Datalore On-Premises

Deploy Datalore On-Premises on Kubernetes or Docker and run the instance: manage users, licenses, environments, monitoring, backups, and upgrades.

What’s new : Check which features, improvements, and fixes shipped in each Datalore On-Premises release
Datalore On-Premises in AWS : Plan an AWS deployment against the reference architecture: supported regions, IAM permissions, networking, and database options

Installation

Kubernetes (Helm method) : Deploy Datalore On-Premises to a Kubernetes cluster with Helm charts, including hardware requirements and AWS EKS specifics
Docker-based installation : Deploy Datalore On-Premises in Docker containers with Docker Compose, a custom domain, and an external Postgres database

Kubernetes deployment : Upgrade a Helm deployment to the current version, applying the version-specific steps on the way
Docker deployment : Upgrade a Docker deployment to the current version, applying the version-specific steps on the way

Enable SSO for Kubernetes deployment : Install Hub next to a Helm deployment and register Datalore as a Hub service to enable single sign-on
Enable SSO for Docker deployment : Run Hub next to a Docker deployment and register Datalore as a Hub service to enable single sign-on
Upgrade Hub : Move Hub to a newer version along the recommended update path without breaking its connection to Datalore

Set up external agents : Run computational agents outside the Datalore infrastructure: open the required ports, configure Docker or Kubernetes nodes, and connect them to your instance
Customize or update environment : Build custom Python or R environments for your instance, generate editor indexes, and point package installs at your own PyPI server
Manage users : Create users and viewers, change their roles and plans, and ban, delete, or take over the workspaces of individual accounts
Manage user groups: Create, edit, and delete user groups, share resources with them, and keep them in sync with Hub groups
Manage licenses : Obtain a license key and activate or reactivate your Datalore instance with it
Customize data integration : Add third-party JDBC drivers and set up instance-wide database connections your users can reuse

Server lifecycle events : Restart or shut down a Kubernetes or Docker deployment without losing user data
Security : Review how sensitive data flows through Datalore, how CVEs are handled, and what to account for in your own security assessment
High availability : Reduce downtime for the Datalore server, its backend database, and notebook agents
Healthcheck and monitoring : Query the healthcheck endpoint and collect Datalore metrics in your monitoring stack
Backup, restore, and migrate : Back up a running instance, restore it, and migrate a deployment to new infrastructure
Emergency maintenance : Use the administrative API to regain access, clone workspaces, and recover an instance with or without a backup