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	<title>Kubernetes Resources &#8211; Operator Pod</title>
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		<title>Kubernetes CPU and Memory Limits: Preventing OOMKilled Exit Code 137</title>
		<link>https://operatorpod.net/kubernetes-memory-limits-oomkilled-137/</link>
					<comments>https://operatorpod.net/kubernetes-memory-limits-oomkilled-137/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Wed, 09 Sep 2026 09:22:05 +0000</pubDate>
				<category><![CDATA[Kubernetes Resources]]></category>
		<guid isPermaLink="false">https://operatorpod.net/kubernetes-memory-limits-oomkilled-137/</guid>

					<description><![CDATA[Understand how the Linux kernel cgroup OOM killer works in Kubernetes, how to size operator pod memory limits, and how to avoid noisy-neighbor evictions.]]></description>
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<p class="wp-block-paragraph">In containerized Kubernetes environments, understanding the distinction between CPU throttling and Memory OOM kills is critical. While exceeding a CPU limit merely compresses execution time via the Linux Completely Fair Scheduler (CFS), exceeding a memory limit results in immediate, unrecoverable container termination.</p>



<h2 class="wp-block-heading">How the Linux Kernel Triggers SIGKILL (Exit 137)</h2>



<p class="wp-block-paragraph">Every container runtime allocates a cgroup for the container process. When resident set memory (RSS) surpasses <code>resources.limits.memory</code>, the cgroup memory controller dispatches SIGKILL (Signal 9 + 128 = Exit Code 137). Kubernetes records this condition as <strong>OOMKilled</strong>.</p>



<h2 class="wp-block-heading">Configuring Memory Headroom for Operator Controllers</h2>



<p class="wp-block-paragraph">Operators frequently maintain in-memory caches (such as controller-runtime client-go informers) of all managed custom resources in the cluster. As the number of CRs grows from 10 to 1,000, informer cache memory grows linearly. Always calculate a 30% to 50% buffer over baseline idle consumption.</p>
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