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Your autoscaler is a liar. It promises to scale your workloads when demand spikes, but in production, when revenue is on the line, it chokes. The HorizontalPodAutoscaler (HPA) controller loop runs every 15 seconds, metrics-server takes another 30 sec...

Introduction Kubernetes has become the go-to orchestration platform for managing containerized workloads at scale. However, optimizing resource utilization while ensuring workload availability remains a challenge. Traditional cluster autoscalers ofte...

What is KEDA? Kubernetes Event-Driven Autoscaling (KEDA) is an open-source project that extends Kubernetes' native Horizontal Pod Autoscaler (HPA) to support event-driven scaling. Unlike traditional autoscalers that rely solely on CPU or memory metri...

Kubernetes Autoscaling: How It Works, Why It Matters, and the Latest Tools Autoscaling in Kubernetes is one of the most critical features enabling cloud-native applications to handle variable workloads efficiently. It ensures optimal resource utiliza...

Introduction In cloud-native applications, efficient resource management is crucial to maintain optimal performance and cost-effectiveness. One powerful tool that aids in this management is the Cluster Autoscaler. This article explores the Cluster Au...

❗Understanding Scaling in Kubernetes Scaling in Kubernetes means to adjusting the number of servers, workloads, or resources to meet demand. It's different from maintaining a fixed number of replicas, which is handled by the ReplicaSet controller(Hig...
