are applied or not:
Connect to the Cluster:
# Port-forward the service to local machine
$ kubectl port-forward -n demo svc/es-multinode 9200
Forwarding from 127.0.0.1:9200 -> 9200
Forwarding from [::1]:9200 -> 9200
Now, our Elasticsearch cluster is accessible at localhost:9200.
Connection information:
Address:
localhost:9200Username:
$ kubectl get secret -n demo es-multinode-elastic-cred -o jsonpath='{.data.username}' | base64 -d elasticPassword:
$ kubectl get secret -n demo es-multinode-elastic-cred -o jsonpath='{.data.password}' | base64 -d ehG7*7SJZ0o9PA05
Now, we will query for settings of all nodes in an Elasticsearch cluster,
$ curl -XGET -k -u 'elastic:ehG7*7SJZ0o9PA05' "https://localhost:9200/_nodes/_all/settings?pretty"
This will return a large JSON with node settings. Here is the prettified JSON response,
{
"_nodes" : {
"total" : 3,
"successful" : 3,
"failed" : 0
},
"cluster_name" : "es-multinode",
"nodes" : {
"_xWvqAU4QJeMaV4MayTgeg" : {
"name" : "es-multinode-0",
"transport_address" : "10.244.0.25:9300",
"host" : "10.244.0.25",
"ip" : "10.244.0.25",
"version" : "7.9.1",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "083627f112ba94dffc1232e8b42b73492789ef91",
"roles" : [
"data",
"ingest",
"master",
"ml",
"remote_cluster_client",
"transform"
],
"attributes" : {
"ml.machine_memory" : "1073741824",
"xpack.installed" : "true",
"transform.node" : "true",
"ml.max_open_jobs" : "20"
},
"settings" : {
"cluster" : {
"name" : "es-multinode",
"routing" : {
"allocation" : {
"disk" : {
"threshold_enabled" : "true",
"watermark" : {
"low" : "15gb",
"flood_stage" : "5gb",
"high" : "10gb"
}
}
}
},
"election" : {
"strategy" : "supports_voting_only"
},
"initial_master_nodes" : "es-multinode-0,es-multinode-1,es-multinode-2"
},
"node" : {
"name" : "es-multinode-0",
"attr" : {
"transform" : {
"node" : "true"
},
"xpack" : {
"installed" : "true"
},
"ml" : {
"machine_memory" : "1073741824",
"max_open_jobs" : "20"
}
},
"data" : "true",
"ingest" : "true",
"master" : "true"
},
"path" : {
"logs" : "/usr/share/elasticsearch/data/new-logs-dir",
"home" : "/usr/share/elasticsearch"
},
"discovery" : {
"seed_hosts" : "es-multinode-master"
},
"client" : {
"type" : "node"
},
"http" : {
"compression" : "false",
"type" : "security4",
"type.default" : "netty4"
},
"transport" : {
"type" : "security4",
"features" : {
"x-pack" : "true"
},
"type.default" : "netty4"
},
"xpack" : {
"security" : {
"http" : {
"ssl" : {
"enabled" : "true"
}
},
"enabled" : "true",
"transport" : {
"ssl" : {
"enabled" : "true"
}
}
}
},
"network" : {
"host" : "0.0.0.0"
}
}
},
"0q1IcSSARwu9HrQmtvjDGA" : {
"name" : "es-multinode-1",
"transport_address" : "10.244.0.27:9300",
"host" : "10.244.0.27",
"ip" : "10.244.0.27",
"version" : "7.9.1",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "083627f112ba94dffc1232e8b42b73492789ef91",
"roles" : [
"data",
"ingest",
"master",
"ml",
"remote_cluster_client",
"transform"
],
"attributes" : {
"ml.machine_memory" : "1073741824",
"ml.max_open_jobs" : "20",
"xpack.installed" : "true",
"transform.node" : "true"
},
"settings" : {
