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1. Prepare the application for production
Django
Keep production settings separate from development settings. Set DEBUG to false, load SECRET_KEY from a confidential value outside source control, and configure ALLOWED_HOSTS for the actual hostnames. Review HTTPS and other security settings for your deployment. Run manage.py check --deploy with the production settings before release. Django states that its runserver command is a lightweight development server, not suitable for production; choose a production WSGI or ASGI server appropriate to your application. See the Django deployment guide and deployment checklist.
FastAPI
Use a production invocation such as the official guide’s fastapi run command rather than a development server. If a reverse proxy terminates TLS, configure proxy-header handling so the app can interpret the original request scheme, and trust those headers only from the intended proxy path. The exact proxy and network configuration depends on your hosting setup. See FastAPI’s Docker deployment guide.
2. Build a Docker image
A typical Python image uses a base image, a working directory, dependency installation, application files, and an exec-form startup command. Copy dependency declarations and install packages before copying frequently changed source code: Docker can then reuse the dependency layer when application code changes but dependencies do not.
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FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["fastapi", "run", "app/main.py", "--port", "80"]This is a shape to adapt, not a universal production recipe: select a Python version and base image supported by your project and image policy, and adjust paths and dependencies to match your app. FastAPI’s documented example uses the official Python image and exec-form CMD; exec form helps the application receive container signals for shutdown. Confirm the command and image tags against the versions you deploy.
For Django, Docker’s current guide demonstrates a multi-stage build: a builder stage prepares dependencies, while a smaller runtime stage contains what the production app needs. Add a .dockerignore file so local virtual environments, bytecode caches, and Git data do not enter the build context. The guide’s specific versions and package-manager choices are examples, not requirements. See Docker’s Django guide.
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3. Configure how the container runs
Docker Compose can run the web app alongside supporting services on a developer machine or a single server. Keep a base Compose definition and layer in production-specific changes rather than carrying development settings directly into production. Docker’s documented pattern includes removing source-code bind mounts, setting production environment values and host ports, defining restart behavior, and optionally adding services such as logging. See Docker Compose in production.
For a code release, rebuild and recreate the affected service. Docker gives this example for a service named web:
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docker compose build web
docker compose up --no-deps -d webChoose the runtime according to the operational work you want to own:
| Deployment approach | What it suits | Operational trade-off |
|---|---|---|
| Compose on one server | A straightforward, single-host deployment with a small set of services. | You manage the host, updates, TLS path, monitoring, persistence, and recovery. |
| Managed container service | Teams that want a platform to run container images without managing every host detail directly. | Available controls and responsibilities vary by service; configure its networking, storage, and operational features for the application. |
| Orchestrator such as Kubernetes, Swarm, or Nomad | Deployments where orchestration-level scheduling and replication are appropriate. | More infrastructure and configuration to operate; the guides do not rank these choices or prescribe a universal provider. |
FastAPI’s guide identifies Kubernetes, Swarm, Nomad, and cloud services that run container images as possible destinations. Replicas can be managed by an orchestrator; a sufficiently simple single-server setup may instead run multiple worker processes in a container. Make that choice based on operational scale, memory, restart behavior, security, and management needs—not on an assumed universal best option.
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4. Handle databases, static files, and uploads deliberately
Configure the database and other dependencies as separate runtime services or use appropriate external managed services. Keep database data in persistent storage and establish backups; a container’s replaceable filesystem is not a backup strategy. Docker’s Django guide includes PostgreSQL in a development Compose example, while production Compose guidance shows how to layer services and configuration for production.
For Django, run collectstatic when static assets change, then serve the resulting STATIC_ROOT output. Django documents serving assets through the same server, a dedicated static server, or cloud storage/CDN. User-uploaded media is different from static assets: provide its own storage, backup, and safe-serving plan. See the Django static-file deployment guide.
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5. Verify the deployment before and after release
- For Django, run
manage.py check --deployusing the production settings and resolve applicable warnings. - Confirm secrets are provided at runtime and are not committed in the image or source repository.
- Check that allowed hostnames, HTTPS behavior, and any trusted proxy configuration match the actual network path.
- Verify the production server starts, receives traffic, and shuts down cleanly when the container is stopped or replaced.
- Confirm static assets, uploaded media, database persistence, and backups work independently of container replacement.
- Set up operational error reporting and logging so failures can be investigated after deployment.
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