Modern DevOps for Java Microservices

Deploying modern Java microservices requires more than code - it’s about automating workflows, securing services, and observing performance. Here’s a summary of the architecture and lessons learned building a production-grade Twitter-clone:

Technology Stack

• Spring Boot - REST APIs for user, message, and timeline services
• Kubernetes - Managed via Helm with custom values.yaml per environment
• GitLab CI/CD - Automated build/test/deploy workflows
• OpenTelemetry + Jaeger + Prometheus + Grafana - Full observability pipeline
• JWT - Stateless authentication between services

GitOps Workflow

1. A push to main branch triggers GitLab CI
2. Docker images built and published to private registry
3. Helm chart deployed to test/prod namespaces
4. Alerts and traces auto-populated in Grafana/Jaeger

Observability in Action

One of the biggest benefits was unified observability:

• Trace microservice communication using Jaeger
• Monitor latency and throughput with Prometheus
• Correlate logs with Elastic and Kibana (future enhancement)

Lessons Learned

• Helm templating avoids duplicated K8s YAML
• Cloudflare Zero Trust secures access to dashboards
• K8s readiness probes are critical for trace collection stability

Takeaway

A containerized Java app alone isn’t enough. With CI/CD, Helm, and observability, you gain operational confidence and faster debugging, which is crucial for any modern engineering team.

Interested in the Helm charts or source code walkthrough? Email me or connect on GitHub.