This guide will walk you through:

  • Defining a task in a simple YAML format

  • Provisioning a cluster and running a task

  • Using the core SkyPilot CLI commands

Be sure to complete the installation instructions first before continuing with this guide.

Hello, SkyPilot!#

Let’s define our very first task, a simple Hello, SkyPilot! program.

Create a directory from anywhere on your machine:

$ mkdir hello-sky
$ cd hello-sky

Copy the following YAML into a hello_sky.yaml file:

  # Optional; if left out, automatically pick the cheapest cloud.
  cloud: aws
  # 1x NVIDIA V100 GPU
  accelerators: V100:1

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

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

# 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

This defines a task with the following components:

  • resources: cloud resources the task must be run on (e.g., accelerators, instance type, etc.)

  • workdir: the working directory containing project code that will be synced to the provisioned instance(s)

  • setup: commands that must be run before the task is executed (invoked under workdir)

  • run: commands that run the actual task (invoked under workdir)

All these fields are optional.

To launch a cluster and run a task, use sky launch:

$ sky launch -c mycluster hello_sky.yaml


This may take a few minutes for the first run. Feel free to read ahead on this guide.


You can use the -c flag to give the cluster an easy-to-remember name. If not specified, a name is autogenerated.

The sky launch command performs much heavy-lifting:

  • selects an appropriate cloud and VM based on the specified resource constraints;

  • provisions (or reuses) a cluster on that cloud;

  • syncs up the workdir;

  • executes the setup commands; and

  • executes the run commands.

In a few minutes, the cluster will finish provisioning and the task will be executed. The outputs will show Hello, SkyPilot! and the list of installed Conda environments.

Execute a task on an existing cluster#

Once you have an existing cluster, use sky exec to execute a task on it:

$ sky exec mycluster hello_sky.yaml

The sky exec command is more lightweight; it

  • syncs up the workdir (so that the task may use updated code); and

  • executes the run commands.

Provisioning and setup commands are skipped.

Bash commands are also supported, such as:

$ sky exec mycluster python train_cpu.py
$ sky exec mycluster --gpus=V100:1 python train_gpu.py

For interactive/monitoring commands, such as htop or gpustat -i, use ssh instead (see below) to avoid job submission overheads.

View all clusters#

Use sky status to see all clusters (across regions and clouds) in a single table:

$ sky status

This may show multiple clusters, if you have created several:

NAME       LAUNCHED     RESOURCES             COMMAND                            STATUS
mygcp      1 day ago    1x GCP(n1-highmem-8)  sky launch -c mygcp --cloud gcp    STOPPED
mycluster  4 mins ago   1x AWS(p3.2xlarge)    sky exec mycluster hello_sky.yaml  UP

See here for a list of all possible cluster states.

SSH into clusters#

Simply run ssh <cluster_name> to log into a cluster:

$ ssh mycluster

Multi-node clusters work too:

# Assuming 3 nodes.

# Head node.
$ ssh mycluster

# Worker nodes.
$ ssh mycluster-worker1
$ ssh mycluster-worker2

The above are achieved by adding appropriate entries to ~/.ssh/config.

Because SkyPilot exposes SSH access to clusters, this means clusters can be easily used inside tools such as Visual Studio Code Remote.

Transfer files#

After a task’s execution, use rsync or scp to download files (e.g., checkpoints):

$ rsync -Pavz mycluster:/remote/source /local/dest  # copy from remote VM

For uploading files to the cluster, see Syncing Code and Artifacts.

Stop/terminate a cluster#

When you are done, stop the cluster with sky stop:

$ sky stop mycluster

To terminate a cluster instead, run sky down:

$ sky down mycluster


Stopping a cluster does not lose data on the attached disks (billing for the instances will stop while the disks will still be charged). Those disks will be reattached when restarting the cluster.

Terminating a cluster will delete all associated resources (all billing stops), and any data on the attached disks will be lost. Terminated clusters cannot be restarted.

Find more commands that manage the lifecycle of clusters in the CLI reference.

Scaling out#

So far, we have used SkyPilot’s CLI to submit work to and interact with a single cluster. When you are ready to scale out (e.g., run 10s or 100s of jobs), SkyPilot supports two options:

  • Queue many jobs on your cluster(s) with sky exec (see Job Queue);

  • Use Managed Spot Jobs to run on auto-managed spot instances (users need not interact with the underlying clusters)

Managed spot jobs run on much cheaper spot instances, with automatic preemption recovery. Try it out with:

$ sky spot launch hello_sky.yaml

Next steps#

Congratulations! In this quickstart, you have launched a cluster, run a task, and interacted with SkyPilot’s CLI.

Next steps:

We invite you to explore SkyPilot’s unique features in the rest of the documentation.