Deploy SkyPilot on existing machines#
This guide will help you deploy SkyPilot on your existing machines — whether they are on-premises or reserved instances on a cloud provider.
Given a list of IP addresses and SSH credentials, SkyPilot will install necessary dependencies on the remote machines and configure itself to run jobs and services on the cluster.
Note
Behind the scenes, SkyPilot deploys a lightweight Kubernetes cluster on the remote machines using k3s.
Note that no Kubernetes knowledge is required for running this guide. SkyPilot abstracts away the complexity of Kubernetes and provides a simple interface to run your jobs and services.
Prerequisites#
Local machine (typically your laptop):
Remote machines (your cluster, optionally with GPUs):
Debian-based OS (tested on Debian 11)
SSH access from local machine to all remote machines with key-based authentication and passwordless sudo
All machines must use the same SSH key and username
All machines must have network access to each other
Port 6443 must be accessible on at least one node from your local machine
Deploying SkyPilot#
Create a file
ips.txt
with the IP addresses of your machines with one IP per line. The first node will be used as the head node — this node must have port 6443 accessible from your local machine.Here is an example
ips.txt
file:192.168.1.1 192.168.1.2 192.168.1.3
In this example, the first node (
192.168.1.1
) has port 6443 open and will be used as the head node.Run
sky local up
and pass theips.txt
file, SSH username, and SSH key as arguments:IP_FILE=ips.txt SSH_USER=username SSH_KEY=path/to/ssh/key sky local up --ips $IP_FILE --ssh-user SSH_USER --ssh-key-path $SSH_KEY
SkyPilot will deploy a Kubernetes cluster on the remote machines, set up GPU support, configure Kubernetes credentials on your local machine, and set up SkyPilot to operate with the new cluster.
Example output of
sky local up
:$ sky local up --ips ips.txt --ssh-user gcpuser --ssh-key-path ~/.ssh/id_rsa Found existing kube config. It will be backed up to ~/.kube/config.bak. To view detailed progress: tail -n100 -f ~/sky_logs/sky-2024-09-23-18-53-14-165534/local_up.log ✔ K3s successfully deployed on head node. ✔ K3s successfully deployed on worker node. ✔ kubectl configured for the remote cluster. ✔ Remote k3s is running. ✔ Nvidia GPU Operator installed successfully. Cluster deployment done. You can now run tasks on this cluster. E.g., run a task with: sky launch --cloud kubernetes -- echo hello world. 🎉 Remote cluster deployed successfully.
To verify that the cluster is running, run:
sky check kubernetes
You can now use SkyPilot to launch your development clusters and training jobs on your own infrastructure.
$ sky show-gpus --cloud kubernetes Kubernetes GPUs GPU REQUESTABLE_QTY_PER_NODE TOTAL_GPUS TOTAL_FREE_GPUS L4 1, 2, 4 12 12 H100 1, 2, 4, 8 16 16 Kubernetes per node GPU availability NODE_NAME GPU_NAME TOTAL_GPUS FREE_GPUS my-cluster-0 L4 4 4 my-cluster-1 L4 4 4 my-cluster-2 L4 2 2 my-cluster-3 L4 2 2 my-cluster-4 H100 8 8 my-cluster-5 H100 8 8 $ sky launch --cloud kubernetes --gpus H100:1 -- nvidia-smi
Tip
You can also use
kubectl
to interact and perform administrative operations on the cluster.
What happens behind the scenes?#
When you run sky local up
, SkyPilot runs the following operations:
Install and run k3s Kubernetes distribution as a systemd service on the remote machines.
[If GPUs are present] Install Nvidia GPU Operator on the newly provisioned k3s cluster. Note that this step does not modify your local nvidia driver/cuda installation, and only runs inside the cluster.
Expose the Kubernetes API server on the head node over port 6443. API calls are on this port are secured with a key pair generated by the cluster.
Configure
kubectl
on your local machine to connect to the remote cluster.
Cleanup#
To clean up all state created by SkyPilot on your machines, use the --cleanup
flag:
IP_FILE=ips.txt
SSH_USER=username
SSH_KEY=path/to/ssh/key
sky local up --ip $IP_FILE --ssh-user SSH_USER --ssh-key-path $SSH_KEY --cleanup
This will stop all Kubernetes services on the remote machines.