CruiseKube is an intelligent Kubernetes resource optimization controller that automatically monitors, analyzes, and applies resource recommendations to improve cluster efficiency and reduce costs.
CruiseKube is a Kubernetes-native, continuous resource optimization system that autonomously right-sizes CPU and memory for workloads at runtime and admission time. It focuses on eliminating persistent over-provisioning while preserving workload reliability and scheduling constraints.
Unlike static requests, manual tuning, or reactive autoscaling, CruiseKube operates as a closed-loop control system that observes real workload behavior and incrementally converges resource requests toward optimal values.
You would need CruiseKube if you are facing any of these issues -
- Chronic over-provisioning driven by guesswork, peak-based sizing, and fear of CPU throttling or OOM crashes
- Cost inefficiency that node-level bin packing as provided by autoscalers (Cluster Autoscaler/Karpenter) alone cannot fix
- Operational Load arising from manual tuning of workloads on kubernetes by developers or DevOps teams
CruiseKube explicitly addresses the pod-level right-sizing problem, in a fully hands-off manner.
Details on how to install and configure CruiseKube can be found in the Getting Started guide.
Refer to DEVELOPMENT.md for more details.
Contribution details can be found in the Contribution guide.
![@github-actions[bot]](https://avatars.githubusercontent.com/in/15368?s=64&v=4){kind=small}
