183 backend tests
Latest local backend validation: 183 tests, 0 failures, 0 errors and 0 skipped — BUILD SUCCESS.
RiLyMed
My contribution
Where I focused.
- Implemented and integrated Spring Boot backend features around candidate/recruiter workflows, notifications and reference data.
- Strengthened reliability with authorization checks, PostgreSQL integration tests, Flyway migration validation and regression coverage.
- Contributed to Docker environments, CI/CD validation, observability and release/deployment documentation across the monorepo.
01 / The problem
RiLyMed had to support three distinct user journeys while keeping authorization, data consistency, asynchronous workflows and delivery concerns explicit instead of hiding them inside one tightly coupled feature layer.
02 / My response
I worked on the Java 21 / Spring Boot backend and DevOps foundations: domain APIs, reference data, notifications, authorization tests, Flyway migrations, Dockerized dependencies, CI validation and runtime health checks. I approached the system from candidate, recruiter and admin journeys first, then translated those needs into clear service, data and integration boundaries.
What changed
01
183 backend tests passing · 0 failures / 0 errors
02
Healthy Docker runtime with PostgreSQL, Redis, RabbitMQ, MinIO, AI and backend services
03
Observable delivery path with health checks, Prometheus/Grafana and CI/CD controls
A quick product walkthrough
Evidence & verification
Runtime verified
The Dockerized backend reported healthy and /actuator/health returned status UP with liveness and readiness groups.
AI scoring evaluation
The Sprint 3 golden-set report passed all 11 cases; scoring p95 was 2.26 ms against a <= 500 ms evaluation gate. This metric applies to the evaluation set, not production API latency.
11-service local environment
The Compose environment defines PostgreSQL, Redis, RabbitMQ, MinIO, Mailpit, AI, Backend, Prometheus, Grafana, Web and Admin services.
Development and evaluation evidence from local runtime checks and repository records; these figures are not production traffic or production-scale performance measurements.
Original RiLyMed DevOps visual: CI/CD quality and security gates, container delivery and the target GitOps deployment flow.
Proof of work: 183 passing backend tests, Dockerized core services and a healthy Spring Boot runtime.
Engineering decisions
The choices behind the interface.
Design from user journeys
Candidate, recruiter and administrator workflows were treated as distinct journeys first; API boundaries and authorization rules followed those responsibilities.
Choose the right data path
PostgreSQL owns transactional recruitment data, Redis handles cache/session concerns, RabbitMQ decouples asynchronous work, and MinIO keeps files outside the relational schema.
Keep AI isolated
FastAPI isolates matching/scoring work from the Java backend so the AI service can evolve independently while Spring Boot remains the source of truth for authorization and domain state.
Verify, do not assume
SOLID boundaries, JUnit/PostgreSQL checks, Flyway validation, Docker health checks and CI/CD gates turn architecture decisions into repeatable evidence.
Stack & capabilities
Java 21Spring BootPostgreSQLRedisRabbitMQMinIOFastAPIFlywayJUnitDockerGitHub ActionsPrometheusGrafana
Team repository is private. The case study focuses on my backend, testing and DevOps contribution; contact me for a walkthrough. Get in touch ↗