# Host public directory with Django: Postgres-backed content

## Summary

Deploy a public directory built with Django on Ample using the relational records pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, and a published bucket serves public assets from the CDN host. Verified on Django: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true). Not separately tested: your record schema, states and access rules; treat the public directory-specific behavior as your application code.

## Infrastructure requirements

- Compute: verified (Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.)
- Postgres: verified (Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.)
- CDN: verified (The CDN host serves objects from published buckets. It does not front app compute and is not a cache or key-value store.)

## Prerequisites

- A Django project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template)
- A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
- A bucket from `ample bucket create` with its credentials passed as encrypted S3_* environment variables
- An Ample account token with servers:write, databases:read, buckets:read

## Exact tested configuration

- template: `python-3.12`
- runtime: `python`
- size: `s-1vcpu-1gb`
- install: `python3 -m pip install --target .ample/python -r requirements.txt`
- start: `PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 run.py`

## Steps

1. **Build and start.** pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
2. **Implement the pattern on PostgreSQL.** The fixture's module implements relational records: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
3. **Wire object storage.** Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket. Publish only the bucket that serves public assets and reference its CDN URL.
4. **Deploy.** Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked). Re-running with no change is a no-op.
5. **Verify.** Fetch the live URL and the pattern self-test route(s) (/p/relational-records) from the example; then run your own checks. On failure read `ample logs <deployment_id> --kind build` then `--kind runtime`.

## Tested examples

- **Django pattern fixture** (tests/deploy-canaries/django-patterns): Multi-pattern Django app whose relational records module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

## Success checks

- app responds on its public URL (`/` on the live URL, expect ample canary django patterns)
- relational-records self-test (`/p/relational-records` on the live URL, expect records=ok transitions=true isolation=true)

## Limitations

- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Django major versions are not verified.
- The public directory itself (your record schema, states and access rules) is application code and was not separately tested; the pattern checks are what was verified.
- Region, compliance attestations and request-duration limits are unknown and not claimed.
- Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.
- PutObject and GetObject with path-style addressing are verified; multipart upload, listing, presigned URLs and lifecycle rules are not.
- The CDN serves published-bucket objects only; cache rules, purge and TTL control are not verified (the fixture sets Cache-Control on upload and versions keys).