Schema Registry Visualiser

FastApi application to visualise Schema Registry subject references as a graph. For demo purposes an endpoint is foreseen to visualise your schema using d3 js.

Getting started

You will need the following tools to get started:

• Python 3
• Installation of requirements.txt in a virtualenv
• A running schema registry in http or https mode
• Access to HTTPS certificate if running in https mode
• docker and docker-compose if you want to build the docker solution

Local development

You can run the program locally by starting the file main.py from python. Before doing this you will need to uncomment the last 2 lines in the main.py. The environment will by default go to local. You can override the environment by setting the environment variable SR_VIZ_ENV. If you need additional environments, add configuration files in the package schema_reg_viz.config

Local development: Endpoint call

If the application is running you can do a curl request as follows:

curl -d'{"subjectname": "google%2fprotobuf%2fdescriptor.proto"}' -X POST http://localhost:8888/viz_topic

This will return a JSON object containing the graph in a JSON structure, this can later be used to visualise the data in a tool like D3.JS.

However, an endpoint has been foreseen to visualise your structure within this app. You will need to call the same endpoint, but you will need to supply the parameter persist. An example call would be:

curl -d'{"subjectname": "google%2fprotobuf%2fdescriptor.proto","persist":true}' -X POST http://localhost:8888/viz_topic

Part of the returning result will be a UUID eg: "uuid":"00a7b2fb-c421-4bf2-8f49-97fa47b7957a"

Local development: Visualising

With the UUID generated in the previous step you can call the following endpoint from your browser

http://localhost/show/00a7b2fb-c421-4bf2-8f49-97fa47b7957a

This will load the persisted JSON and visualise it in your browser.

Docker environment

A docker solution has also been foreseen. First you will need to build the base image which can be done with the following command in the root of the project

docker build -t schema_registry_visualizer -f Docker/Dockerfile .

Once the base image is created you can run docker-compose to have a playground. Within this playground the following services will be active:

• zookeeper
• kafka broker
• schema registry
• our schema registry visualiser app

Note: If you build the docker image with a different name, you need to change the docker-compose accordingly.

Unit test

Pytests have been foreseen in the root directory tests and will be executed during pipeline execution.

Contributing

If you want to contribute, please abide by the following rules:

• Create a feature branch and add your changes
• Create a pull request to merge into master
• Have a reviewer and merge