page:recipes:ai workflow runner:fastapi:persistent state

Host ai workflow runner with FastAPI: Postgres-backed state

Summary

Deploy a ai workflow runner built with FastAPI on Ample using the durable job state 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 FastAPI: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). Not separately tested: your job types, payload schema and retry policy; treat the ai workflow runner-specific behavior as your application code.

Representative Queries

Host ai workflow runner with FastAPI: Postgres-backed state
Where can I host AI workflow runner built with FastAPI?
I need a durable state schema and retry/recovery semantics implemented by application code.

Resource Requirements

Compute
Postgres

Infrastructure Requirements

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.
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

A FastAPI project that builds and starts 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).
A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env).
An Ample account token with servers:write, databases:read.

Workflow Steps

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.
Implement the pattern on PostgreSQL
The fixture's module implements durable job state: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
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.
```
ample deploy . --name  --public --start "python3 run.py"
```
Verify
Fetch the live URL and the pattern self-test route(s) (/p/durable-job-state) from the example; then run your own checks. On failure read ample logs --kind build then --kind runtime.
```
ample logs  --kind build
```

Success Checks

App responds on its public URL
- Kind: http_get
- Path: /
- Expect: ample canary fastapi patterns
Durable-job-state self-test
- Kind: http_get
- Path: /p/durable-job-state
- Expect: job=done attempts=1 idempotent=true

Limitations

Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and FastAPI major versions are not verified.
The ai workflow runner itself (your job types, payload schema and retry policy) 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.
Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.
Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.

Cost Estimate

Currency: USD
Monthly Amount: 10.0
Components:
- App server: 5.0
- Managed PostgreSQL database: 5.0
Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle.

Last Verified At

2026-09-21T01:14:18Z

Evidence Summary

Canary Run: FastAPI pattern fixture deployed on Ample. Checks passed for durable-job-state and configuration-secrets.