Designed by Agile Lab, witboost is a versatile platform that addresses various sophisticated data engineering challenges. It enables businesses to discover, enhance, and productize their data, fostering the creation of automated data platforms that adhere to the highest standards of data governance. Want to know more about witboost? Check it out here or contact us!
This repository is part of our Starter Kit meant to showcase witboost's integration capabilities and provide a "batteries-included" product.
This project provides integration between Witboost and Ice Panel to automatically generate a C4 architectural diagram representing the entire ecosystem of Data Products and their internal implementation.
In a C4 representation, the Data Product is a system. Ice Panel offers a multi-layer visualization where is also possible to explore multiple domains within the same layer, this is a perfect fit for a Data Mesh representation, because systems can be grouped in domains and then it is possible to zoom in each system ( Data Product ) to discover the inner architecture.
Requirements:
- Python 3.11
- Poetry
Installing:
To set up a Python environment we use Poetry:
curl -sSL https://install.python-poetry.org | python3 -
Once Poetry is installed and in your $PATH
, you can execute the following:
poetry --version
If you see something like Poetry (version x.x.x)
, your install is ready to use!
Install the dependencies defined in specific-provisioner/pyproject.toml
:
cd specific-provisioner
poetry install
Note: All the following commands are to be run in the Poetry project directory with the virtualenv enabled.
Type check: is handled by mypy:
poetry run mypy src/
Tests: are handled by pytest:
poetry run pytest --cov=src/ tests/. --cov-report=xml
Artifacts & Docker image: the project leverages Poetry for packaging. Build package with:
poetry build
The Docker image can be built with:
docker build .
More details can be found here.
Note: the version for the project is automatically computed using information gathered from Git, using branch name and tags. Unless you are on a release branch 1.2.x
or a tag v1.2.3
it will end up being 0.0.0
. You can follow this branch/tag convention or update the version computation to match your preferred strategy.
CI/CD: the pipeline is based on GitLab CI as that's what we use internally. It's configured by the .gitlab-ci.yaml
file in the root of the repository. You can use that as a starting point for your customizations.
To run the server locally, use:
cd specific-provisioner
source $(poetry env info --path)/bin/activate # only needed if venv is not already enabled
uvicorn src.main:app --host 127.0.0.1 --port 8091
By default, the server binds to port 8091 on localhost. After it's up and running, you can make provisioning requests for this address. You can also check the API documentation served here.
In order to set the application some environmental variable must be injected:
- LandscapeId: to define the IcePanle landscape ID where all the domains and data products will be created
- IcePanel API Key: you can retrieve it from the organization setting panel of IcePanel
landscapeId = os.getenv('IcePanelLandscapeId')
apiKey = os.getenv('API_KEY')
This microservice is meant to be deployed to a Kubernetes cluster with the included Helm chart and the scripts that can be found in the helm
subdirectory. You can find more details here.
This project is available under the Apache License, Version 2.0; see LICENSE for full details.
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