SkyPilot：統一管理 Kubernetes、20+雲端及本地AI運算的一站式系統

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Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, 20+ clouds, or on-prem).

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Run AI on Any Infrastructure

SkyPilot is a system to run, manage, and scale AI workloads on any AI infrastructure.

SkyPilot gives AI teams a simple interface to run jobs on any infra.
Infra teams get a unified control plane to manage any AI compute — with advanced scheduling, scaling, and orchestration.

🔥 News 🔥

Overview

SkyPilot is easy to use for AI teams:

SkyPilot makes Kubernetes easy for AI & Infra teams:

SkyPilot unifies multiple clusters, clouds, and hardware:

SkyPilot cuts your cloud costs & maximizes GPU availability:

SkyPilot supports your existing GPU, TPU, and CPU workloads, with no code changes.

Install with pip:

To get the latest features and fixes, use the nightly build or install from source:

Current supported infra: Kubernetes, Slurm, AWS, GCP, Azure, OCI, CoreWeave, Nebius, Lambda Cloud, RunPod, Fluidstack,
Cudo, Digital Ocean, Paperspace, Cloudflare, Samsung, IBM, Vast.ai, VMware vSphere, Seeweb, Prime Intellect, Shadeform.

Getting started

You can find our documentation here.

SkyPilot in 1 minute

A SkyPilot task specifies: resource requirements, data to be synced, setup commands, and the task commands.

Once written in this unified interface (YAML or Python API), the task can be launched on any available infra (Kubernetes, Slurm, cloud, etc.). This avoids vendor lock-in, and allows easily moving jobs to a different provider.

Paste the following into a file my_task.yaml:

Prepare the workdir by cloning:

Launch with sky launch (note: access to GPU instances is needed for this example):

SkyPilot then performs the heavy-lifting for you, including:

See Quickstart to get started with SkyPilot.

Runnable examples

See SkyPilot examples that cover: development, training, serving, LLM models, AI apps, and common frameworks.

Latest featured examples:

Source files can be found in llm/ and examples/.

More information

To learn more, see SkyPilot Overview, SkyPilot docs, and SkyPilot blog.

SkyPilot adopters: Testimonials and Case Studies

Partners and integrations: Community Spotlights

Follow updates:

Read the research:

SkyPilot was initially started at the Sky Computing Lab at UC Berkeley and has since gained many industry contributors. To read about the project's origin and vision, see Concept: Sky Computing.

Questions and feedback

We are excited to hear your feedback:

For general discussions, join us on the SkyPilot Slack.

Contributing

We welcome all contributions to the project! See CONTRIBUTING for how to get involved.

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