Deploy Django, Flask, and FastAPI apps with git push. Scale with gigalixir ps:scale.
Replace the complexity of AWS EC2 and Kubernetes with a simple, standard workflow that Python developers recognize.
Deploying Python to production often forces a choice: manually configure servers (DigitalOcean/EC2) or wrestle with complex container orchestration.
Gigalixir offers a third path.We provide a fully managed runtime that respects standard Python tooling.
You define your dependencies and entry points using the files you already have in your repository, and we handle the build, network configuration, and process management.
Python web applications require a stable network and database environment to perform well.
Serverless platforms often kill "idle" applications, causing cold starts that ruin the user experience for frameworks like Django.
Gigalixir runs your application as a persistent container that stays online, keeping your internal caches warm and your database connections ready.
We provision and manage production-grade PostgreSQL databases. You connect using standard drivers like psycopg2 or asyncpg.
We handle the backups, availability, and storage, so you can focus on your data models.
Manage sensitive settings like DJANGO_SECRET_KEY, DEBUG, or API tokens using environment variables.
You set them via the CLI (gigalixir config:set), and they are injected securely into your process at runtime. This keeps secrets out of your codebase.
Unlike Heroku, which forces a restart of your dynos every 24 hours, Gigalixir processes run indefinitely until you deploy or restart them.
This stability allows you to maintain long-lived in-memory state and avoids the performance hit of daily cache clearing.
Django is a "batteries-included" framework that benefits significantly from persistent infrastructure.
We provide the direct access required to use Django's full feature set without compromises.
You don't need to disable database features or offload simple tasks to external services just to fit platform constraints.
The Questions We Get The Most at Gigalixir Support
No.
We utilize Cloud Native Buildpacks to detect your Python application.
As long as you have a valid requirements.txt or Pipfile and a Procfile, we will build the container image for you.
This abstracts away the OS-level dependencies and security patching required when maintaining your own Dockerfile.
We support all major active Python versions.
You can specify the exact version you need by creating a runtime.txt file in your root directory (e.g., containing python-3.11.4).
If you do not specify a version, we will default to a recent stable release.
You should run migrations as a one-off task after deploying. Use the command gigalixir ps:run python manage.py migrate.
This spins up a temporary instance connected to your production database to execute the schema changes safely. You can also automate this in your CI/CD pipeline.
Yes. Celery works excellently on Gigalixir.
You define a worker process in your Procfile (e.g., worker: celery -A myapp worker -l info) and scale it independently of your web process.
You will need a message broker; you can use our managed PostgreSQL (with a library like celery-sqlalchemy-scheduler) or connect to an external Redis provider.
The free tier includes 1 app instance and 1 database per account. It is fully functional and does not sleep, making it far superior to other free tiers for low-traffic sites and bots.
However, it has memory limits (typically suitable for small Flask/FastAPI apps or lean Django sites).
Heavy applications may require a paid tier for more RAM.
Reach out directly to the Engineers who built Gigalixir to discuss your specific architecture, integration challenges, or compliance constraints here 👇
Stop fighting generic cloud infrastructure.
Whether you’re working with Elixir, Python, or Node.js, get the specialized support and performance your application deserves.