Prompt
What should I use for workload scheduling across clusters?
Latest observation
If you mean scheduling and moving workloads across multiple Kubernetes clusters, the best choice depends on what you want to optimize:
Good options
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Kubernetes Federation / KubeFed
- Best if you want a Kubernetes-native way to propagate apps across clusters.
- Good for multi-cluster deployment management, less ideal for advanced workload placement.
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Karmada
- Strong choice for multi-cluster workload scheduling.
- Handles placement, propagation, failover, and scheduling across clusters.
- Good if you want centralized control over workloads across many clusters.
-
Cluster API + GitOps tools
- If your main need is cluster lifecycle plus app deployment, not sophisticated scheduling.
- Works well with Argo CD / Flux for deployment, but not true cross-cluster scheduling.
-
Service mesh / traffic management tools like Istio, Submariner, Cilium Cluster Mesh
- Useful for connectivity and service discovery across clusters.
- Not workload schedulers, but often needed alongside one.
Recommendation
- If your focus is workload scheduling across clusters, start with Karmada.
- If you just need deployment orchestration, use Argo CD/Flux plus multi-cluster patterns.
- If you need cluster networking and service connectivity, add Submariner or Cilium Cluster Mesh.
If you want, I can also give you a decision matrix comparing Karmada, KubeFed, Argo CD, and Cluster API for your specific environment.
Observation history
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