A tailored course, built for your situation
Mastering CI/CD Pipeline Automation for Full-Stack Java Developers
Turn deployment cycles from multi-day sprints into automated, one-click releases
Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.
The situation this course is for
Java-based enterprise systems often suffer from slow, manual deployment cycles. Despite clean code, developers waste hours on environment mismatches, configuration drift, and last-minute hotfixes. This course eliminates those bottlenecks with repeatable, versioned CI/CD pipelines tailored to Spring Boot, Maven, and cloud-native JVM deployments.
Who this is for
Full-Stack Java Developers in consulting or services firms delivering to enterprise clients, managing Spring-based applications across dev, staging, and production environments.
Who this is not for
Developers working exclusively on legacy monoliths with no CI investment, or those not involved in deployment decisions.
What you walk away with
- Design and deploy a fully automated CI/CD pipeline for Java applications using GitLab CI or Jenkins
- Eliminate environment drift with containerized build and deployment stages
- Reduce deployment time from 3+ days to under 4 hours
- Standardize release validation with automated testing and rollback triggers
- Own the deployment lifecycle end-to-end, reducing dependency on ops teams
The 12 modules (with all 144 chapters)
- Understanding the role of CI/CD in modern Java development
- Mapping your current deployment workflow step by step
- Identifying bottlenecks in build, test, and deployment phases
- Choosing between Jenkins, GitLab CI, and GitHub Actions
- Setting up a version-controlled pipeline configuration
- Managing secrets and credentials securely in pipelines
- Integrating with Maven and Gradle build tools
- Standardizing Java versions and JDKs across environments
- Containerizing builds using Docker for reproducibility
- Tagging and versioning Java artifacts automatically
- Monitoring pipeline execution and failure patterns
- Documenting pipeline design for team onboarding
- Automating Maven builds with CI pipeline scripts
- Caching dependencies to reduce build times
- Parallelizing test execution in build stages
- Validating code quality with SonarQube integration
- Enforcing static analysis rules pre-merge
- Generating build reports for audit and traceability
- Handling multi-module Maven project builds
- Optimizing Gradle builds for faster execution
- Using build scans to diagnose performance issues
- Signing JARs automatically in the pipeline
- Publishing artifacts to Nexus or Artifactory
- Rolling back broken builds with versioned archives
- Running JUnit 5 tests in CI with coverage reporting
- Executing integration tests with Testcontainers
- Automating Selenium tests for full-stack validation
- Mocking external services with WireMock in pipelines
- Validating API contracts with Pact or Spring Cloud Contract
- Running performance tests with JMeter in CI
- Failing builds on test coverage thresholds
- Parallelizing test suites across containers
- Isolating test environments per pipeline run
- Generating test result dashboards automatically
- Retrying flaky tests without false positives
- Archiving test logs for compliance and debugging
- Writing efficient Dockerfiles for Spring Boot apps
- Minimizing image size with multi-stage builds
- Using OpenJDK vs. GraalVM in container images
- Configuring JVM memory settings in containers
- Exposing health checks and metrics endpoints
- Building images with distroless base images
- Signing and scanning images for vulnerabilities
- Pushing images to private registries securely
- Versioning containers with semantic tags
- Running containers in headless CI environments
- Debugging container startup issues in pipelines
- Optimizing container startup time for fast deploys
- Deploying Java apps to Kubernetes using Helm charts
- Managing config maps and secrets in K8s
- Using Kustomize for environment-specific overlays
- Implementing blue-green deployments in K8s
- Setting up canary releases with Istio or Linkerd
- Automating rollbacks on health check failures
- Scaling Java apps based on CPU and memory usage
- Integrating with ingress controllers for routing
- Monitoring deployments with Prometheus and Grafana
- Securing K8s deployments with network policies
- Using ArgoCD for GitOps-style Java deployments
- Auditing deployment changes with K8s event logs
- Scanning Java dependencies with OWASP Dependency-Check
- Integrating Snyk or Aqua into the build pipeline
- Running static code analysis with Checkmarx or Sonar
- Validating container images for CVEs pre-deploy
- Enforcing signed commits and images
- Limiting pipeline permissions with least privilege
- Auditing pipeline access and changes
- Automating security policy enforcement
- Generating compliance reports from pipeline data
- Integrating with SIEM for anomaly detection
- Handling secrets with HashiCorp Vault or AWS Secrets Manager
- Responding to pipeline security alerts automatically
- Externalizing configuration with Spring Cloud Config
- Using environment variables in CI/CD pipelines
- Managing profiles for dev, staging, and prod
- Encrypting sensitive config values at rest
- Syncing config changes with GitOps workflows
- Validating config syntax before deployment
- Rolling back config changes safely
- Automating config drift detection
- Integrating with Consul or etcd for runtime config
- Documenting config dependencies per service
- Testing config changes in isolated environments
- Auditing config change history for compliance
- Designing health checks for Java microservices
- Using readiness and liveness probes in K8s
- Implementing rolling updates with Kubernetes
- Testing failover behavior during deploys
- Validating session persistence in stateful apps
- Automating traffic shift with service meshes
- Monitoring error rates during deployment
- Setting up automated rollback triggers
- Communicating deployment status to stakeholders
- Scheduling off-peak deployments safely
- Validating database schema changes pre-deploy
- Coordinating backend and frontend deploys
- Instrumenting Java apps with Micrometer
- Exporting metrics to Prometheus from CI
- Generating distributed traces with OpenTelemetry
- Validating logs format and structure in pipeline
- Setting up alerts on pipeline-generated metrics
- Correlating deployment events with system metrics
- Using Grafana dashboards for deployment visibility
- Testing observability in staging environments
- Archiving logs for audit and debugging
- Reducing noise in monitoring alerts
- Validating SLA compliance post-deployment
- Automating observability checks in CI
- Creating shared pipeline templates in GitLab
- Enforcing standards with pipeline linters
- Onboarding new teams to the CI/CD framework
- Managing multi-repo deployments
- Synchronizing versioning across services
- Using monorepo vs. polyrepo strategies
- Auditing pipeline usage across teams
- Training developers on pipeline ownership
- Documenting best practices in internal wikis
- Measuring CI/CD maturity across teams
- Reducing pipeline duplication with includes
- Scaling infrastructure for parallel pipeline runs
- Caching Maven dependencies between runs
- Using SSD runners for faster I/O
- Parallelizing test suites across jobs
- Optimizing Docker layer caching
- Reducing pipeline stages with early validation
- Skipping stages based on file changes
- