Your team is migrating workloads to a GKE Autopilot cluster. In one Pod manifest you set a container's resource requests to 50m CPU and 256 MiB memory. After deployment, kubectl describe pod shows the Pod running with a 250m CPU request while the memory request remains 256 MiB. What explains this unexpected increase in the CPU request value?
Autopilot converts undersized CPU requests into additional memory, so the CPU request increases to preserve the required CPU-to-memory ratio.
Autopilot disregards all user-defined CPU requests and assigns values dynamically based on observed runtime usage.
Autopilot enforces a platform minimum of 0.25 vCPU per container and automatically rounds up any smaller CPU request to 250 mCPU, leaving valid memory requests unchanged.
Autopilot keeps the original resource requests but scales the underlying nodes, so the higher value you see is the node's allocatable CPU, not the Pod request.
GKE Autopilot validates every Pod's resource requests. If the requested amount is below the platform's minimum per-container threshold, Autopilot automatically raises the request to the minimum so that scheduling, billing, and performance expectations stay consistent. Today the minimum CPU request it enforces is 0.25 vCPU (250 mCPU). Memory is not changed because the requested 256 MiB already meets Autopilot's minimum and respects the allowed CPU-to-memory ratio. The platform does not ignore requests, keep the original value, or convert CPU requests into memory.
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What is GKE Autopilot?
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What does '250m CPU' mean in Kubernetes resource requests?
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Why is the memory request unchanged, but the CPU request is increased?
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What is GKE Autopilot?
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Why does Autopilot enforce a minimum resource request of 0.25 vCPU per container?
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How does Autopilot validate resource requests in a Pod manifest?
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GCP Associate Cloud Engineer
Ensuring successful operation of a cloud solution
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