# Host graphql api with FastAPI: worker execution and job state

## Summary

Deploy a graphql api built with FastAPI 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 FastAPI: 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 graphql api-specific behavior as your application code.

## Infrastructure requirements

- [Compute](/discover/primitive/compute): verified (Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.)
- [Postgres](/discover/primitive/postgres): verified (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

- 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 uvicorn from run.py reading PORT on the python-3.12 template; the worker starts with python3 worker.py and binds no port)
- 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
- An Ample account token with servers:write and databases:write (ample up creates the database)

## Exact 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 run.py`

## Steps

1. **Plan the topology.** Run the planner once. It discovers the web and worker services, infers kind = "worker" for the process without a port, declares the database each service needs, and writes ample.toml. Exit 2 means it left questions in the manifest; answer them with --answer or by editing the file.

```
   ample plan --write .
   ```
2. **Share one database.** Keep a single [databases.main] with engine = "postgres", drop any per-service database the planner added, and set DATABASE_URL = { database = "main" } under both [services.web.env] and [services.worker.env]. Python services also need an explicit start command in the manifest (the fixture sets start for both services).

```
   ample plan --offline .
   ```
3. **Apply.** Reconcile the whole manifest in dependency order: the database first, then both services. It is idempotent and never destructive; exit 0 means everything applied, 2 needs input, 1 a failed resource (independent siblings still proceed and re-running resumes).

```
   ample up .
   ```
4. **Verify.** Fetch the web service URL and its worker status route (/p/worker-queue/status in the example) and confirm the worker processed the enqueued job; on failure read the worker service's runtime logs.

```
   ample logs <deployment_id> --kind runtime
   ```

## Tested examples

- **FastAPI web + worker fixture** (tests/deploy-canaries/fastapi-worker): A FastAPI 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.

## Success checks

- web service responds on its public URL (`/` on the live URL, expect ample canary fastapi patterns)
- worker consumed the enqueued job (`/p/worker-queue/status` on the live URL, expect worker=done attempts=1 result=processed-by-worker)

## Limitations

- Verified on the python-3.12 template at s-1vcpu-1gb for both services with the example fixture; other sizes, templates and FastAPI major versions are not verified.
- The graphql api itself (your job payloads, retry policy and scheduling) is application code and was not separately tested; the worker-queue check is what was verified.
- The worker is a single long-running process supervised in its own microVM; there is no scheduler, cron or horizontal worker scaling in this recipe, and the check ran immediately after deploy so idle behavior of the worker VM is not verified.
- The worker service is private: it has no public URL and is reached only through the shared database; both services are placed with their database.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.
- Region, compliance attestations and request-duration limits are unknown and not claimed.

## Cost estimate

Estimated 15.00 USD per month (size prices from pricing.toml at build revision a1b8c38919e59cd035ebabaced73cf84ece24371).
- web server x1 `s-1vcpu-1gb`: 5.00 USD
- worker server x1 `s-1vcpu-1gb`: 5.00 USD
- managed PostgreSQL database x1 `s-1vcpu-1gb`: 5.00 USD

Always-on monthly price of the tested sizes for the web service, the worker service and the database; apps auto-pause when idle.

## Verification evidence

- canary_run on 2026-09-20T03:56:46Z at revision `03b6402b1b3e19178985f08ea4033804521d85d4-dirty (CLI b75e104)`: FastAPI web service plus a separate Python worker process deployed on Ample with `ample plan --write` then `ample up` (pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template); the web service enqueued a job that the private worker service consumed from the shared managed PostgreSQL database. Pattern proof: 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). (expires 2027-03-19T03:56:46Z)

Last verified: 2026-09-20T03:56:46Z

## Execution binding

MCP tool `ample_up` (registry `mcp:ample_up`), schema hash `db7ca0facfe2cd28` observed 2026-09-21T03:19:59.525781+00:00 at revision `49962bcade4f`, binding state `current`, required scopes: servers:write, databases:write.