Datalore 2023.4 Help

Datalore Enterprise installation guide

This page is an overview of Datalore Enterprise installation options. You can skip it and advance directly to the installation topics. However, we recommend reading this page to get a better idea of the entire process.

What is Datalore Enterprise

Datalore Enterprise is a self-hosted version of Datalore, tailored for teams that want to have a collaborative data science platform set up on their own infrastructure.

Watch Datalore overview or schedule a personalized demo with our team to learn more about the product.

How to get support

Installation process overview

The installation workflow comprises the following stages:

Infrastructure preparation and installation method selection

Before the installation of Datalore Enterprise itself, prepare the platform where you want to deploy it. Once the platform is prepared, select your installation method:

Refer to the table below to consider your infrastructure options and compare the two installation methods.

Docker deployment

Kubernetes deployment


The following options are suitable for both methods:

General information

Docker Compose method

This method is recommended unless you specifically want to use a Kubernetes cluster.

If you have not decided which platform or service to choose yet, we recommend that you try installing Datalore Enterprise on an AWS EC2 instance. Refer to this guide to learn how to create your own infrastructure in AWS.

Helm charts method

Besides creating and running a cluster directly on a virtual machine (eg. EC2 instance), you can use dedicated Kubernetes services:

Key differences

  • Docker-based installation is quicker and easier, which makes it more suitable for a wider range of customers

  • Kubernetes deployment allows you to use several machines in your Datalore infrastructure and control your computational resources.

Hardware requirements

  • Datalore server machine RAM: 4GB (the number of CPU is irrelevant if the load is not high)

  • 8 GB for 2 agents working in parallel

Because users have different needs and projects, we can only suggest a simplified formula for you to get a better idea of how calculating this value can be done:

4 * (N + 1)
where N is the number of projected users, each working on one document.

For example, for a team of 10 people working as described above, you will need at least 44 GB of RAM.

System requirements

  • Docker

  • Docker Compose v2.2.3

  • k8s cluster

  • Kubectl on your machine pointed to this cluster

  • Helm

This installation was tested with Kubernetes v1.24 and Helm v3.11.1, but other versions may work too.

Basic installation

The next stage is the basic installation procedure that allows you to get Datalore Enterprise up and running on the infrastructure of your choice. Follow one of the guides below to use the method you selected.

As a result, you will have Datalore Enterprise installed and ready for use, as well as your first signed-up Datalore user, who will have the administrator rights.

Configuration procedures

Whichever basic installation method you choose, it is followed by a set of configuration procedures.

The table below lists all configuration procedures. Unless noted otherwise, a procedure is applicable for both installation methods.




Configure agents (Docker | Helm)

Used to customize how your agents work to manage your computational resources

Set up GPU machines (Docker | Helm)

Used to enable GPU machines

Configure plans (Docker | Helm)

Used to customize resource usage among your Datalore users


Customize or update environment

Used to create multiple base environments out of custom Docker images

Set up JetBrains Hub (Docker | Helm)

Used to integrate an authentication service

Enable gift codes (Docker | Helm)

Used to enable a service generating and distributing gift codes

Enable email service (Docker | Helm)

Used to activate email notifications

Enable user activity logging (Docker | Helm)

Used to set up auditing of your Datalore users

Upgrade your version

Each installation method has its own upgrade procedure:

We duly notify our customers of new version releases so they can promptly upgrade. Generally, upgrading a Docker-based installation is quicker and easier than the Kubernetes-based one.

Last modified: 28 August 2023