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Merge pull request #36314 from libander/RHDEVDOCS-3095
RHDEVDOCS-3095: cluster logging updates
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modules/cluster-logging-logstore-limits.adoc

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@@ -40,12 +40,14 @@ metadata:
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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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elasticsearch:<1>
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resources:
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limits: <2>
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memory: "32Gi"
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requests: <3>
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cpu: "1"
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memory: "64Gi"
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proxy: <2>
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memory: "16Gi"
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proxy: <4>
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resources:
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limits:
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memory: 100Mi
@@ -54,21 +56,25 @@ spec:
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----
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<1> Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank,
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the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are `16Gi` for the memory request and `1` for the CPU request.
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<2> Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are `256Mi` for the memory request and `100m` for the CPU request.
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<2> The maximum amount of resources a pod can use.
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<3> The minimum resources required to schedule a pod.
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<4> Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that are sufficient for most deployments. The default values are `256Mi` for the memory request and `100m` for the CPU request.
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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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When adjusting the amount of Elasticsearch memory, the same value should be used for both `requests` and `limits`.
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For example:
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[source,yaml]
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----
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resources:
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limits:
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limits: <1>
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memory: "32Gi"
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requests:
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requests: <2>
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cpu: "8"
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memory: "32Gi"
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----
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<1> The maximum amount of the resource.
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<2> The minimum amount required.
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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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