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current release documentation.
Autoscaling stateless applications
editAutoscaling stateless applications
editThis section only applies to stateless applications. See Elasticsearch autoscaling for more details about scaling automatically Elasticsearch.
The Horizontal Pod Autoscaler can be used to automatically scale the deployments of the following resources:
- Kibana
- APM Server
- Enterprise Search
- Elastic Maps Server
These resources expose the scale
subresource which can be used by the Horizontal Pod Autoscaler controller to automatically adjust the number of replicas according to the CPU load or any other custom or external metric. The example below shows how to create an HorizontalPodAutoscaler
resource to adjust the replicas of a Kibana deployment according to the CPU load:
apiVersion: elasticsearch.k8s.elastic.co/v1 kind: Elasticsearch metadata: name: elasticsearch-sample spec: version: 8.15.2 nodeSets: - name: default count: 1 config: node.store.allow_mmap: false --- apiVersion: kibana.k8s.elastic.co/v1 kind: Kibana metadata: name: kibana-sample spec: version: 8.15.2 count: 1 elasticsearchRef: name: "elasticsearch-sample" podTemplate: spec: containers: - name: kibana resources: requests: memory: 1Gi cpu: 1 limits: memory: 1Gi --- apiVersion: autoscaling/v2beta2 kind: HorizontalPodAutoscaler metadata: name: kb spec: scaleTargetRef: apiVersion: kibana.k8s.elastic.co/v1 kind: Kibana name: kibana-sample minReplicas: 1 maxReplicas: 4 metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 50