Part 5 7 chapters

Appendices

Seven optional deep-dives: WebSockets.Next at scale, gotchas, agentic development notes, testing in depth, in-memory messaging versus Kafka, the three orchestration engines compared, and running on OpenShift Local.

16

Appendix: scaling WebSocket push with Kafka

Why notification-service's single-process WebSocket push would break across more than one replica, and how Kafka-backed fan-out across per-replica consumer groups fixes it.

20 minutesRead →
17

Gotchas and things to look out for

Eight pitfalls hit while building this project, each with its symptom, root cause, and the fix applied in this repository's code.

30 minutesRead →
18

Agentic development recommendations

Guidance for AI-agent-assisted development on a Quarkus/Camel codebase: where it helps, where it does not, the plan/execute/validate relay, and the MCP tooling that grounds agents in the real catalog and docs.

25 minutesRead →
19

Testing, in detail: the full pyramid and the single-entry runner

A ground-up walk through this project's test pyramid — @QuarkusTest unit tests, failsafe *IT integration tests on self-provisioned Testcontainers, the Newman functional collection, and hey/ghz load passes — tied together by scripts/run-all-tests.sh.

35 minutesRead →
20

In-memory (Vert.x) messaging vs. Kafka

Vert.x in-memory messaging and Kafka compared: the SmallRye Reactive Messaging in-memory connector used in tests and the Kafka connector used in %prod run the same @Incoming/@Outgoing code over two transports, with the limits of what the in-memory connector can stand in for.

25 minutesRead →
21

Appendix: the three orchestration engines, compared in depth

Kafka choreography, Camel orchestration, and Quarkus Flow orchestration compared over the same order-triage domain: coupling, failure handling, debuggability, where logic lives, testing, and operational cost.

40 minutesRead →
22

Appendix: running on OpenShift Local (CRC)

The seven Quarkus services, Kafka, Postgres and Apicurio on OpenShift Local, then the platform tier: Service Mesh 3 with a canary, the Custom Metrics Autoscaler, OpenTelemetry tracing, the AI services, a native build and GitOps, all built and verified inside the cluster, with a teardown that leaves it clean.

60 minutesRead →