Deployment¶

Deployment support is a new feature in Pegasus under active development (as of November 2020)! Watch this page for more updates and platforms, coming soon.

Pegasus can be deployed on any standard cloud infrastructure. The most common ways of deploying Pegasus are:

On a raw VPS / Virtual Machine, such Digital Ocean, Linode, or Amazon Lightsail
On a platform-as-a-service (PaaS) platform, such as Heroku, or PythonAnywhere
In a containerized way, using Docker, Kubernetes, or Google Cloud Platform

Pegasus natively supports Heroku, Digital Ocean App Platform, and Google Cloud Run—though can be deployed on any infrastructure that supports Django apps. The following instructions are for specific supported platforms.

If you would like to deploy to a platform that’s not listed here, please get in touch by emailing cory@saaspegasus.com and I’m happy to help!

Deploying to containers with Docker¶

As of version 0.10.2, Pegasus ships with Docker support for development. The Docker containers used for development can be modified to deploy to production environments that support containers - for example, Google Cloud Run/Kubernetes Engine, Amazon ECS, Heroku Container Registry, and Digital Ocean App Platform.

Each environment has its own quirks in getting set up with containers - some of which are documented below.

Heroku Containers¶

Pegasus supports deploying to Heroku with Docker out of the box. For more details see the Heroku documentation.

Google Cloud Run¶

Pegasus supports deploying to Google Cloud Run. See the Google Cloud documentation for details. Note that Celery is not yet supported on Google Cloud Run.

Heroku¶

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

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 your Heroku Procfile, runtime.txt, and additional requirements/settings files needed for the Heroku platform.

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_heroku. 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_heroku

Set up Database¶

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

heroku addons:create heroku-postgresql

Then run your initial migrations using:

heroku run python manage.py migrate

Note: if you’re using Heroku’s Python module, migrations will run automatically.

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 master

Additional settings configuration¶

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

SECRET_KEY = os.environ.get('SECRET_KEY')

We recommend also setting SECRET_KEY in your Heroku config vars to avoid having it in version control.

Stripe support¶

If you’re using Stripe, you will need to set the STRIPE_TEST_PUBLIC_KEY, STRIPE_TEST_SECRET_KEY, STRIPE_LIVE_PUBLIC_KEY, and STRIPE_LIVE_SECRET_KEY config vars (or whatever subset you are using).

After setting up your Stripe variables, you can run:

heroku run python manage.py bootstrap_subscriptions

to initialize your subscription data.

Celery support¶

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

However, you will need to install the Heroku Redis addon from the UI or by running:

heroku addons:create heroku-redis

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.

Digital Ocean¶

Pegasus provides native support for Digital Ocean App Platform. To build for Digital Ocean, choose the “digital_ocean_app_platform” option when installing Pegasus. Then follow the steps below to deploy your app.

Prerequisites¶

If you haven’t already, create your Digital Ocean account. You can sign up with this link to get $100 credit and help support Pegasus.

Next, install and configure the doctl command line tool by following these instructions.

Additionally, you must connect Digital Ocean to your project’s Github repository. This can be done from inside App Platform, or by following this link.

Deploying¶

Once you’ve configured the prerequisites, deploying is just a few steps.

Edit the /deploy/app-spec.yaml file. In particular, make sure to set your Github repository and branch.
Run doctl apps create --spec deploy/app-spec.yaml

That’s it! In a few minutes your app should be online. You can find and view it here.

Running Database Migrations¶

You’ll need to run database migrations to get your app working properly. The easiest way to do this is to click the “console” tab in app platform and just type in the command:

./manage.py migrate

See the screenshot below for what it looks like:

Console Migrations

Settings and Secrets¶

App platform builds use the settings_do.py file. You can add settings here, and use environment variables to manage any secrets, following the SECRET_KEY example.

Google Cloud¶

Pegasus can be deployed to Google Cloud Run using containers. This feature is in beta and Celery is not yet supported.

To build for Google Cloud, choose the “google_cloud” option when installing Pegasus. Then follow the steps below to deploy your app.

Prerequisites¶

It is recommended to complete steps 1, 2, 3, and 5 of the Django on Cloud Run guide (Pegasus handles step 4 for you). Pegasus generates a script that you can use as a starting point at ./scripts/google/cloud_run.sh, however it is recommended you follow the steps in order to troubleshoot.

In particular you must:

Set up your gcloud environment, services, and billing
Set the the PROJECT_ID and REGION environment variables

Additionally, when completing step 5 be sure to save your SQL user credentials in a file named .env.production (you can start with a template provided in .env.production.example).

Building images for Google Cloud¶

After settings up Pegasus and configuring your Google cloud environment, database, and secrets, you can build your container for Google Cloud by running the following command:

gcloud builds submit --config cloudmigrate.yaml  --substitutions _REGION=$REGION

This will create your image, upload it to Google’s container registry, run your database migrations, and collect your static files.

You can then deploy it to Google Cloud Run by running the following command, replacing the variables as needed:

gcloud run deploy my-project --platform managed --region $REGION --image gcr.io/$PROJECT_ID/{project_slug}-cloudrun --add-cloudsql-instances ${PROJECT_ID}:${REGION}:your_instance  --allow-unauthenticated --set-env-vars=DJANGO_SETTINGS_MODULE={project_slug}.settings_google

Pegasus will also generate this command for you as the last line of ./scripts/google/cloud_run.sh.

Settings and Secrets¶

To tell Google Cloud to use your production settings you will need to set the DJANGO_SETTINGS_MODULE=[project_slug].settings_google. If you use Pegasus’s cloudmigrate.yaml file this will be handled automatically for you

You can use Google Secret Manager to add additional settings and secrets by adding them to .env.production and uploading it to Secret Manager using:

gcloud secrets versions add {project_slug}_settings --data-file .env.production

See settings_google.py for examples of using these secrets in your settings file.