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63 lines
1.9 KiB
Plaintext
63 lines
1.9 KiB
Plaintext
// Module included in the following assemblies:
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//
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// * logging/cluster-logging-elasticsearch.adoc
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[id="cluster-logging-logstore-limits_{context}"]
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= Configuring CPU and memory requests for the log store
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Each component specification allows for adjustments to both the CPU and memory requests.
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You should not have to manually adjust these values as the Elasticsearch
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Operator sets values sufficient for your environment.
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Each Elasticsearch node can operate with a lower memory setting though this is *not* recommended for production deployments.
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For production use, you should have no less than the default 16Gi allocated to each pod. Preferably you should allocate as much as possible, up to 64Gi per pod.
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.Prerequisites
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* Cluster logging and Elasticsearch must be installed.
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.Procedure
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. Edit the Cluster Logging Custom Resource (CR) in the `openshift-logging` project:
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+
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[source,terminal]
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----
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$ oc edit ClusterLogging instance
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----
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+
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[source,yaml]
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----
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apiVersion: "logging.openshift.io/v1"
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kind: "ClusterLogging"
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metadata:
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name: "instance"
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....
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spec:
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logStore:
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type: "elasticsearch"
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elasticsearch:
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resources: <1>
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requests:
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cpu: "1"
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memory: "16Gi"
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----
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<1> Specify the CPU and memory requests as needed. If you leave these values blank,
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the Elasticsearch Operator sets default values that should be sufficient for most deployments.
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+
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If you adjust the amount of Elasticsearch memory, you must change both the request value and the limit value.
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+
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For example:
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+
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[source,yaml]
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----
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resources:
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limits:
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memory: "32Gi"
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requests:
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cpu: "8"
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memory: "32Gi"
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----
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+
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Kubernetes generally adheres the node configuration and does not allow Elasticsearch to use the specified limits.
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Setting the same value for the `requests` and `limits` ensures that Elasticsearch can use the memory you want, assuming the node has the memory available.
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