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.
See also
View documentationMultidimensional 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