Image requirements
This document outlines the specifications for creating a standardized image used in Anyscale infrastructure. It details the system requirements, essential software packages, and the Python libraries needed to ensure compatibility and performance in Anyscale environments.
System requirements
- Base image: Use
ubuntu:22.04
as image foundation, ensuring a stable and widely supported Linux environment. - User configuration: Include
ray
user with user ID1000
and group ID100
. Also,ray
needs to able to runsudo
without a password. - Working directory: Set
WORKDIR
to/home/ray
, which designates the primary directory for user operations and application execution. Ensure that theray
user has read and write permissions to this directory. - Home directory: Set
/home/ray
asHOME
, centralizing user configurations and runtime files.
System
sudo
python
bash
openssh-server
openssh-client
rsync
zip
unzip
git
gdb
curl
Python
ray>=2.7
anyscale
packaging
boto3
google
google-cloud-storage
jupyterlab
Anyscale reserved resources
Filesystem Paths:
/etc/anyscale
/opt/anyscale
/tmp/anyscale
/tmp/ray
/mnt/
Network Ports:
80, 443, 1010, 1012, 2222, 5555, 5903, 6379, 6822, 6823, 6824, 6826, 7878, 8000 ,8076, 8085, 8201, 8265, 8266, 8686, 8687, 8912, 8999, 9090, 9092, 9100, 9478 ,9479, 9480, 9481, 9482
Workspace Dependencies
If the image is intended to run on Workspaces, the following additional dependencies are required:
- Persistent Bash History: Add
PROMPT_COMMAND="history -a"
to/home/ray/.bashrc
to ensure that the bash history is saved after each command. - Source .workspacerc:
source ~/.workspacerc
if it exists.
Example Dockerfile
# syntax=docker/dockerfile:1.3-labs
FROM ubuntu:22.04
ENV DEBIAN_FRONTEND=noninteractive
# Install basic dependencies and setup `ray` user with sudoer permissions.
# Note that `ray` user should be (uid: 1000, gid: 100) to work with shared file
# systems.
# Add gdb since Ray dashboard uses `memray attach`, which requires gdb.
RUN <<EOF
#!/bin/bash
set -euxo pipefail
apt-get update -y
apt-get install -y --no-install-recommends sudo tzdata openssh-client openssh-server rsync zip unzip git gdb
# Install Python -- you can replace this with whatever Python installation method
# you want (i.e. conda, etc...), as long as `python` is on PATH. At runtime
# we'll source `/home/ray/.bashrc` in case you modify PATH there. This example uses
# virtualenv
apt-get install -y python3-venv
apt-get clean
rm -rf /var/lib/apt/lists/*
# Work around for https://bugs.launchpad.net/ubuntu/+source/openssh/+bug/45234
mkdir -p /var/run/sshd
useradd -ms /bin/bash -d /home/ray ray --uid 1000 --gid 100
usermod -aG sudo ray
echo 'ray ALL=NOPASSWD: ALL' >> /etc/sudoers
EOF
# Switch to `ray` user
USER ray
ENV HOME=/home/ray
ENV PATH=/home/ray/virtualenv/bin:$PATH
RUN <<EOF
#!/bin/bash
# Run as user `ray` from here.
su --login ray
python3 -m venv --system-site-packages /home/ray/virtualenv
export PATH=/home/ray/virtualenv/bin:$PATH
# jupyterlab is only needed if you want to access Jupyter notebooks from the web UI.
# Note that this only installs `ray[default]` to minimize the amount of dependencies,
# you can add extra libraries such as tune with `ray[default,tune]`. See the Ray
# docs for more info: https://docs.ray.io/en/latest/ray-overview/installation.html
pip install --no-cache-dir anyscale jupyterlab ray[default]
# If you want to run your cluster on Google Cloud Platform, you should uncomment the following line.
# pip install --no-cache-dir google google-cloud-storage
# Start of workspace dependencies: this section is only needed if you want your image to run on workspaces.
# This flushes bash history after each command, so that workspaces can persist it.
echo 'PROMPT_COMMAND="history -a"' >> /home/ray/.bashrc
# If the workspacerc exists, load it.
echo '[ -e ~/.workspacerc ] && source ~/.workspacerc' >> /home/ray/.bashrc
# End of Workspace dependencies
EOF