Java CI/CD Pipelines — Because Life Is Too Short for Manual WAR Deployments
Java applications have mature tooling but complex build processes. Maven and Gradle builds can be slow, dependency resolution hits remote repositories, and the JVM startup time affects container health checks. We build CI/CD pipelines that tame Java's build complexity and produce lean, fast-starting containers.
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Why Java Needs a Proper CI/CD Pipeline
Java builds are notoriously slow. A Maven build that downloads half the internet on every CI run, compiles hundreds of classes, runs thousands of JUnit tests, and produces a fat JAR or WAR file can easily take 10-15 minutes. Without caching and parallelization, your CI pipeline becomes a bottleneck.
The Java ecosystem offers multiple build tools (Maven, Gradle), testing frameworks (JUnit 4, JUnit 5, TestNG), and packaging formats (JAR, WAR, Spring Boot fat JAR, native images). Your pipeline needs to handle whichever combination your project uses, and they all have different caching and configuration requirements.
Docker images for Java apps tend to be large. A naive FROM openjdk:17 image can be over 400 MB. The JVM needs tuning for container environments — memory limits, garbage collector selection, and container-aware heap sizing all affect reliability. An unconfigured JVM in a container with a 512 MB memory limit will OOM-kill on load.
Our Java CI/CD Implementation
For Maven projects, we cache the ~/.m2/repository directory with a cache key based on pom.xml hashes. For Gradle, we cache ~/.gradle/caches and ~/.gradle/wrapper. We configure the Gradle daemon to stay alive across build steps but not between pipeline runs (avoiding stale daemon issues). Build parallelism is enabled via -T 4 for Maven or --parallel for Gradle.
Testing runs JUnit 5 with Surefire and Failsafe plugins (or Gradle's test task) in parallel. Integration tests use Testcontainers to spin up PostgreSQL, Kafka, Redis, or any Docker-based dependency directly within the test. We configure test result reporting in JUnit XML format and publish them as pipeline artifacts for dashboard integration.
Docker builds use Eclipse Temurin JRE (not JDK) as the base image with jlink to create a custom JRE containing only the modules your application uses. This can reduce image size from 400 MB to under 150 MB. We configure JVM flags for container awareness: -XX:+UseContainerSupport -XX:MaxRAMPercentage=75.0 and select the appropriate garbage collector for your workload.
What You Get
A Java CI/CD pipeline built for speed and reliability:
- Dependency caching — Maven/Gradle repositories cached, cutting build times by 40-60%
- Parallel testing — JUnit 5 with parallel execution and Testcontainers for integration tests
- Optimized Docker images — custom JRE via jlink, Temurin base, container-aware JVM flags
- Code quality — SpotBugs, Checkstyle, or SonarQube integration
- Database migrations — Flyway or Liquibase run automatically pre-deploy
- Health check deployment — Spring Boot Actuator or custom health endpoints validated post-deploy
- Artifact versioning — semantic versioning with Git-based build metadata
Why Anubiz Engineering
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