Best AWS EC2 Instance for Django

For typical Django apps — gunicorn behind nginx, serving template-rendered HTML with database queries — **t4g.large** at $0.0672/hr (~$48/mo) is the right default. Two vCPUs and 8GB of RAM comfortably runs gunicorn with 4-8 sync workers plus a Celery worker and a local Redis broker for background jobs. Burstable mechanics work in your favor because Django request handling is genuinely bursty: spike traffic spends credits, idle minutes between bursts replenish them.

Graviton (ARM64) is well-supported across the Python ecosystem in 2026. Django itself is pure Python and runs identically on any architecture; psycopg2 (or psycopg3), Pillow, lxml, NumPy, and most other common dependencies all have prebuilt ARM64 wheels on PyPI. You'll occasionally hit a niche package without arm64 binaries — keep a build dependency check in your CI for any "pip install" you don't fully control.

The "right" tier depends heavily on whether your Django app is sync or async. Sync gunicorn workers — the default and still the most common — are a great fit for burstable t-series. The moment you switch to gevent or async views with high concurrency, the math changes: each worker holds CPU longer, so you'll burn credits faster and want sustained-CPU c-series (c6i.large or c7g.large) instead.

Don't try to keep PostgreSQL on the same burstable instance once you cross ~1,000 requests/min. The database's I/O wait times accumulate against your CPU credit balance in unexpected ways, and you'll see latency spikes that are hard to debug. Move to RDS Postgres before that point — even the smallest db.t4g.micro RDS instance offloads enough work to make the application tier behave predictably.