Getting Started

• 1: Deployment
• 2: Advanced monitoring
• 3: Kubernetes deployment
• 4: Maintainance
• 5: Recommended setup

1 - Deployment

Clone via git

git clone --depth 1  https://github.com/taranis-ai/taranis-ai
cd taranis-ai/docker/

Configuration

Copy env.sample to .env

cp env.sample .env

Open file .env and change defaults if needed. More details about environment variables can be found here.

See Advanced monitoring for more logging insights.

Startup & Usage

Start-up application

docker compose up -d

Use the application

http://<url>:<TARANIS_PORT>/login

Initial Setup 👤

The default credentials are user / user and admin / admin.

The passwords for these two default users can be overridden by setting the environment variables PRE_SEED_PASSWORD_ADMIN or PRE_SEED_PASSWORD_USER before first launch. Afterwards they are stored in the database in the user table.

Open http://<url>:<TARANIS_PORT>/config/sources and click load default sources to import the default sources from: default_sources.json

Or import a source export via the Import.

2 - Advanced monitoring

Prerequisites

• Sentry instance available, either SaaS or self-hosted.
• Follow this guide to have a Sentry project (and SENTRY_DSN) ready.

What is Sentry

Sentry is a monitoring tool that enables more insights about an application. Taranis AI takes advantage of this if you enable it at the start up.

What is there to monitor

Sentry can be used to monitor insights about GUI, Core and database. In Taranis AI: Issues, Traces, Profiles and Queries can be tracked.

How to enable Sentry in Taranis AI

To enable Sentry, set the SENTRY_DSN variables in the .env file before start of the application. More details about environment variables can be found here.

GUI monitoring

To gain insights about GUI, use the TARANIS_GUI_SENTRY_DSN variable and set it to your Sentry DSN address.

Core and database monitoring

To gain insights about Core and database, use the TARANIS_CORE_SENTRY_DSN variable and set it to your Sentry DSN address.

3 - Kubernetes deployment

Configuration

Clone via git

git clone --depth 1  https://github.com/taranis-ai/taranis-ai
cd taranis-ai/docker/

Copy env.sample to .env

cp env.sample .env

Open file .env and change defaults if needed. More details about environment variables can be found here.

See Advanced monitoring for more logging insights.

Convert via Kompose

Download and install kompose.io

# resovle variables from .env into taranis-ai/docker/compose.yml 
docker compose config > resolved-compose.yml

# convert compose file to kubernetes 
kompose --file resolved-compose.yaml convert

4 - Maintainance

Supported upgrade of PostgreSQL 14.x to PostgreSQL 17.x. This upgrade is capable of upgrading a fully running instance of Taranis AI. Expect Taranis AI downtime during the process of the upgrade.

Prerequisites

• Installed Docker Compose V2 or podman-compose
• Running Taranis AI deployment using the docker/compose.yml file.
• Running database PostgreSQL of major version 14
• Compose file (docker/compose.yml) is setup to use the image of PostgreSQL 17 (check your POSTGRES_TAG variable in the .env file)

Steps to upgrade

1. Go to directory: taranis-ai/docker
2. Ensure the script upgrade-database.sh is executable
3. Run the script: ./upgrade-database.sh

All containers should now be again up and running!

5 - Recommended setup

For the best experience, we recommend the following minimal requirements for Taranis AI:

• Resolution: FullHD or more

• Browser:

  • Chromium
  • Mozilla Firefox
  • Microsoft Edge