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Introduction

What is CruiseKube?

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.

When do you need CruiseKube?

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.

Architecture

flowchart LR
    %% Actor
    Human((Human))

    %% Kubernetes Cluster Boundary
    subgraph K8s[Kubernetes Cluster]
        direction LR

        %% Frontend
        Frontend[Frontend]

        %% Controller
        subgraph Controller
            direction TB
            Stats[Statistics Engine]
            Runtime[Runtime Optimizer]
        end

        %% API Server
        APIServer[kube-api-server]

        %% Webhook
        subgraph Webhook
            Admission[Admission Optimizer]
        end

        %% Data & Metrics
        Database[(Database)]
        Prometheus[Prometheus]
    end

    %% User Flow
    Human --> Frontend
    Frontend --> Controller

    %% Control Plane Flow
    Controller --> APIServer
    APIServer <--> Webhook

    %% Data Flow
    Controller --> Database
    Webhook --> Database
    Controller --> Prometheus

Read more about the architecture in the Architecture section.