alchemiscale consists of multiple services that can be independently scaled. This document details on how to deploy and configure the “server” services in a number of ways. The “server” services need not be deployed to the same physical host, though you may choose to do so.

Only Linux is supported as a platform for deploying alchemiscale services; Windows and OSX are not recommended as deployment targets.

Single-host deployment with docker-compose

An alchemiscale “server” deployment consists of a neo4j database (the “state store”), a client API endpoint, a compute API endpoint, and a reverse proxy (traefik). The client and compute API endpoints can be scaled by adjusting the number of workers. A single docker-compose.yml file defines all of these services. Because our deployment process is containerized, the only requirement for the host is to be able to run docker compose in a x86_64 environment. Installation of alchemiscale software dependencies is unnecessary on the host itself.

The “server” also requires an object store; see Setting up an object store.

Deployment instructions

Install docker compose. We recommend using “Scenario two: Install the Compose plugin” since Docker Desktop may require a paid subscription. First install the docker engine and then install the plugin.

Now clone the repository and then navigate to the alchemiscale/docker/alchemiscale-server folder:

$ git clone
$ cd alchemiscale/docker/alchemiscale-server


It is not strictly necessary to clone the repository. For host deployment, only alchemiscale/docker/alchemiscale-server/docker-compose.yml and either a .env file and/or environment variables set are needed. By cloning the repository, a git pull can be used to retrieve an updated .env.template and docker-compose.yml which may be useful.

Now make a copy of .env.template:

$ cp .env.template .env

and modify .env with your favorite text editor.


The .env file will contain sensitive information and should not be checked into version control or shared publicly.

See .env.testing for an example.

The neo4j database requires the directory for the data store to exist before it starts. This location should be on a storage medium that can handle the IOPS demand of a neo4j database. For example, using the location set in .env.testing:

$ mkdir -p data/server

Now start the service with:

$ USER_ID=$(id -u) GROUP_ID=$(id -g) docker-compose up -d

We set USER_ID and GROUP_ID to be the same as the user running the docker-compose up -d command.

Setting up a host on AWS EC2


This is a guide on how to setup a fresh EC2 x86_64 instance running a Amazon Linux 2023 AMI. These steps should generally work for other Linux distributions, but may require some modification e.g. the package manager may be apt instead of dnf.

Once connected to the instance, run the following commands:

$ sudo dnf check-release-update  # Check for updates
$ sudo dnf --releasever=version update  # Update if new version is available NOTE: This guide used Amazon Linux Version 2023.1.20230705
$ sudo dnf -y install docker git
$ sudo service docker start  # Start docker service
$ sudo systemctl enable docker.service  # Start docker service on boot
$ sudo usermod -a -G docker ec2-user  # Add ec2-user to docker group
$ newgrp docker  # Trick so we don't have to reboot (or login and logout) after adding ec2-user to docker group
# Now we have to manually install the docker compose plugin until this issue gets resolved
$ DOCKER_CONFIG=${DOCKER_CONFIG:-$HOME/.docker}  # Set location to install plugin
$ mkdir -p $DOCKER_CONFIG/cli-plugins  # Create the directory to install the plugin
$ curl -SL -o $DOCKER_CONFIG/cli-plugins/docker-compose  # Download plugin
$ chmod +x $DOCKER_CONFIG/cli-plugins/docker-compose  # Set executable permissions to the plugin
$ docker info  # Test if everything works
$ docker compose version  # Test if plugin was installed correctly

Now the instance has all of the dependencies required for docker-compose-based deployment (Deployment instructions)

Kubernetes-based deployment with alchemiscale-k8s

To deploy alchemiscale to a Kubernetes cluster, review the resources defined and detailed in alchemiscale-k8s.

Setting up an object store

An “object store” is also needed for a complete server deployment. Currently, the only supported object store is AWS S3.

Create a private AWS S3 bucket, then provide the following environment variables to the client and compute API services:


The name of the AWS S3 bucket to use.


The prefix within the bucket to use for all objects; typically set to objectstore


The AWS region the bucket exists in.

If your API services are deployed on AWS resources, you should grant those resources role-based access to S3. If your API services are deployed on resources outside AWS, you will need to give your services an access key on a user account with S3 access permissions.


The ID of the access key.


The access key content itself.

No additional setup is required for the object store.