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SkyPilot is a framework for running LLMs, AI, and batch jobs on any cloud. This integration uses the Runpod CLI infrastructure to spin up on-demand Pods and deploy Serverless endpoints with SkyPilot.

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Get started

1

Obtain your API key

Get your API key from the Runpod Settings page.
2

Install Runpod

Install the latest version of Runpod:
pip install "runpod>=1.6"
3

Configure Runpod

Run runpod config and paste your API key when prompted.
4

Install SkyPilot Runpod Cloud

Install the SkyPilot Runpod cloud:
pip install "skypilot-nightly[runpod]"
5

Verify your setup

Run sky check to verify your credentials are set up correctly.

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Run a project

1

Create a new project directory

Create a new directory for your project:
mkdir hello-sky
cd hello-sky
2

Create a configuration file

Create a file named hello_sky.yaml with the following content:
resources:
  cloud: runpod

# Working directory (optional) containing the project codebase.
# Its contents are synced to ~/sky_workdir/ on the cluster.
workdir: .

# Setup commands (optional).
# Typical use: pip install -r requirements.txt
# Invoked under the workdir (i.e., can use its files).
setup: |
  echo "Running setup."

# Run commands.
# Typical use: make use of resources, such as running training.
# Invoked under the workdir (i.e., can use its files).
run: |
  echo "Hello, SkyPilot!"
  conda env list
3

Launch your project

Launch your project on the cluster:
sky launch -c mycluster hello_sky.yaml
4

Confirm your GPU type

You’ll see the available GPU options. Confirm your GPU type and the cluster will start spinning up.
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