Development
If you plan to work on CueObserve code and make changes, this documentation will give you a high level overview of the components used and how to modify them.
Overview
CueObserve has multi-service architecture, with services as mentioned:
Frontend
single-page application written on ReactJS. It's code can be found inui
folder and runs on http://localhost:3000/.API
is based on Django (python framework) & uses REST API. It is the main service, responsible for connections, authentication and anomaly.Alerts
micro-service, currently responsible for sending alerting/notifications only to slack. It's code is inalerts-api
folder and runs on localhost:8100.Celery to execute the tasks asynchronously. Tasks like anomaly detection are handled by Celery.
Celery beat scheduler to trigger the scheduled tasks.
Redis to handle the task queue of Celery.
Getting code & starting development servers
Get the code by cloning our open source github repo
docker-compose
's build command will pull several components and install them on local, so this will take a few minutes to complete.
Backend Development
The code for the backend is in /api
directory. As mentioned in the overview it is based on Django framework.
Configure environment variables
Configure environment variables as you need for the backend server :
Change the values based on your running PostgreSQL instance. If you do not wish to use PostgreSQL as your database for development, comment lines 4-8 and CueObserve will create a SQLite database file at the location api/db/db.sqlite3
.
The backend server can be accessed on http://localhost:8000/.
Celery Development
CueObserve uses Celery for executing asynchronous tasks like anomaly detection. There are three components needed to run an asynchronous task, i.e. Redis, Celery and Celery Beat. Redis is used as the message queue by Celery, so before starting Celery services, Redis server should be running. Celery Beat is used as the scheduler and is responsible to trigger the scheduled tasks. Celery workers are used to execute the tasks.
Testing
At the moment, we have test cases only for the backend service, test cases for UI are in our roadmap.
Backend for API and services is tested using PyTest. To run test cases exec
into cueo-backend and run command
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