CAUTION! The default Open Telemetry prometheus port is 8888 and Jupyter Notebook starts to
occupy ports at 8888. I could change default port values, but I was a bit confused and decided to
leave otel-config.yaml
as vanila as possible (aligned to the typical examples found in the
documentation) so you may need to restart the notebook and restart the otel-collector if you see
errors on docker compose logs.
- Start the docker compose. Keep it running.
- Start the Jupyter Notebook. Keep it running.
- Run the Jupyter Notebook
BridgeConfig
(change settings if you wish). - Start the bridge (
run_bridge.py
). Keep it running. - Play with the
Consumer
Notebook. If should adapt real time (by default the collector is configured to batch every 60 seconds, but that is configurable at the OpenTelemetry configuration level and is set as that just to experiment).
The following sections explain the different parts in more detail.
To test this utility, the otel/opentelemetry-collector
is used with the telemetry
service
activated (see docker-compose.yml
and otel-config.yaml
for more information). This is ONLY
used for having some dummy sample data so that we can validate that the bridge is receiving and
processing data.
Any proper functional testing (and, of course, a production environment) will have real data and a proper collector configured instead.
A docker-compose.yml
is provided. Run docker compose up
.
If you don't want the dummy otel-collector
container comment it.
The bridge expects to find some configuration in dataClay. This allows the system to have some flexible runtime configuration.
The notebooks include some demo configuration on how they work.
Create the virtual environment and install the requirements (pip install -r requirements.txt
).
After this, you can run the run_bridge.py
script directly, i.e.:
$ ./run_bridge.py