### Host REST API with Flask: Worker Execution and Job State

Deploy a REST API built with Flask as a public web service plus a dedicated worker process on Ample. `ample plan --write` discovers both services and their shared database and writes ample.toml; `ample up` reconciles the topology: a managed PostgreSQL 16 database, a public web microVM and a private worker microVM (kind worker, no public URL), both reading DATABASE_URL. Verified on Flask: a separately deployed worker service (kind worker, no public URL) sharing a declared managed PostgreSQL database with the web service, consuming a jobs table with row locks and marking jobs done once (worker=done attempts=1). Not separately tested: your job payloads, retry policy and scheduling; treat the REST API-specific behavior as your application code.

#### Resource Requirements
- Primitive: Compute
- Primitive: Postgres

#### 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.

#### Framework
- Flask

#### Workload
- REST API

#### Prerequisites
1. A repository with the web app and the worker as separate service directories (the fixture uses apps/web and apps/worker), each building and starting 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; the worker starts with python3 worker.py and binds no port)
2. Both services read DATABASE_URL at runtime and share one jobs table; the worker claims rows with SELECT ... FOR UPDATE SKIP LOCKED and marks them done once
3. An Ample account token with servers:write and databases:write (ample up creates the database)

#### Testing 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

#### Workflow Steps
1. **Plan the topology**: Run the planner once. It discovers the web and worker services…
   - **Command**: ample plan --write .
2. **Share one database**: Keep a single [databases.main] with engine = "postgres"…
   - **Command**: ample plan --offline .
3. **Apply**: Reconcile the whole manifest in dependency order: the database first…
   - **Command**: ample up .
4. **Verify**: Fetch the web service URL and its worker status route…
   - **Command**: ample logs  --kind runtime

#### Success Checks
- Web service responds on its public URL
- Worker consumed the enqueued job

#### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb for both services with the example fixture…

#### Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 15.0
- **Components**:
  - Web server: Size s-1vcpu-1gb, Monthly Amount: 5.0
  - Worker server: Size s-1vcpu-1gb, Monthly Amount: 5.0
  - Managed PostgreSQL database: Size s-1vcpu-1gb, Monthly Amount: 5.0
- **Note**: Always-on monthly price of the tested sizes for the web service, the worker service and the database; apps auto-pause when idle.

#### Examples
- **Title**: Flask web + worker fixture
  - **Description**: A Flask web app (apps/web) and a worker process (apps/worker) sharing one managed PostgreSQL database; the queue module is under tests/deploy-canaries/_pattern-modules.
  - **Source Ref**: tests/deploy-canaries/flask-worker

#### Evidence Summary
- A Flask web service plus a separate Python worker process deployed on Ample with `ample plan --write` then `ample up`…

#### Last Verified At
- 2026-09-20T03:56:46Z