## Host recruiting tracker with Flask: relational workspace data

### Summary
Deploy a recruiting tracker 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. 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 recruiting tracker-specific behavior as your application code.

### Representative Queries
- Host recruiting tracker with Flask: relational workspace data
- Where can I host Recruiting tracker built with Flask?
- I need a workspace-specific schema, state transitions and access rules.

### Resource Requirements
- **Compute**
- **Postgres**

### Infrastructure Requirements
1. **Compute**
   - Status: verified
   - Summary: 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**
   - Status: verified
   - Summary: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.

### Prerequisites
1. 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).
2. A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env).
3. An Ample account token with servers:write, databases:read.

### 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. **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"`

4. **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`

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

### Success Checks
1. App responds on its public URL.
2. Relational-records self-test.

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb; other sizes, templates and Flask major versions are not verified.
- The recruiting tracker itself (your record schema, states and access rules) is application code and was not separately tested.

### Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 10.0
- **Components**:
  - app server (s-1vcpu-1gb): $5.00/month
  - managed PostgreSQL database (s-1vcpu-1gb): $5.00/month

### Evidence Summary
- **Canary run**: Flask pattern fixture deployed on Ample; checks passed for relational-records and configuration-secrets.

### Unknowns
- Region availability is unknown until a verified region fact is recorded.
- Compliance attestations are unknown; none are claimed.