Start a Development Cluster — SkyPilot documentation (original) (raw)

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SkyPilot makes interactive development easy on Kubernetes or cloud VMs. It helps you:

  1. Launch: Quickly get a cluster with GPUs or other resources with a single command.
  2. Autostop: Automatically stop the cluster after some idle time for cost savings.
  3. Connect: Easily connect to the cluster using the cluster name:

Launch#

To launch a cluster with a cheap GPU for development:

Launch a cluster with 1 NVIDIA GPU and sync the local working directory to the

cluster.

sky launch -c dev --gpus L4 --workdir .

This can be launched as a pod in your Kubernetes cluster or a VM on any cloud.

Kubernetes

Launch a cluster as a pod in Kubernetes

Launch a cluster as a pod in Kubernetes#

Cloud

Launch a cluster as a VM on GCP

Launch a cluster as a VM on GCP#

Note

View the supported GPUs with the sky show-gpus command.

Autostop#

SkyPilot allows you to automatically stop the cluster after a period of idle time to save costs. You can set the autostop time with a single command:

Auto stop the cluster after 5 hours

sky autostop -i 300 dev

Or add an additional flag -i during the launch:

Launch a cluster with auto stop after 5 hours

sky launch -c dev --gpus L4 --workdir . -i 300

For more details of auto stopping, check out: Autostop and Autodown. This feature is designed to prevent idle clusters from incurring unnecessary costs, ensuring your cluster stops automatically, whether it’s overnight or throughout the weekend.

Connect#

A user can easily connect to the cluster using your method of choice:

SSH#

SkyPilot will automatically configure the SSH setting for a cluster, so that users can connect to the cluster with the cluster name:

VSCode#

A common use case for interactive development is to connect a local IDE to a remote cluster and directly edit code that lives on the cluster. This is supported by simply connecting VSCode to the cluster with the cluster name:

  1. Click on the top bar, type: > remote-ssh, and select Remote-SSH: Connect Current Window to Host...
  2. Select the cluster name (e.g., dev) from the list of hosts.
  3. Open folder: sky_workdir and find your code.

For more details, please refer to the VSCode documentation.

Connect to the cluster with VSCode

Jupyter notebooks#

Jupyter notebooks are a useful tool for interactive development, debugging, and visualization.

Connect to the machine and forward the port used by jupyter notebook:

ssh -L 8888:localhost:8888 dev

Inside the cluster, you can run the following commands to start a Jupyter session:

pip install jupyter jupyter notebook

In your local browser, you should now be able to access localhost:8888 and see the following screen:

Jupyter authentication window

Enter the password or token and you will be directed to a page where you can create a new notebook.

Create a new Jupyter notebook

You can verify that this notebook is running on the GPU-backed instance using nvidia-smi.

nvidia-smi in notebook

The GPU node is a normal SkyPilot cluster, so you can use the usual CLI commands on it. For example, run sky down/stop to terminate or stop it, and sky exec to execute a task.

Notebooks in SkyPilot tasks#

Jupyter notebooks can also be used in SkyPilot tasks, allowing access to the full range of SkyPilot’s features including mounted storage andautostop.

The following jupyter.yaml is an example of a task specification that can launch notebooks with SkyPilot.

jupyter.yaml

name: jupyter

resources: accelerators: L4:1

file_mounts: /covid: source: s3://fah-public-data-covid19-cryptic-pockets mode: MOUNT

setup: | pip install --upgrade pip conda init bash conda create -n jupyter python=3.9 -y conda activate jupyter pip install jupyter

run: | cd ~/sky_workdir conda activate jupyter jupyter notebook --port 8888 &

Launch the GPU-backed Jupyter notebook:

sky launch -c jupyter jupyter.yaml

To access the notebook locally, use SSH port forwarding.

ssh -L 8888:localhost:8888 jupyter

You can verify that this notebook has access to the mounted storage bucket.

accessing covid data from notebook

Working with clusters#

To see a typical workflow of working with clusters, you can refer to Quickstart.