Kubernetes CPU limits and requests: A deep dive

The blog post delves into the intricacies of managing CPU resources in Kubernetes, focusing on the CPU Manager's default and static policies. It explains how CPU requests and limits impact container scheduling and resource allocation, emphasizing the role of the Completely Fair Scheduler (CFS) in enforcing these limits under the default policy. The post highlights the importance of monitoring metrics such as CPU usage and throttling to optimize performance and prevent overprovisioning or underutilization. Additionally, it discusses scenarios where setting CPU limits is beneficial, such as in multi-tenant environments or for ensuring predictable application performance. The static policy, which allows containers exclusive access to specific CPU cores, is examined for workloads sensitive to context switching and cache misses. Throughout, the post underscores the value of tracking key performance metrics to troubleshoot and improve application efficiency, offering insights into how these settings influence application behavior in Kubernetes environments.