Advanced Elasticsearch node scheduling
editAdvanced Elasticsearch node scheduling
editElastic Cloud on Kubernetes (ECK) offers full control over Elasticsearch cluster nodes scheduling by combining Elasticsearch configuration with Kubernetes scheduling options:
These features can be combined together, to deploy a production-grade Elasticsearch cluster.
Define Elasticsearch nodes roles
editYou can configure Elasticsearch nodes with one or multiple roles. This allows you to describe an Elasticsearch cluster with 3 dedicated master nodes, for example:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: # 3 dedicated master nodes - name: master count: 3 config: node.master: true node.data: false node.ingest: false node.remote_cluster_client: false # 3 ingest-data nodes - name: ingest-data count: 3 config: node.master: false node.data: true node.ingest: true
Affinity options
editYou can setup various affinity and anti-affinity options through the podTemplate
section of the Elasticsearch resource specification.
A single Elasticsearch node per Kubernetes host (default)
editTo avoid scheduling several Elasticsearch nodes from the same cluster on the same host, use a podAntiAffinity
rule based on the hostname and the cluster name label:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodesSets: - name: default count: 3 podTemplate: spec: affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchLabels: elasticsearch.k8s.elastic.co/cluster-name: quickstart topologyKey: kubernetes.io/hostname
This is ECK default behaviour if you don’t specify any affinity
option.
To explicitly disable that behaviour, set an empty affinity object:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: - name: default count: 3 podTemplate: spec: affinity: {}
The default affinity is using preferredDuringSchedulingIgnoredDuringExecution
, which acts as best effort and won’t prevent an Elasticsearch node from being scheduled on a host if there are no other hosts available. Scheduling a 4-nodes Elasticsearch cluster on a 3-host Kubernetes cluster would then successfully schedule 2 Elasticsearch nodes on the same host. To enforce a strict single node per host, specify requiredDuringSchedulingIgnoredDuringExecution
instead:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: - name: default count: 3 podTemplate: spec: affinity: podAntiAffinity: requiredDuringSchedulingIgnoredDuringExecution: - labelSelector: matchLabels: elasticsearch.k8s.elastic.co/cluster-name: quickstart topologyKey: kubernetes.io/hostname
Local Persistent Volume constraints
editBy default, volumes can be bound to a pod before the pod gets scheduled to a particular Kubernetes node. This can be a problem if the PersistentVolume can only be accessed from a particular host or set of hosts. Local persistent volumes are a good example: they are accessible from a single host. If the pod gets scheduled to a different host based on any affinity or anti-affinity rule, the volume may not be available.
To solve this problem, you can set the Volume Binding Mode of the StorageClass
you are using. Make sure volumeBindingMode: WaitForFirstConsumer
is set, especially if you are using local persistent volumes.
kind: StorageClass apiVersion: storage.k8s.io/v1 metadata: name: local-storage provisioner: kubernetes.io/no-provisioner volumeBindingMode: WaitForFirstConsumer
Node affinity
editTo restrict the scheduling to a particular set of Kubernetes nodes based on labels, use a NodeSelector.
The following example schedules Elasticsearch pods on Kubernetes nodes tagged with both labels diskType: ssd
and environment: production
.
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: - name: default count: 3 podTemplate: spec: nodeSelector: diskType: ssd environment: production
You can achieve the same (and more) with node affinity:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: - name: default count: 3 podTemplate: spec: affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: environment operator: In values: - e2e - production preferredDuringSchedulingIgnoredDuringExecution: - weight: 1 preference: matchExpressions: - key: diskType operator: In values: - ssd
This example restricts Elasticsearch nodes so they are only scheduled on Kubernetes hosts tagged with environment: e2e
or environment: production
. It favors nodes tagged with diskType: ssd
.
Availability zone awareness
editBy combining Elasticsearch shard allocation awareness with Kubernetes node affinity, you can setup an availability zone-aware Elasticsearch cluster:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: - name: zone-a count: 1 config: node.attr.zone: europe-west3-a cluster.routing.allocation.awareness.attributes: zone podTemplate: spec: affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: failure-domain.beta.kubernetes.io/zone operator: In values: - europe-west3-a - name: zone-b count: 1 config: node.attr.zone: europe-west3-b cluster.routing.allocation.awareness.attributes: zone podTemplate: spec: affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: failure-domain.beta.kubernetes.io/zone operator: In values: - europe-west3-b
This example relies on:
-
Kubernetes nodes in each zone being labeled accordingly.
failure-domain.beta.kubernetes.io/zone
is standard, but any label can be used. - node affinity for each group of nodes set to match the Kubernetes nodes' zone.
-
Elasticsearch configured to allocate shards based on node attributes. Here we specified
node.attr.zone
, but any attribute name can be used.node.attr.rack_id
is another common example.
Hot-warm topologies
editBy combining Elasticsearch shard allocation awareness with Kubernetes node affinity, you can setup an Elasticsearch cluster with hot-warm topology:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: quickstart spec: version: 8.15.3 nodeSets: # hot nodes, with high CPU and fast IO - name: hot count: 3 config: node.attr.data: hot podTemplate: spec: containers: - name: elasticsearch resources: limits: memory: 16Gi cpu: 4 affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: beta.kubernetes.io/instance-type operator: In values: - highio volumeClaimTemplates: - metadata: name: elasticsearch-data spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Ti storageClassName: local-storage # warm nodes, with high storage - name: warm count: 3 config: node.attr.data: warm podTemplate: spec: containers: - name: elasticsearch resources: limits: memory: 16Gi cpu: 2 affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: beta.kubernetes.io/instance-type operator: In values: - highstorage volumeClaimTemplates: - metadata: name: elasticsearch-data spec: accessModes: - ReadWriteOnce resources: requests: storage: 10Ti storageClassName: local-storage
In this example, we configure two groups of Elasticsearch nodes:
-
the first group has the
data
attribute set tohot
. It is intended to run on hosts with high CPU resources and fast IO (SSD). Here we restrict pods to be scheduled on Kubernetes nodes labeled withbeta.kubernetes.io/instance-type: highio
(to adapt to your Kubernetes nodes' labels). -
the second group has the
data
attribute set towarm
. It is intended to run on hosts with larger but maybe slower storage. Pods are only able to be scheduled on nodes labeled withbeta.kubernetes.io/instance-type: highstorage
.
this example uses Local Persistent Volumes for both groups, but can be adapted to use high-performance volumes for hot
Elasticsearch nodes and high-storage volumes for warm
Elasticsearch nodes.
Finally, setup Index Lifecycle Management policies on your indices, optimizing for hot-warm architectures.