python3-cyberfusion-rabbitmq-consumer-log-server 1.0

Log server for RabbitMQ consumer.

python3-cyberfusion-rabbitmq-consumer-log-server

Log server for RabbitMQ consumer.

Use the RabbitMQ consumer? The log server gives you an overview of RPC requests/responses - from all your RabbitMQ consumers - in one place.

Install

PyPI

Run the following command to install the package from PyPI:

pip3 install python3-cyberfusion-rabbitmq-consumer-log-server

Debian

Run the following commands to build a Debian package:

mk-build-deps -i -t 'apt -o Debug::pkgProblemResolver=yes --no-install-recommends -y'
dpkg-buildpackage -us -uc

Configure

The log server consists of two parts: a web-based GUI, and an API.

API

The RabbitMQ consumer writes RPC requests/responses to the API. To let the consumer ship logs to the log server, see the consumer's README.

In the consumer, an API token must be set. Set it in /etc/rabbitmq-consumer-log-server/api_token (regular text file).

You can generate a random API token using openssl: openssl rand -hex 32

You don't need to keep the API token confidential: it's only used by the RabbitMQ consumer to write logs. Therefore, abuse would be a nuisance at the worst, not a data breach.

GUI

Use the web-based GUI to view RPC requests/responses.

The web GUI uses basic authentication. Set a password in /etc/rabbitmq-consumer-log-server/gui_password (regular text file).

You can generate a random password using openssl: openssl rand -hex 32

You can use any basic authentication username - it's ignored.

Usage

Run

Manually

• Run migrations: alembic upgrade head
• Run the app using an ASGI server such as Uvicorn.

systemd

The server runs on :::4194.

systemctl start rabbitmq-consumer-log-server.service

Web GUI

Once the server is started, access the web GUI on /rpc-requests.

SSL

Use a proxy that terminates SSL. E.g. HAProxy.

⚠️ Development

Developing the RabbitMQ consumer? Access the API documentation on /redoc (Redoc) and /docs (Swagger).

Developing the log server? After installing it, and running migrations, seed your database with example data:

python3 seed_example_data.py

You can run the seeder multiple times to fill up your database with more data.