Datadog Kubernetes Autoscaling offers three rollout paths for fleet-wide workload rightsizing: an in-app setup page for bulk activation without writing YAML, GitOps cluster profiles that apply a single policy across namespaces via labels, and AI-assisted onboarding through Bits AI or MCP-compatible clients that generate DatadogPodAutoscaler manifests and draft PRs. The tool also supports in-place vertical resizing of CPU and memory requests to avoid pod recreation disruption. Together these features let platform teams reduce idle costs at scale without requiring each application team to design their own autoscaling policies.
Table of contents
Activate autoscaling across your fleet from a single pageManage Datadog Kubernetes Autoscaling policy as code with GitOps cluster profilesGenerate manifests and PRs with AI-assisted onboardingAdjust resource requests in place with vertical resizingGet started with Datadog Kubernetes Autoscaling932 Impressions