"cluster" : {
"name" : "es-multinode",
"routing" : {
"allocation" : {
"disk" : {
"threshold_enabled" : "true",
"watermark" : {
"low" : "15gb",
"flood_stage" : "5gb",
"high" : "10gb"
}
}
}
},
"election" : {
"strategy" : "supports_voting_only"
},
"initial_master_nodes" : "es-multinode-0,es-multinode-1,es-multinode-2"
},
"node" : {
"name" : "es-multinode-1",
"attr" : {
"transform" : {
"node" : "true"
},
"xpack" : {
"installed" : "true"
},
"ml" : {
"machine_memory" : "1073741824",
"max_open_jobs" : "20"
}
},
"data" : "true",
"ingest" : "true",
"master" : "true"
},
"path" : {
"logs" : "/usr/share/elasticsearch/data/new-logs-dir",
"home" : "/usr/share/elasticsearch"
},
"discovery" : {
"seed_hosts" : "es-multinode-master"
},
"client" : {
"type" : "node"
},
"http" : {
"compression" : "false",
"type" : "security4",
"type.default" : "netty4"
},
"transport" : {
"type" : "security4",
"features" : {
"x-pack" : "true"
},
"type.default" : "netty4"
},
"xpack" : {
"security" : {
"http" : {
"ssl" : {
"enabled" : "true"
}
},
"enabled" : "true",
"transport" : {
"ssl" : {
"enabled" : "true"
}
}
}
},
"network" : {
"host" : "0.0.0.0"
}
}
},
"ITvdnOcERwuG0qBmBJLaww" : {
"name" : "es-multinode-2",
"transport_address" : "10.244.0.29:9300",
"host" : "10.244.0.29",
"ip" : "10.244.0.29",
"version" : "7.9.1",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "083627f112ba94dffc1232e8b42b73492789ef91",
"roles" : [
"data",
"ingest",
"master",
"ml",
"remote_cluster_client",
"transform"
],
"attributes" : {
"ml.machine_memory" : "1073741824",
"ml.max_open_jobs" : "20",
"xpack.installed" : "true",
"transform.node" : "true"
},
"settings" : {
"cluster" : {
"name" : "es-multinode",
"routing" : {
"allocation" : {
"disk" : {
"threshold_enabled" : "true",
"watermark" : {
"low" : "15gb",
"flood_stage" : "5gb",
"high" : "10gb"
}
}
}
},
"election" : {
"strategy" : "supports_voting_only"
},
"initial_master_nodes" : "es-multinode-0,es-multinode-1,es-multinode-2"
},
"node" : {
"name" : "es-multinode-2",
"attr" : {
"transform" : {
"node" : "true"
},
"xpack" : {
"installed" : "true"
},
"ml" : {
"machine_memory" : "1073741824",
"max_open_jobs" : "20"
}
},
"data" : "true",
"ingest" : "true",
"master" : "true"
},
"path" : {
"logs" : "/usr/share/elasticsearch/data/new-logs-dir",
"home" : "/usr/share/elasticsearch"
},
"discovery" : {
"seed_hosts" : "es-multinode-master"
},
"client" : {
"type" : "node"
},
"http" : {
"compression" : "false",
"type" : "security4",
"type.default" : "netty4"
},
"transport" : {
"type" : "security4",
"features" : {
"x-pack" : "true"
},
"type.default" : "netty4"
},
"xpack" : {
"security" : {
"http" : {
"ssl" : {
"enabled" : "true"
}
},
"enabled" : "true",
"transport" : {
"ssl" : {
"enabled" : "true"
}
}
}
},
"network" : {
"host" : "0.0.0.0"
}
}
}
}
}
Here we can see that our given configuration is merged to the default configurations.
Cleanup
To cleanup the Kubernetes resources created by this tutorial, run:
$ kubectl delete elasticsearch -n demo es-multinode
$ kubectl delete secret -n demo es-custom-config
$ kubectl delete namespace demo