Kubernetes Pod Auto-Scaling with HorizontalPodAutoscaler

In modern cloud environments, application traffic fluctuates constantly, making manual resource management inefficient and risky. This text-based course guides you through configuring and managing Kubernetes auto-scaling to ensure your applications remain highly available and cost-effective. You will begin by understanding the core architecture of the HorizontalPodAutoscaler (HPA) and how it interacts with the Metrics Server. From there, you will learn to define resource requests and limits, deploy scaling policies, and monitor scaling events through clear, step-by-step written explanations and configuration examples. What you'll learn: - Understand the foundational concepts of Kubernetes auto-scaling and the HPA control loop - Configure resource requests and limits for CPU and memory within deployment manifests - Deploy and configure the Metrics Server to gather real-time utilization data - Create and apply HorizontalPodAutoscaler resource definitions using YAML - Analyze scaling behavior and troubleshoot common HPA configuration issues - Apply modern best practices for scaling policies to prevent rapid fluctuation or thrashing Starting with basic terminology and foundational concepts, this course moves systematically from cluster prerequisites to deploying and testing functional scaling policies. It is designed for beginners, system administrators, and developers new to Kubernetes orchestration, requiring no prior container-scaling experience. Gain the skills to build resilient, self-scaling infrastructure today.