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Aptible

Prerequisites​

The options and health check routes described in this document are available from Flagsmith 2.130.0.

Configuration​

Running Flagsmith on Aptible requires some configuration tweaks because of how Aptible's application lifecycle works:

  • Don't wait for the database to be available before the Flagsmith API starts. You can do this by setting the SKIP_WAIT_FOR_DB environment variable.
  • Add containers as an allowed host to comply with Aptible's strict health checks.
  • Use the before_release tasks from .aptible.yml to run database migrations
  • Use a Procfile to only start the API and not perform database migrations on startup

This configuration can be applied by adding the Procfile and .aptible.yml configuration files to a Docker image that you build starting from a Flagsmith base image:

Procfile
cmd: serve
.aptible.yml
before_release:
 - migrate
 - bootstrap
Dockerfile
# Use flagsmith/flagsmith-private-cloud for the Enterprise image
FROM --platform=linux/amd64 flagsmith/flagsmith

# Don't wait for the database to be available during startup for health checks to succeed
ENV SKIP_WAIT_FOR_DB=1

# Use root user to add Aptible files to the container
USER root
RUN mkdir /.aptible/
ADD Procfile /.aptible/Procfile
ADD .aptible.yml /.aptible/.aptible.yml

# Use non-root user at runtime
USER nobody

Before deploying, set the environment variables for your database URL and allowed hosts from the Aptible dashboard, or using the Aptible CLI:

aptible config:set --app flagsmith \
    DATABASE_URL=postgresql://aptible:...@...:23532/db \
    DJANGO_ALLOWED_HOSTS='containers,YOUR_APTIBLE_HOSTNAME'

Deployment​

After your image is built and pushed to a container registry that Aptible can access, you can deploy it using the Aptible CLI as you would any other application:

aptible deploy --app flagsmith --docker-image example/my-flagsmith-aptible-image

Once Flagsmith is running in Aptible, make sure to create the first admin user by visiting /api/v1/users/config/init/.

Limitations​

The steps described in this document do not deploy the asynchronous task processor, which may affect performance in production workloads.