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skypilot-multi-cloud-orchestration

Official

Run ML workloads across clouds.

Software Engineering#orchestration#infrastructure#cost optimization#gpu#multi-cloud#skypilot
AuthorOrchestra-Research
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill simplifies and optimizes the execution of machine learning workloads across multiple cloud providers, significantly reducing costs and complexity.

Core Features & Use Cases

  • Multi-Cloud Orchestration: Seamlessly run jobs on AWS, GCP, Azure, and more.
  • Cost Optimization: Automatically selects the cheapest cloud and instance types, leveraging spot instances for up to 6x savings.
  • Distributed Training: Manages multi-node training setups with ease.
  • Model Serving: Deploy and scale ML models with Sky Serve.
  • Use Case: You need to train a large language model that requires 32 A100 GPUs. Use this Skill to find the most cost-effective way to provision these resources across AWS and GCP, ensuring your training job runs reliably even if spot instances are preempted.

Quick Start

Install SkyPilot and check your cloud credentials by running pip install skypilot[aws,gcp,azure,kubernetes] followed by sky check.

Dependency Matrix

Required Modules

None required

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: skypilot-multi-cloud-orchestration
Download link: https://github.com/Orchestra-Research/AI-Research-SKILLs/archive/main.zip#skypilot-multi-cloud-orchestration

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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