Django VPS Requirements: Gunicorn/Uvicorn, RAM, Database & Production Checklist

Django VPS requirements depend on application concurrency, worker processes, database/cache memory and background jobs. Django’s built-in runserver is for development and should not be the production application server. Django’s current deployment checklist explicitly tells operators to switch to a production-ready WSGI or ASGI server and run manage.py check --deploy against production settings.

Production Django stack

A common VPS layout is:

• Nginx or another reverse proxy for HTTP/TLS/static delivery;
• Gunicorn for WSGI applications or an appropriate ASGI server such as Uvicorn/Daphne/Hypercorn where ASGI is required;
• Django application workers;
• PostgreSQL/MySQL, either local or separate;
• Redis/cache/queue services where needed;
• Celery or other background workers where the application uses them.

Every component consumes RAM and CPU. Do not size the server from Django alone.

How much RAM does Django need?

There is no official “Django needs 4 GB” rule. Memory depends on the application’s imported code, worker count, request behaviour, caching, database and background jobs.

Worker sizing

Do not copy a worker formula without testing. More Gunicorn/Uvicorn workers can improve concurrency up to the point where CPU, memory or database capacity becomes the constraint. Each process has a memory cost.

Measure:

• memory per worker;
• request concurrency;
• CPU saturation;
• response p95/p99;
• worker restarts/timeouts;
• database connections created by workers.

Database and Redis

If PostgreSQL/MySQL and Redis share the VPS, reserve memory for them explicitly. A Django application that looks light can become memory-bound after adding database cache, Redis, Celery workers and monitoring.

Keep the primary database close to the application. Cross-city database traffic adds latency to every chatty request.

Background workers change the VPS size

Celery and similar job workers consume CPU/RAM independently from web traffic. Image processing, PDF generation, imports and report jobs can create load spikes. Isolate heavy workers or apply concurrency limits when they compete with user requests.

Static files and media

Django’s deployment documentation calls out static-file handling as part of production deployment. Use an appropriate web server/object-storage/CDN design rather than expecting Django application workers to serve every static asset.

User-uploaded media is stateful data and must be included in the backup/recovery design.

Security checklist from Django

• Run python manage.py check --deploy against production settings.
• Set DEBUG = False.
• Keep SECRET_KEY secret and out of source control.
• Configure ALLOWED_HOSTS.
• Use HTTPS and secure cookie settings appropriate to the deployment.
• Review error reporting/logging.
• Keep dependencies and OS packages updated.

Backups

Back up the database and uploaded media/configuration required to reconstruct the service. A code repository alone is not enough. Store important recovery copies outside the live VPS and test restoration.

4 vCPU / 8 GB as a production discussion point

VPSWala’s 4 vCPU / 8 GB tier is a useful starting discussion for a normal production web stack with moderate traffic, but it is not a Django guarantee. A tiny API may need less; a local database plus Redis and several workers may need more.

When high-frequency VPS helps

If profiling shows one request path or Python process is CPU-bound, a higher-frequency CPU can reduce execution time. It will not fix slow SQL, external APIs or insufficient memory.

Django migration checklist

1. Record current worker count and memory per process.
2. Measure database/cache footprint.
3. Provision production WSGI/ASGI server.
4. Configure reverse proxy and HTTPS.
5. Set production secrets/settings.
6. Configure static/media handling.
7. Deploy monitoring/logging.
8. Create off-server backups.
9. Run check --deploy.
10. Load-test before final DNS cutover.

Bottom line

Size Django VPS hosting around processes and services: web workers, database, cache, queues and background jobs. Use production-ready WSGI/ASGI deployment, follow Django’s deployment checklist and scale from real CPU/RAM/latency measurements.

Next step: compare VPSWala VPS plans and provide worker count, database size and expected concurrency for sizing.

Sources

• Django deployment checklist
• Django deployment methods
• VPSWala KVM VPS catalogue