Kubernetes Autoscaling

Feature Overview

Datadog Kubernetes Autoscaling continuously monitors your Datadog telemetry signals to generate intelligent resource recommendations in your Kubernetes environments. Rightsize your Kubernetes workloads safely and automatically to drive cloud cost savings while maintaining application performance.

Multidimensional workload autoscaling

Combine container size and replica count changes to maximize efficiency
Configure desired utilization thresholds, with resource guarantees for your most critical workloads
Use vertical-only scaling and recommendations if preferred

Identify overprovisioned workloads and clusters

Pinpoint your most overprovisioned clusters and workloads quickly and easily
Get started immediately with reporting based on your existing Datadog Agent deployment
Quickly gain visibility into excess CPU and memory resource consumption

Deploy fast via app or GitOps

Deploy autoscalers in one click directly from Datadog
Integrate with your existing GitOps system and review process by installing the DatadogPodAutoscaler directly
Track the impact of optimization directly in the platform