SkyPilot

Free

Run LLMs and batch jobs on any cloud. Get maximum cost savings, highest GPU availability, and managed execution -- all with a simple interface.

FreeFree tier

Type

Open Source

Visit Website GitHub (38 stars)

About SkyPilot

SkyPilot is an open-source system for running, managing, and scaling AI workloads across any AI infrastructure. It provides a unified control plane that gives AI teams a simple interface to run jobs on any cloud, Kubernetes cluster, Slurm cluster, or on-prem hardware. Key capabilities include advanced scheduling with gang scheduling and binpacking, automatic resource cleanup (autostop), multi-cluster orchestration, and support for 20+ cloud providers. SkyPilot also offers features like Job Groups for reinforcement learning, Agent Skills for AI agents, pool autoscaling for batch inference, and sandboxes for running untrusted LLM-generated code. It maximizes GPU fleet utilization and reduces costs through intelligent scheduling and automatic failover across clouds.

Key Features

Unified control plane for multiple clusters, clouds, and hardware

Supports 20+ cloud providers, Kubernetes, Slurm, and on-prem

Automatic resource cleanup (Autostop) and idle binpacking

Intelligent scheduler with gang scheduling and multi-cluster failover

Job Groups for reinforcement learning and parallel experiments

Pool autoscaling for batch inference workloads

Agent Skills for AI agents to request and manage GPU access

Sandboxes for safe execution of untrusted LLM-generated code

GPU Compass: dashboard to browse and compare GPU pricing across clouds

Environment and job as code for portability and reproducibility

Pros & Cons

Pros

Open source and free to use
Supports a wide variety of infrastructure (20+ clouds, K8s, Slurm, on-prem)
Significant cost savings through autostop and binpacking
High GPU availability via smart failover across clouds
Simplifies job management with queueing, auto-recovery, and environment-as-code
Active development with frequent releases and community contributions
Includes advanced scheduling features like gang scheduling for distributed training

Cons

Requires familiarity with cloud and/or Kubernetes concepts to set up and operate
Documentation may be extensive; learning curve for new users
Not a managed SaaS; users must manage their own infrastructure

Best For

Running LLM inference and batch jobs on any cloud with cost optimizationManaging GPU fleets across multi-cloud and on-prem environmentsScaling AI training workloads with gang scheduling and autoscalingEnabling AI agents to autonomously request and use compute resourcesRunning untrusted code (e.g., LLM sandboxes) on owned Kubernetes clustersComparing GPU pricing and launching instances across multiple clouds

FAQ

What infrastructure does SkyPilot support?

SkyPilot supports 20+ cloud providers, Kubernetes clusters, Slurm clusters, and on-prem hardware. It provides a unified interface to manage all of them.

Is SkyPilot free?

Yes, SkyPilot is open-source and free to use. It is licensed under the Apache License 2.0 and available on GitHub.

Can SkyPilot be used for reinforcement learning?

Yes, SkyPilot supports Job Groups which are designed for reinforcement learning workflows, allowing parallel experiments and coordinated job execution.

How does SkyPilot help with GPU costs?

SkyPilot reduces GPU costs through automatic cleanup of idle resources (Autostop), binpacking workloads on shared clusters, and intelligent scheduling that can failover to cheaper or available clouds.