
Karpenter 0.15: Node Autoscaling Improvements and Multi-Cloud Support
Karpenter 0.15 delivers node provisioning improvements, initial multi-cloud support, and enhanced cost optimization features for Kubernetes clusters.

Karpenter 0.15 delivers node provisioning improvements, initial multi-cloud support, and enhanced cost optimization features for Kubernetes clusters.

Hard-won lessons from running autoscaling in production—covering right-sizing, metrics selection, stabilization windows, observability, and common failure modes.

AWS launches Karpenter 0.1, an open-source high-performance node autoscaler for Kubernetes clusters, providing faster node provisioning and better cost optimization.

KEDA 2.4 expands autoscaling capabilities with new scalers, improved HTTP add-on, and enhanced observability for event-driven Kubernetes workloads.

Orchestrating Horizontal Pod Autoscaler, Vertical Pod Autoscaler, and Cluster Autoscaler together for comprehensive Kubernetes autoscaling—covering coordination strategies, conflict avoidance, and cost optimization.

KEDA 2.0 introduces ScaledObject v2, HTTP add-on integration, and multi-metric scaling for resilient event workloads.

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 1.9 introduces Vertical Pod Autoscaler alpha, enabling automatic resource request and limit adjustment for pods based on historical usage patterns.