A development team notices that their analytics engine restarts several times a day due to memory failures. System logs show the process never uses more than 70% of the expected capacity before crashing. The cluster uses default container resource definitions. Which action is most likely to stop the daily restarts?
Adjust the assigned memory for the container to a larger amount in the cluster configuration
Switch the container to a new regional node for lower latency
Pull a newer container image from the registry and redeploy
Grant more privileges to the container for resource handling
Raising the defined limit for the container in the orchestrator addresses this class of memory failures. The process shuts down when it nears its artificial boundary, even though real usage isn’t at true capacity. Changing the region would not help an internal memory limit. Granting broader permissions would not resolve a memory usage failure. Deploying a new version might fix certain bugs, though it would not eliminate a resource threshold problem.
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What is a container's memory limit in a cluster?
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Why doesn’t switching to a new regional node fix memory issues?
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How does redeploying a container with a new image impact memory issues?