Managing Container Memory and CPU in Kubernetes

Running applications in production requires a deep understanding of how containers consume system resources. Without proper boundaries, misconfigured workloads can easily destabilize your entire cluster. This text-based course guides you from the fundamental concepts of container resource allocation to practical strategies for managing CPU and memory. You will learn how to prevent Out-Of-Memory errors, avoid CPU throttling, and ensure high availability for your applications through precise configuration. What you'll learn: - Understand the core definitions of CPU shares, memory bytes, requests, and limits. - Configure Pod specifications to request and limit resources accurately. - Analyze how Kubernetes schedules pods based on available node capacity. - Prevent common runtime issues like OOMKilled errors and CPU throttling. - Apply LimitRanges and ResourceQuotas to enforce resource policies across namespaces. - Explore modern autoscaling basics, including how resource settings impact horizontal and vertical pod autoscalers. The course begins with foundational terminology and container mechanics before progressing to configuration scenarios and cluster-wide governance policies. You will read detailed explanations, analyze YAML examples, and complete written exercises to solidify your learning. This course is designed for system administrators, DevOps beginners, and software engineers looking to run reliable workloads on Kubernetes, with no prior cluster administration experience required. Start reading today to build stable, cost-efficient, and highly performant Kubernetes environments.