skypilot-multi-cloud-orchestration

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.

by Orchestra-Research 12k GitHub stars MIT Updated Jun 16, 2026
skypilot-multi-cloud-orchestration skill by Orchestra-Research
skypilot-multi-cloud-orchestration — DevOps skill by Orchestra-Research

Overview

skypilot-multi-cloud-orchestration is an open-source devops skill for Claude Code and compatible agents, published by Orchestra-Research. Its author describes it as: “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 ac…”. The project has 12k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`.

What skypilot-multi-cloud-orchestration does

Comprehensive guide to running ML workloads across clouds with automatic cost optimization using SkyPilot.

Best for

What’s inside

The SKILL.md for skypilot-multi-cloud-orchestration is organised into these sections:

  • When to use SkyPilot
  • Quick start
  • Installation
  • Hello World
  • Core concepts
  • Task YAML structure
  • Key commands
  • GPU configuration
  • Available accelerators
  • GPU fallbacks
  • Spot instances
  • Cluster management

Installation

Add skypilot-multi-cloud-orchestration to your agent with:

/plugin marketplace add Orchestra-Research/AI-Research-SKILLs

Review a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.

Supported agents

  • Claude Code — ships a claude code plugin marketplace
  • Codex — declared in the repository topics

License

skypilot-multi-cloud-orchestration is published under the MIT license.

Strengths

  • Clear MIT license — safe to read and adapt within its terms
  • Ships in Orchestra-Research/AI-Research-SKILLs, an established project with 11,807 GitHub stars
  • Works with Claude Code, Codex

Author

Orchestra-Research 41 skills in the catalog · GitHub profile ↗
View skills

Topics

Need a skill like this, tailored to your team?Build a custom skill →

Frequently asked questions

What does skypilot-multi-cloud-orchestration do?
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.
How do I install skypilot-multi-cloud-orchestration?
Run /plugin marketplace add Orchestra-Research/AI-Research-SKILLs in your agent, then reload your skills. Review the source at https://github.com/Orchestra-Research/AI-Research-SKILLs before installing.
Is skypilot-multi-cloud-orchestration free to use?
Yes. skypilot-multi-cloud-orchestration is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
Which agents does skypilot-multi-cloud-orchestration work with?
skypilot-multi-cloud-orchestration lists Claude Code and Codex — named in its SKILL.md, its plugin marketplace or its repository topics. Skills use the portable SKILL.md format, so other agents that read that format may load it too.
Where does skypilot-multi-cloud-orchestration come from?
skypilot-multi-cloud-orchestration ships inside Orchestra-Research/AI-Research-SKILLs, a repository that contains 41 catalogued skills in total. The repository's 11,807 GitHub stars apply to that whole collection, not to this skill on its own.

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

Claude CodeCodex
12k GitHub stars MIT Updated Jun 16, 2026 Free

Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

Claude CodeCodex
12k GitHub stars MIT Updated Jun 16, 2026 Free

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

Claude CodeCodex
12k GitHub stars MIT Updated Jun 16, 2026 Free

Install our local first extensions for your favorite AI IDE or Terminal Agent. Process your histories into reusable skills with Lore. Sync your conversations to the cloud. File issues and requests.

Claude CodeCodexCursor+1
1.3k GitHub stars Apache-2.0 Updated Jul 29, 2026 Free

Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

↑ Growing Claude CodeCodexCursor+3
39k GitHub stars MIT Updated Aug 24, 2026 Free