# Host mobile backend with Starlette: stored input and output artifacts

Deploy a mobile backend built with Starlette 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 Starlette: 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 mobile backend-specific behavior as your application code.

## Representative Queries
- Host mobile backend with Starlette: stored input and output artifacts
- Where can I host Mobile backend built with Starlette?
- I need an input/output artifact contract, object metadata and access boundaries.

## Infrastructure Requirements
- **Compute**: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
- **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.
- **S3-compatible object storage**: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

## Workflow Steps
1. **Build and start**: pip install into .ample/python from requirements.txt, then uvicorn 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 and returned only to an authorized caller (401 without token, export=ok rows=3). 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 Keep private data in an unpublished bucket.
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. Command: ample deploy . --name --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...
5. **Verify**: Fetch the live URL and the pattern self-test route(s) (/p/generated-downloads) from the example; then run your own checks. On failure read `ample logs --kind build` then `--kind runtime`. Command: ample logs --kind build

## Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Starlette major versions are not verified.
- The mobile backend itself (your export formats, retention policy and entitlement model) 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.

## Examples
### Starlette pattern fixture
- **Description**: Multi-pattern Starlette app whose generated downloads module was checked live; the module is under tests/deploy-canaries/_pattern-modules.
- **Source Reference**: tests/deploy-canaries/starlette-patterns

## Success Checks
- Application responds on its public URL: expected response is "ample canary starlette patterns".
- Generated-downloads self-test: expected response is "export=ok rows=3 (with ?token=...; 401 without)".