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A container can be killed for exceeding its own memory limit even while the Kubernetes node has free memory. The pod limit, application heap settings, sidecars, and burst patterns determine whether the workload reaches its ceiling.
Check container and pod memory limits, working set and peak usage, restart reason, sidecar consumption, and application runtime limits. Compare short spikes with sustained growth and inspect memory usage after a release.
Set limits based on measured workload and node capacity, then address leaks or inefficient caching where present. Use gradual changes and monitor evictions and latency so the fix does not destabilize other workloads.
Informatix Systems provides Kubernetes and container platform engineering. We can assess the affected systems, clarify likely causes, and help plan a practical fix. Contact us with the platform involved, when the issue began, and non-sensitive error details.
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