### Host company website with Flask: Postgres-backed content

Deploy a company website built with Flask 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 Flask: 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 company website-specific behavior as your application code.

### Prerequisites
- A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.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

### Resource Requirements
- `primitive:compute`
- `primitive:postgres`
- `primitive:cdn`

### Workflow Steps
1. **Build and start**  
   pip install into .ample/python from requirements.txt, then waitress from app.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 Keep private data in an unpublished bucket.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.  
   Command: `ample deploy . --name  --public --start "python3 app.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=... --env CDN_PUBLIC_URL=...`

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  --kind build` then `--kind runtime`.  
   Command: `ample logs  --kind build`

### Success Checks
- app responds on its public URL
- relational-records self-test

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Flask major versions are not verified.
- The company website itself (your record schema, states and access rules) is application code and was not separately tested; the pattern checks are what was verified.
- Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.

### Cost Estimate
Monthly Amount: $10.00 USD
- App server: $5.00
- Managed PostgreSQL database: $5.00

### 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 app.py`

### Examples
- **Flask pattern fixture**  
  Multi-pattern Flask app whose relational records module was checked live; the module is under tests/deploy-canaries/_pattern-modules.
  Source: `tests/deploy-canaries/flask-patterns`