Host ai workflow runner with Starlette: Postgres-backed state

Summary

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

Resource Requirements

• primitive:compute
• primitive: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.

Workflow Steps

1. 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.
2. 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.
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 run.py"
4. 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.
   • Command: ample logs --kind build

Success Checks

• App responds on its public URL

  • Kind: http_get
  • Path: /
  • Expect: ample canary starlette patterns

• Durable-job-state self-test

  • Kind: http_get
  • Path: /p/durable-job-state
  • Expect: job=done attempts=1 idempotent=true

Examples

Starlette pattern fixture

• Description: Multi-pattern Starlette app whose durable job state module was checked live; the module is under tests/deploy-canaries/_pattern-modules.
• Source Ref: tests/deploy-canaries/starlette-patterns

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Basis: Size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty

Components

• App server
  • Size: s-1vcpu-1gb
  • Quantity: 1.0
  • Monthly Amount: 5.0
• Managed PostgreSQL database
  • Size: s-1vcpu-1gb
  • Quantity: 1.0
  • Monthly Amount: 5.0
• Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.