Cloud Native Chronicles: Unleashing the Power of the Cloud

In the era of cloud-native applications, scalability is a critical factor in ensuring optimal performance and resource utilisation. Kubernetes, as a leading container orchestration platform, provides strong scaling capabilities through its Horizontal Pod Autoscaler (HPA). However, HPA is primarily designed for scaling based on CPU and memory metrics, which may not be sufficient for event-driven workloads. To address this limitation, Kubernetes Event-Driven Autoscaling (KEDA) has emerged as a powerful solution. KEDA extends the scaling capabilities of Kubernetes by enabling autoscaling based on various event sources. In this blog, we will explore the details of KEDA, its architecture, main components and use cases. We'll also discuss the benefits of using KEDA and provide a step-by-step guide on how to implement it in a Kubernetes cluster. Understanding Autoscaling in Kubernetes: Modern applications often experience dynamic and unpredictable workloads. Autoscaling is essential to en...