A comprehensive retrospective on Kubernetes autoscaling evolution from 2016 to 2025—covering the current landscape, emerging patterns, cost optimization strategies, and future trends.
KEDA 2.12 delivers new scalers, improved performance, enhanced security features, and better integration with Kubernetes autoscaling for event-driven workloads.
KEDA 2.11 delivers new scalers, improved performance, enhanced security features, and better integration with Kubernetes autoscaling for event-driven workloads.
Predictive autoscaling uses machine learning and historical patterns to pre-scale workloads before traffic arrives, reducing latency and improving cost efficiency compared to reactive scaling.
KEDA 2.10 introduces new scalers, improved HTTP add-on, and better observability for dynamic autoscaling in Kubernetes.
KEDA 2.8 expands autoscaling capabilities with new scalers, improved HTTP add-on, and enhanced observability for event-driven Kubernetes workloads.
KEDA 2.4 expands autoscaling capabilities with new scalers, improved HTTP add-on, and enhanced observability for event-driven Kubernetes workloads.
KEDA 2.0 introduces ScaledObject v2, HTTP add-on integration, and multi-metric scaling for resilient event workloads.
KEDA 1.0 graduates with HPA integration, scaler extensibility, and event-driven autoscaling for serverless-style workloads.