Skypilot Multi Cloud Orchestration
Skypilot Multi Cloud Orchestration automates deployments across diverse clouds, simplifying complex workflows and boosting infrastructure efficiency.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add zechenzhangagi-skypilot-multi-cloud-orchestration npx -- -y @trustedskills/zechenzhangagi-skypilot-multi-cloud-orchestration
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"zechenzhangagi-skypilot-multi-cloud-orchestration": {
"command": "npx",
"args": [
"-y",
"@trustedskills/zechenzhangagi-skypilot-multi-cloud-orchestration"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
Skypilot Multi-Cloud Orchestration automates and simplifies running machine learning (ML) workloads across a variety of cloud providers, including AWS, GCP, Azure, Kubernetes, Lambda, and RunPod, among 20+ others. It focuses on cost optimization by automatically selecting the cheapest available cloud region and leveraging spot instances for significant savings. The skill also enables distributed training and managed jobs with features like auto-recovery and checkpointing.
When to use it
- You need to run ML workloads across multiple cloud providers (AWS, GCP, Azure, etc.).
- Cost optimization is a priority, and you want automatic selection of the most affordable cloud region.
- You're running long jobs and want to take advantage of spot instances with automated recovery from interruptions.
- You require support for distributed multi-node training.
- You desire a unified interface for managing resources across numerous cloud providers and wish to avoid vendor lock-in.
Key capabilities
- Multi-cloud Support: Works with AWS, GCP, Azure, Kubernetes, Lambda, RunPod, and 20+ other providers.
- Cost Optimization: Automatically selects the cheapest available cloud region.
- Spot Instance Utilization: Leverages spot instances for cost savings (up to 3-6x) with automatic recovery.
- Distributed Training: Supports multi-node jobs with gang scheduling.
- Managed Jobs: Provides auto-recovery, checkpointing, and fault tolerance features.
- Sky Serve: Enables model serving with autoscaling capabilities.
Example prompts
- "Launch a cluster on the cheapest available cloud region using spot instances to run my training script."
- "Deploy my machine learning model for serving with autoscaling enabled."
- "Run this task, specifying an A100 GPU and ensuring it uses spot instances."
Tips & gotchas
- You'll need to install the SkyPilot package:
pip install "skypilot[aws,gcp,azure,kubernetes]". - Ensure you have valid cloud credentials configured using
sky checkbefore launching any tasks. - SkyPilot is designed for ML workloads; consider alternatives like Modal or Ray if your needs are more specialized.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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Passed automated security scans.