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skypilot-multi-cloud-orchestration

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Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.

When to use

• Running ML workloads across multiple clouds (AWS, GCP, Azure, etc.)
• Need cost optimization with automatic cloud/region selection
• Running long jobs on spot instances with auto-recovery
• Managing distributed multi-node training
• Want unified interface for 20+ cloud providers
• Need to avoid vendor lock-in
• **Multi-cloud**: AWS, GCP, Azure, Kubernetes, Lambda, RunPod, 20+ providers
• **Cost optimization**: Automatic cheapest cloud/region selection

When not to use

• Simpler serverless GPU with Python-native API
• Single-cloud persistent pods
• Existing K8s infrastructure
• Pure Ray-based orchestration

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