# Host ai workflow runner with Spring Boot: streamed responses

## Summary

Deploy an AI workflow runner built with Spring Boot on Ample using the streaming response service pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, with a managed PostgreSQL 16 database auto-provisioned and injected as DATABASE_URL. Verified on Spring Boot: a Server-Sent Events endpoint read incrementally through the public HTTPS gateway, with five one-second chunks arrived spread over time. This confirmed a 70-second stream of 36 chunks, which surpassed common 60-second idle timeouts and observed a client disconnect after two chunks (disconnected=true).

## Infrastructure requirements

- **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:** 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 Spring Boot project that builds and starts with documented commands (./mvnw -q -DskipTests package or the Gradle wrapper).
- 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.

## Exact tested configuration

- template: `jvm-21`
- runtime: `java`
- size: `s-1vcpu-2gb`
- build: `./mvnw -q -DskipTests package`
- start: `java -jar $(ls target/*.jar | grep -v -- '-plain' | head -n 1)`

## Steps

1. **Build and start.**  Run `./mvnw -q -DskipTests package` (or the Gradle wrapper) to produce one application jar, then `java -jar` on the jvm-21 template (Temurin JDK 21) with server.port read from PORT. The server must bind 0.0.0.0 on PORT.
2. **Implement the pattern on PostgreSQL.** The fixture's module implements streaming response service: a Server-Sent Events endpoint read incrementally through the public HTTPS gateway, conducting a 70-second stream of 36 chunks.  Follow the approach in your schema; ensure migrations are idempotent and run them with --release-command.
3. **Deploy.** Run the synchronous deploy once to read the result:
   ```
   ample deploy . --name <app-name> --public
   ```
4. **Verify.** Fetch the live URL and self-test route(s) from the example; run own checks. On failure read `ample logs <deployment_id> --kind build` then `--kind runtime`.
   ```
   ample logs <deployment_id> --kind build
   ```

## Success checks

- App responds on its public URL (`/` on the live URL).
- Streaming-response-service self-test (`/p/streaming-response-service` on the live URL).

## Limitations

- Verified on the jvm-21 template at s-1vcpu-2gb; other sizes and configurations are not verified.
- Apps auto-pause when idle and wake on the next request; always-on is an operator setting.

## Cost estimate

Estimated 10.00 USD per month:
- app server x1 `s-1vcpu-1gb`: 5.00 USD
- managed PostgreSQL database x1 `s-1vcpu-1gb`: 5.00 USD

## Verification evidence

- Successful canary run at revision showing the Spring Boot pattern fixture deployed on Ample.

## Execution binding

MCP tool `ample_deploy`, schema hash `876465fce906da0c`, binding state `current`, required scopes: servers:write, databases:read.