README.md

Drift Monitoring

A simple to use library to monitor drift detection jobs.

TODO list

• Add gitlab/github actions, depends on final repository location.
• Add frontend to the integration tests and reverse proxy deps.
• Publish the client to pypi.
• Add database backup and restore services to compose.
• Add extra utilities to the compose services (Graphana, etc.).

Drift Monitoring client

A simple to use library to monitor drift detection jobs. Simply create a context in your script and use the monitor function to synchronize the job status with the monitoring server.

from drift_monitoring import DriftMonitoring

with DriftMonitor("model_1", mytoken_secret) as monitor:
    detected, detection_parameters = your_concept_detector()
    monitor.concept(detected, detection_parameters)
    detected, detection_parameters = your_data_detector()
    monitor.data(detected, detection_parameters)

Installation

To install the client, you can use the following command:

pip install drift-monitor

MyToken

MyToken are special access token that can last for a long time. They are used to authenticate the client with the server. To create a MyToken, you can visit mytoken.data.kit.edu.

We recommend that you create a MyToken that only has access to the drift monitoring server.

Drift Monitoring server

A server that stores drift detection to simplify and monitor jobs. Provides a dashboard to visualize the results. The server is composed of multiple components:

• A Mongo database to store the drift detection jobs and data.
• A backend to handle authentication and database interface.
• A frontend to visualize the drift detection jobs.
• A reverse proxy to handle https and expose the API.

Run in Production

Before starting the server, you need to generate the following secrets on /secrets folder:

• app_database_password: Mongo database password.

Once the secrets are generated, you also need to create and configure the .env file with the required variables. You can use the .env.sample file as a template.

Once all the environment variables and secrets are set, you can start the server by running:

docker compose -f compose.yml -f compose.prod.yml up --build

This command will start, all containers. Database is stored in a docker volume, so it will persist between restarts. For the first time, a new certificate will be generated and stored in /letsencrypt, do not share this folder. Renewal of the certificate is done automatically.

Due to security issues, it is not possible to run in production mode as "localhost". You need to set the APP_DOMAIN_NAME to a valid domain name. See edudns as an example of an university domain name.

To stop the server, you can run:

docker compose down

Run in Development

Secrets are not required for development, the folder /sandbox contains a set of secrets and database items that are automatically loaded when using compose.override.yml. However, it is still required to create the .env file with the required variables and use a valid domain name.

To start the server in development mode, you can run:

docker compose up --build

Certificates are generated automatically, from letsencrypt staging server to avoid rate limiting. The certificates are NOT mounted and stored in only in the reverse proxy container.

After the containers are running, you can access when running in development mode, you need to attache a debugger to the backend and frontend services to start the python execution.

To stop the server, you can run:

docker compose down

Integration tests

To test a component you can run compose with the test file, for example:

docker compose -f compose.yml -f compose.test.yml run --build --rm testing

It will run the tests on tests folder with services running as close to production as possible (except for using a staging certificate). Note that after testing is complete, the remove step does not stop the rest of services, to stop all services you can run:

docker compose down