Host inventory manager with Django: downloadable reports

Deploy an inventory manager built with Django on Ample using the generated downloads 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, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Django: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Not separately tested: your export formats, retention policy and entitlement model; treat the inventory manager-specific behavior as your application code.

Representative Queries

• Host inventory manager with Django: downloadable reports
• Where can I host Inventory manager built with Django?
• I need an export query, generated artifact retention and authorized download flow.

Resource Requirements

• Compute
• Postgres
• S3-compatible object storage

Infrastructure Requirements

1. Compute: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
2. Postgres: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.
3. S3-compatible object storage: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

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

Workflow 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 generated downloads: an export query rendered to a CSV artifact stored with metadata in a private bucket.
3. Wire object storage: Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing.
4. Deploy: Run the synchronous deploy once and read the result.
5. Verify: Fetch the live URL and the pattern self-test route(s) and run your own checks.

Examples

• Django pattern fixture: Multi-pattern Django app whose generated downloads module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

Success Checks

• App responds on its public URL
• Generated-downloads self-test

Limitations

• Verified on the python-3.12 template; other sizes and Django major versions are not verified.

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Components:
  • App server (size: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0)
  • Managed PostgreSQL database (size: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0)