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InfoQClaudio Masolo3 min readrelease notesintermediate

Kubernetes Multi-Cluster Project Karmada Reaches CNCF Graduation

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Summary

Karmada, a multi-cluster and multi-cloud Kubernetes orchestration project, has graduated to the highest maturity tier within the CNCF. It extends the standard Kubernetes API to manage workloads across diverse environments, enhancing multi-component scheduling for AI training jobs and promoting priority-based scheduling.

  • Karmada allows managing Kubernetes workloads across multiple clusters and clouds using familiar Kubernetes APIs without changes.
  • It uses `PropagationPolicy` for workload placement and `OverridePolicy` for cluster-specific configuration adjustments.
  • The control plane consists of a Karmada API Server, Controller Manager, and Scheduler, backed by its own etcd instance.
  • Key use cases include hybrid cloud capacity, cross-region resilience, distributed AI workload scheduling, and fleet-wide configuration.

Engineers operating complex multi-cluster Kubernetes environments, particularly for hybrid cloud strategies or distributed AI workloads, should consider Karmada as a production-ready, standardized solution.

6/10
kubernetesmulti clustercncfcloud nativeorchestrationai infra

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