---
title: Manage compute resources
description: To help the Kubernetes scheduler correctly place Pods in available Kubernetes nodes and ensure quality of service (QoS), it is recommended to specify...
url: https://www.elastic.co/elastic/docs-builder/docs/3028/deploy-manage/deploy/cloud-on-k8s/manage-compute-resources
products:
- Elastic Cloud on Kubernetes
applies_to:
- Elastic Cloud on Kubernetes: Generally available
---
# Manage compute resources
To help the Kubernetes scheduler correctly place Pods in available Kubernetes nodes and ensure quality of service (QoS), it is recommended to specify the CPU and memory requirements for objects managed by the operator (Elasticsearch, Kibana, APM Server, Beats, Elastic Agent, Elastic Maps Server, Logstash, AutoOps Agent Policy and Package Registry). In Kubernetes, `requests` defines the minimum amount of resources that must be available for a Pod to be scheduled; `limits` defines the maximum amount of resources that a Pod is allowed to consume. For more information about how Kubernetes uses these concepts, check [Managing Compute Resources for Containers](https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/).
The operator applies default requests and limits for memory and CPU. They may be suitable for experimenting with the Elastic Stack, however it is recommended to reevaluate these values for production use cases.
Consider that Kubernetes throttles containers exceeding the CPU limit defined in the `limits` section. Do not set this value too low, or it would affect the performance of your workloads, even if you have enough resources available in the Kubernetes cluster.
Also, to minimize disruption caused by Pod evictions due to resource contention, you can run Pods at the "Guaranteed" QoS level by setting both `requests` and `limits` to the same value.
## Set compute resources
You can set compute resource constraints in the `podTemplate` of objects managed by the operator.
### Set compute resources for Elasticsearch
```yaml
apiVersion: elasticsearch.k8s.elastic.co/v1
kind: Elasticsearch
metadata:
name: quickstart
spec:
version: 9.3.2
nodeSets:
- name: default
count: 1
podTemplate:
spec:
containers:
- name: elasticsearch
resources:
requests:
memory: 4Gi
cpu: 8
limits:
memory: 4Gi
```
#### Memory limit and JVM Heap settings
Starting with Elasticsearch 7.11, the heap size of the JVM is automatically calculated based on the node roles and the available memory. The available memory is defined by the value of `resources.limits.memory` set on the `elasticsearch` container in the Pod template, or the available memory on the Kubernetes node if no limit is set.
For Elasticsearch before 7.11, or if you want to override the default calculated heap size on newer versions, set the `ES_JAVA_OPTS` environment variable in the `podTemplate` to an appropriate value:
```yaml
apiVersion: elasticsearch.k8s.elastic.co/v1
kind: Elasticsearch
metadata:
name: quickstart
spec:
version: 9.3.2
nodeSets:
- name: default
count: 1
podTemplate:
spec:
containers:
- name: elasticsearch
env:
- name: ES_JAVA_OPTS
value: -Xms2g -Xmx2g
resources:
requests:
memory: 4Gi
cpu: 8
limits:
memory: 4Gi
```
#### CPU resources
The value set for CPU limits or requests directly impacts the Elasticsearch `node.processors` setting. By default Elasticsearch automatically detects the number of processors and sets the thread pool settings based on it. The following table gives the default value for `node.processors` given the CPU limits and requests set on the `elasticsearch` container:
| | No CPU limit | With CPU limit |
|----------------------|-------------------------------------------|--------------------------|
| No CPU request | `All the available cores on the K8S node` | `Value of the CPU limit` |
| CPU request set to 1 | `All the available cores on the K8S node` | `Value of the CPU limit` |
| Other CPU requests | `Value of the CPU request` | `Value of the CPU limit` |
You can also set your own value for `node.processors` in the Elasticsearch config.
