Configure autoscaling in Azure Kubernetes Service with CPU & Memory
Introduction: Azure Kubernetes Service (AKS) empowers you to dynamically scale your applications to meet fluctuating demands. By leveraging CPU and memory-based autoscaling, you can optimize resource allocation, minimize costs, and ensure your applications consistently deliver peak performance. This guide will walk you through the process of configuring and implementing effective autoscaling in Azure Kubernetes Service deployment. By default, the Horizontal Pod Autoscaler (HPA) in Kubernetes primarily uses CPU utilization as a metric for scaling. However, it is also possible to configure HPA to use memory utilization or custom metrics. Here’s how you can set up HPA to consider memory usage in addition to CPU usage. What is HPA? Horizontal Pod Auto scaler (HPA) automatically scales the number of pods in a Kubernetes deployment based on observed metrics such as CPU and memory usage. It ensures your application can handle increased load and conserves resources when demand is low. Fo...