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Issue #38286: Clarify control plane resource sizing recommendation
Signed-off-by: Kevin Grigorenko <[email protected]>
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modules/master-node-sizing.adoc

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@@ -40,7 +40,7 @@ The control plane node resource requirements depend on the number of nodes in th
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On a large and dense cluster with three masters or control plane nodes, the CPU and memory usage will spike up when one of the nodes is stopped, rebooted or fails. The failures can be due to unexpected issues with power, network or underlying infrastructure in addition to intentional cases where the cluster is restarted after shutting it down to save costs. The remaining two control plane nodes must handle the load in order to be highly available which leads to increase in the resource usage. This is also expected during upgrades because the masters are cordoned, drained, and rebooted serially to apply the operating system updates, as well as the control plane Operators update. To avoid cascading failures, keep the overall resource usage on the control plane nodes to at most half of all available capacity to handle the resource usage spikes. Increase the CPU and memory on the control plane nodes accordingly to avoid potential downtime due to lack of resources.
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On a large and dense cluster with three masters or control plane nodes, the CPU and memory usage will spike up when one of the nodes is stopped, rebooted or fails. The failures can be due to unexpected issues with power, network or underlying infrastructure in addition to intentional cases where the cluster is restarted after shutting it down to save costs. The remaining two control plane nodes must handle the load in order to be highly available which leads to increase in the resource usage. This is also expected during upgrades because the masters are cordoned, drained, and rebooted serially to apply the operating system updates, as well as the control plane Operators update. To avoid cascading failures, keep the overall CPU and memory resource usage on the control plane nodes to at most half of all available capacity to handle the resource usage spikes. Increase the CPU and memory on the control plane nodes accordingly to avoid potential downtime due to lack of resources.
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