A [known Kubernetes issue](https://github.com/kubernetes/kubernetes/issues/51135) may lead to over-aggressive CPU limits throttling. If the host Linux Kernel does not include [this CFS quota fix](https://github.com/kubernetes/kubernetes/issues/67577), you may want to:
- not set any CPU limit in the Elasticsearch resource (Burstable QoS)
- [reduce the CFS quota period](https://github.com/kubernetes/kubernetes/pull/63437) in kubelet configuration
- [disable CFS quotas](https://github.com/kubernetes/kubernetes/issues/51135#issuecomment-386319185) in kubelet configuration
### Set compute resources for Kibana, Elastic Maps Server, APM Server and Logstash
```yaml
apiVersion: kibana.k8s.elastic.co/v1
kind: Kibana
metadata:
name: quickstart
spec:
version: 9.3.2
podTemplate:
spec:
containers:
- name: kibana
env:
- name: NODE_OPTIONS
value: "--max-old-space-size=2048"
resources:
requests:
memory: 1Gi
cpu: 0.5
limits:
memory: 2.5Gi
cpu: 2
```
```yaml
apiVersion: maps.k8s.elastic.co/v1alpha1
kind: ElasticMapsServer
metadata:
name: quickstart
spec:
version: 9.3.2
podTemplate:
spec:
containers:
- name: maps
env:
- name: NODE_OPTIONS
value: "--max-old-space-size=980"
resources:
requests:
memory: 1Gi
cpu: 1
limits:
memory: 1Gi
cpu: 1
```
```yaml
apiVersion: apm.k8s.elastic.co/v1
kind: ApmServer
metadata:
name: quickstart
spec:
version: 9.3.2
podTemplate:
spec:
containers:
- name: apm-server
resources:
requests:
memory: 1Gi
cpu: 0.5
limits:
memory: 2Gi
cpu: 2
```
```yaml
apiVersion: enterprisesearch.k8s.elastic.co/v1
kind: EnterpriseSearch
metadata:
name: enterprise-search-quickstart
spec:
version: 8.19.1
podTemplate:
spec:
containers:
- name: enterprise-search
resources:
requests:
memory: 4Gi
cpu: 1
limits:
memory: 4Gi
cpu: 2
env:
- name: JAVA_OPTS
value: -Xms3500m -Xmx3500m
```
```yaml
apiVersion: logstash.k8s.elastic.co/v1
kind: logstash
metadata:
name: logstash-quickstart
spec:
version: 9.3.2
podTemplate:
spec:
containers:
- name: logstash
resources:
requests:
memory: 4Gi
cpu: 1
limits:
memory: 4Gi
cpu: 2
env:
- name: LS_JAVA_OPTS
value: -Xms2000m -Xmx2000m
```
For the container name, use `apm-server`, `maps`, `kibana` or `enterprise-search`, respectively.
### Set compute resources for Beats and Elastic Agent
For Beats or Elastic Agent objects, the `podTemplate` can be configured as follows, depending on the chosen deployment model.
When deploying as a Kubernetes Deployment:
```yaml
apiVersion: beat.k8s.elastic.co/v1beta1
kind: Beat
metadata:
name: quickstart
spec:
type: filebeat
version: 9.3.2
deployment:
podTemplate:
spec:
containers:
- name: filebeat
resources:
requests:
memory: 300Mi
cpu: 0.5
limits:
memory: 500Mi
cpu: 0.5
```
When deploying as a Kubernetes DaemonSet:
```yaml
apiVersion: agent.k8s.elastic.co/v1alpha1
kind: Agent
metadata:
name: elastic-agent
spec:
version: 9.3.2
daemonSet:
podTemplate:
spec:
containers:
- name: agent
resources:
requests:
memory: 300Mi
cpu: 0.5
limits:
memory: 300Mi
cpu: 0.5
```
For the container name, use the name of the Beat in lower case. For example `filebeat`, `metricbeat`, or `heartbeat`. In case of Elastic Agent, use `agent`.
