Heroku

Pegasus supports deploying to Heroku as a standard Python application or using containers.

Before getting started, first take the following steps in Heroku:

1. In the Heroku dashboard, create a new app.
2. Set up the Heroku CLI and run heroku login locally.
3. Connect your app, by running heroku git:remote -a {{ heroku_app_name }} in your project directory.

Building using Heroku’s Python support

To deploy with Heroku’s Python module, first set up Pegasus using the “heroku” deploy platform option. This will create the necessary files for the Heroku Python buildpack.

You will also need to add the nodejs buildpack to your application using the following command:

heroku buildpacks:add --index 1 heroku/nodejs

This will ensure that the front end files are built and available when the collectstatic command runs.

Building using Heroku’s Docker container support

To deploy to Heroku using Docker, you should build Pegasus with the “heroku docker” deployment option. This will create your production Dockerfile, a heroku.yml file you can use to build and deploy your container, and additional requirements/settings needed for the Heroku platform.

After building and setting up Heroku you will also need to configure Heroku to deploy with containers by running:

heroku stack:set container

Configure Django Settings

The Heroku deployment uses its own settings module (which extends the normal settings.py). To tell Heroku to use it, set the DJANGO_SETTINGS_MODULE config var to { project_slug }.settings_production. This can be done in the “settings” tab of your Heroku application (you may need to click to reveal the Config vars) or in the CLI using the following command (replacing the project_slug with your app name):

heroku config:set DJANGO_SETTINGS_MODULE={ project_slug }.settings_production

Disable DEBUG

Similar to setting the Django Settings, you should disable DEBUG mode in your Heroku config:

heroku config:set DEBUG=False

Set up Databases

To set up your Postgres database, first enable the addon in the UI or by running:

heroku addons:create heroku-postgresql

Database migrations should be handled automatically by Heroku.

If you want to use Redis as a cache or to use Celery, you will need to install the Heroku Redis addon from the UI or by running:

heroku addons:create heroku-redis

Deploying

Both builds can be deployed using Heroku’s standard git integration. After you’ve connected your project’s git repository to Heroku, just run:

git push heroku main

You can also configure Heroku to automatically build from a branch of your git repository.

After deploying, review the production checklist for a list of common next steps

Setting environment variables

To set environment variables run:

heroku config:set {variable_name}={ value }

e.g.

heroku config:set SECRET_KEY={some long randomly generated text}

Additional settings configuration

If you need additional production settings, you can put them in the settings_production.py file, or include them as config vars like this:

SECRET_KEY = env('SECRET_KEY')

It is strongly advised to put any secrets in your environment instead of directly in your settings file.

Running one-off commands

You can run once-off commands using the heroku CLI. E.g.

heroku run python manage.py bootstrap_subscriptions

Building the front end

As of Pegasus version 0.19, Heroku container builds will automatically build your front end files for you. You don’t need to do anything to set this up.

If you’re using Heroku’s Python support you can also configure Heroku to build your front-end files for you.

To set this up, all you need to do is add the heroku/nodejs buildpack to your application from the settings page.

Just make sure that this buildpack runs before the heroku/python buildpack, so that the compiled files are available when the collectstatic command runs.

Celery support

The Heroku environment supports Celery out-of-the-box.

Additionally, you may need to run the following command to initialize a Celery worker:

heroku ps:scale worker=1

This process should be the same for Python and containerized builds.