1️⃣How Memory and CPU Work Differently?

✅ Memory (RAM):

  • When a container has limits.memory: 512Mi but only uses 256Mi, the remaining 256Mi is returned to the system, and other pods can use it.
  • This happens because the operating system dynamically manages memory allocation and deallocation through Paging and Memory Management.

❌ CPU:

  • If a container has limits.cpu: 500m but only uses 200m, the remaining 300m is NOT available to other pods.
  • This is due to the CFS Quota (Completely Fair Scheduler) in the Linux Kernel, which pre-allocates CPU cycles based on the limit and does not dynamically redistribute unused CPU time.

2️⃣ Effect of limits.cpu and CFS Quota

When we set limits.cpu: 500m, Kubernetes tells the Linux kernel that this container can only use 500ms of CPU time in every 1000ms window.

  • If the container only consumes 200m, the remaining 300m does not get reallocated to other processes dynamically.
  • The CPU time is effectively reserved and cannot be shared with other workloads, even if there is unused capacity.

3️⃣ Why Should We Avoid Setting limits.cpu?

Because CPU limits introduce throttling, meaning:

  • If the container needs more CPU, it cannot exceed the set limit, even when there are idle CPU resources.
  • CPU time that is not used does not get returned to the system efficiently, unlike memory.
  • This can slow down applications unnecessarily by limiting them, even when more CPU power is available.

💡 Best Practice:

  • Set only requests.cpu to ensure a minimum guaranteed CPU allocation.
  • Do NOT set limits.cpu, unless you are in a strict multi-tenant environment where CPU overuse needs to be controlled.

Example Recommended Configuration:

resources:
  requests:
    cpu: "500m"
    memory: "256Mi"
  limits:
    memory: "512Mi"  # Memory limits are fine because unused memory is returned

🚀 Conclusion: Avoiding CPU limits allows containers to use extra CPU when available, preventing throttling and improving performance.

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linuxopenshift