Pooja Malik

This blog discusses optimizing autoscaling in Azure Kubernetes Service (AKS) to enhance cost-effectiveness and performance. It emphasizes the Cluster Autoscaler’s role in managing node numbers and outlines best practices, including implementing availability zones, assigning CPU/memory requests, and tailoring configurations for mixed workloads. The blog also covers creating performance-focused and cost-focused autoscaler profiles, addressing common challenges like scale-up and scale-down failures, and utilizing monitoring tools like resource logs and custom metrics. By adopting these strategies, organizations can significantly improve their cloud infrastructure's efficiency and scalability.

We explore the key role of autoscaling in optimizing performance and cost within Kubernetes. Specifically, we delve into two critical autoscalers—Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA)—and shed light on their functionalities, benefits, and limitations.