GlitchTip

GlitchTip Backend

GlitchTip is an open source, Sentry API compatible error tracking platform. It is a partial fork/mostly re-implementation of Sentry's open source codebase before it went proprietary. Its goals are to be a modern, easy-to-develop error tracking platform that respects your freedom to use it any way you wish. Some differences include:

• A modern development environment with Python 3, Django 5, async, and types.
• Simplicity over features. We use Postgres to store error data. Our code base is a fraction of the size of Sentry and looks like a typical Django app. We leverage existing open source Django ecosystem apps whenever possible.
• Lightweight - GlitchTip runs with as little as 1GB of ram, PostgreSQL, and Redis.
• Respects your privacy. No massive JS bundles. No invasive tracking. No third party spying. Our marketing site runs the privacy-focused Plausible analytics. Self hosted GlitchTip will never report home. We will never know if you run it yourself.
• Commitment to open source. We use open source tools like GitLab whenever possible. With our MIT license, you can use it for anything you'd like and even sell it. We believe in competition and hope you make GlitchTip even better.

GlitchTip is a stable platform used in production environments for several years.

Developing

We use Docker for development. View our Contributing documentation if you'd like to help make GlitchTip better. See API Documentation

Run local dev environment

1. Ensure docker and docker-compose are installed
2. docker compose up
3. docker compose run --rm web ./manage.py migrate

Run tests with docker-compose run --rm web ./manage.py test

Run HTTPS locally for testing FIDO2 keys

1. cp docker-compose.yml docker-compose.override.yml
2. Edit the override file and set command: ./manage.py runsslserver 0.0.0.0:8000
3. Restart docker compose services

VS Code (Optional)

VS Code can do type checking and type inference. However, it requires setting up a virtual environment.

1. Install Python. For Ubuntu this is apt install python3-dev python3-venv
2. Install poetry
3. Create Python virtual environment python -m venv env
4. Activate environment source env/bin/activate
5. Install packages poetry install

Load testing

First set the env var IS_LOAD_TEST to true in docker-compose.yml

Locust is built into the dev dependencies. To run with Locust run docker compose -f docker-compose.yml -f docker-compose.locust.yml up

Now go to localhost:8089 to run the test.

Locust will not be installed to production docker images and cannot be run from them.

Observability metrics with Prometheus

1. Edit monitoring/prometheus/prometheus.yml and set credentials to a GlitchTip auth token
2. docker compose -f docker-compose.yml -f docker-compose.metrics.yml up

GCP Logging

In order to enable json logging, set the environment as follows::

DJANGO_LOGGING_HANDLER_CLASS=google.cloud.logging_v2.handlers.ContainerEngineHandler
UWSGI_LOG_ENCODER='json {"severity":"info","timestamp":${unix},"message":"${msg}"}}'

Acknowledgements

• Thank you to the Sentry team for their ongoing open source SDK work and formerly open source backend of which this project is based on.
• We use element.io for our public gitter room
• Plausible Analytics is used for analytics
• Django - no other web framework is as feature complete
• django-ninja/Pydantic - brings typed and async-first api design