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

Host ai workflow runner with Hono: Postgres-backed state

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

Prerequisites

• A Hono project that builds and starts with the documented commands (npm install and npm run start with @hono/node-server on the node-22 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

1. Build and start
   npm install and npm run start with @hono/node-server on the node-22 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.

   ample deploy . --name  --public
   

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.

   ample logs  --kind build
   

Limitations

• Verified on the node-22 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Hono 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
• 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, monthlyAmount: 5.0
  • managed PostgreSQL database: size s-1vcpu-1gb, quantity: 1.0, monthlyAmount: 5.0

Success Checks

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