### Set compute resources for Elastic AutoOps Agent
- Elastic Cloud on Kubernetes: Generally available since 3.3
For `AutoOpsAgentPolicy` resources (Elastic AutoOps Agent), the `podTemplate` can be configured as follows:
```yaml
apiVersion: autoops.k8s.elastic.co/v1alpha1
kind: AutoOpsAgentPolicy
metadata:
name: autoops-agent-policy
spec:
version: 9.3.2
podTemplate:
spec:
containers:
- name: autoops-agent
resources:
requests:
cpu: 200m
memory: 600Mi
limits:
cpu: 200m
memory: 600Mi
```
For the container name, use `autoops-agent`.
[Learn more about configuring AutoOps in Elastic Cloud on Kubernetes](https://www.elastic.co/elastic/docs-builder/docs/3028/deploy-manage/monitor/autoops/cc-autoops-as-cloud-connected).
## Default behavior
If `resources` is not defined in the specification of an object, then the operator applies a default memory limit to ensure that Pods have enough resources to start correctly. This memory limit will also be applied to any user-defined init containers that do not have explict resource requirements set. As the operator cannot make assumptions about the available CPU resources in the cluster, no CPU limits will be set — resulting in the Pods having the "Burstable" QoS class. Check if this is acceptable for your use case and follow the instructions in [Set compute resources](#k8s-compute-resources) to configure appropriate limits.
| Type | Requests | Limits |
|--------------------------|----------|---------|
| APM Server | `512Mi` | `512Mi` |
| Elasticsearch | `2Gi` | `2Gi` |
| Kibana | `1Gi` | `1Gi` |
| Beat | `300Mi` | `300Mi` |
| Elastic Agent | `400Mi` | `400Mi` |
| Elastic Maps Server | `200Mi` | `200Mi` |
| Logstash | `2Gi` | `2Gi` |
| Elastic Package Registry | `1Gi` | `1Gi` |
| AutoOps Agent | `400Mi` | `400Mi` |
If the Kubernetes cluster is configured with [LimitRanges](https://kubernetes.io/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/) that enforce a minimum memory constraint, they could interfere with the operator defaults and cause object creation to fail.
For example, you might have a `LimitRange` that enforces a default and minimum memory limit on containers as follows:
```yaml
apiVersion: v1
kind: LimitRange
metadata:
name: default-mem-per-container
spec:
limits:
- min:
memory: "3Gi"
defaultRequest:
memory: "3Gi"
type: Container
```
With this limit range in place, if you create an Elasticsearch object without defining the `resources` section, you will get the following error:
```
Cannot create pod elasticsearch-sample-es-ldbgj48c7r: pods "elasticsearch-sample-es-ldbgj48c7r" is forbidden: minimum memory usage per Container is 3Gi, but request is 2Gi
```
To avoid this, explicitly define the requests and limits mandated by your environment in the resource specification. It will prevent the operator from applying the built-in defaults.
## Monitor compute resources
#### Using Beats
[Metricbeat](https://www.elastic.co/elastic/docs-builder/docs/3028/deploy-manage/deploy/cloud-on-k8s/beats) can collect the percentage of both the CPU and the memory limits used by each Pod (or total node allocatable if resource is not limited). The two relevant metrics are `kubernetes.pod.cpu.usage.limit.pct` for CPU, and `kubernetes.pod.memory.usage.node.pct` for memory.
#### Monitoring Elasticsearch CPU using Stack Monitoring
If [Stack Monitoring](https://www.elastic.co/elastic/docs-builder/docs/3028/deploy-manage/monitor/stack-monitoring/eck-stack-monitoring) is enabled, the pressure applied by the CPU cgroup controller to an Elasticsearch node can be evaluated from the **Stack Monitoring** page in Kibana.
1. On the **Stack Monitoring** page select the Elasticsearch node you want to monitor.
2. Select the **Advanced** tab.
In the following example, an Elasticsearch container is limited to 2 cores.
```yaml
nodeSets:
- name: default
count: 3
podTemplate:
spec:
containers:
- name: elasticsearch
resources:
limits:
cpu: 2
```
The **Cgroup usage** curve shows that the CPU usage of this container has been steadily increasing up to 2 cores. Then, while the container was still requesting more CPU, the **Cgroup Throttling** curve shows how much the Elasticsearch container has been throttled:
