Kubernetes 1.19 graduates HPA v2 to GA, marking the maturity of custom metrics autoscaling. This post covers production patterns, metrics pipelines, and real-world deployment strategies.
KEDA 1.0 graduates with HPA integration, scaler extensibility, and event-driven autoscaling for serverless-style workloads.
Kubernetes 1.12 introduces HPA v2beta2 with stable custom metrics support, enabling autoscaling on application metrics, queue depth, and cloud service metrics beyond CPU and memory.
Kubernetes 1.12 graduates kubelet TLS bootstrap and Azure VMSS to GA, introduces RuntimeClass, volume snapshot alpha, and major autoscaling improvements for large clusters.
Kubernetes 1.9 introduces Vertical Pod Autoscaler alpha, enabling automatic resource request and limit adjustment for pods based on historical usage patterns.
A look at the first production-ready autoscaling stack for Kubernetes—covering Cluster Autoscaler and Horizontal Pod Autoscaler v2.
Overview of Kubernetes 1.2 — scale to 1,000 nodes, new declarative APIs (Deployment, ConfigMap), and a richer autoscaling story.