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# Description **Prowler** is an Open Source security tool to perform AWS, Azure, Google Cloud and Kubernetes security best practices assessments, audits, incident response, continuous monitoring, hardening and forensics readiness, and also remediations! We have Prowler CLI (Command Line Interface) that we call Prowler Open Source and a service on top of it that we call Prowler SaaS. This repository contains the JSON API and Task Runner components for Prowler, which facilitate a complete backend that interacts with the Prowler SDK and is used by the Prowler UI. # Production deployment ## Install all dependencies with Poetry ```console poetry install poetry shell ``` ## Modify environment variables Under the root path of the project, you can find a file called `.env.example`. This file shows all the environment variables that the project uses. You can *must* create a new file called `.env` and set the values for the variables. Keep in mind if you export the `.env` file to use it with local deployment that you will have to do it within the context of the Poetry interpreter, not before. Otherwise, variables will not be loaded properly. ## Run migrations For migrations, you need to force the `admin` database router. Assuming you have the correct environment variables and Python virtual environment, run: ```console python manage.py migrate --database admin ``` ## Run the Celery worker ```console cd src/backend python -m celery -A config.celery worker -l info -E ``` ## Run the Django server with Gunicorn ```console cd src/backend gunicorn -c backend/guniconf.py backend.wsgi:application ``` > By default, the Gunicorn server will try to use as many workers as your machine can handle. You can manually change that in the `src/backend/backend/guniconf.py` file. # 💻 Development guide The Prowler API is composed of the following components: - The JSON API, which is the main component of the API. - The Celery worker, which is responsible for executing the background tasks that are defined in the JSON API. - The PostgreSQL database, which is used to store the data. - The Valkey database, which is used to manage the background tasks. ## Note about Valkey [Valkey](https://valkey.io/) is an open source (BSD) high performance key/value datastore. Valkey exposes a Redis 7.2 compliant API. Any service that exposes the Redis API can be used with Prowler API. ## Local deployment This method requires installing a Python virtual environment and keep dependencies updated. ### Clone the repository ```console # HTTPS git clone https://github.com/prowler-cloud/api.git # SSH git clone git@github.com:prowler-cloud/api.git ``` ### Start the PostgreSQL database and Valkey The PostgreSQL database and Valkey are required for the development environment. To make development easier, we have provided a docker-compose file that will start them for you. ```console docker compose up postgres valkey -d ``` ### Install the Python dependencies > You must have Poetry installed ```console poetry install poetry shell ``` ### Apply migrations For migrations, you need to force the `admin` database router. Assuming you have the correct environment variables and Python virtual environment, run: ```console python manage.py migrate --database admin ``` ### Run the Django development server ```console cd backend python manage.py migrate --database admin python manage.py runserver ``` You can access the server in `http://localhost:8000`. All changes in the code will be automatically reloaded in the server. ### Run the Celery worker ```console python -m celery -A config.celery worker -l info -E ``` The Celery worker does not detect and reload changes in the code, so you need to restart it manually when you make changes. ## Docker deployment This method requires `docker` and `docker compose`. ### Clone the repository ```console # HTTPS git clone https://github.com/prowler-cloud/api.git # SSH git clone git@github.com:prowler-cloud/api.git ``` ### Build the base image ```console docker compose --profile dev build ``` ### Run the development service This command will start the Django development server and the Celery worker and also the Valkey and PostgreSQL databases. ```console docker compose --profile dev up -d ``` You can access the server in `http://localhost:8080`. All changes in the code will be automatically reloaded in the server. > **NOTE:** notice how the port is different. When developing using docker, the port will be `8080` to prevent conflicts. ### View the development server logs For Django ```console docker logs -f api-api-dev-1 ``` or for the Celery worker: ```console docker logs -f api-worker-dev-1 ``` ## Applying migrations For migrations, you need to force the `admin` database router. Assuming you have the correct environment variables and Python virtual environment, run: ```console poetry shell python manage.py migrate --database admin ``` ## Apply fixtures Fixtures are used to populate the database with initial development data. ```console poetry shell # For dev tenants python manage.py loaddata api/fixtures/dev_tenants.json --database admin ``` ## Run tests Note that the tests will fail if you use the same `.env` file as the development environment. For best results, run in a new shell with no environment variables set. ```console poetry shell cd src/backend pytest ```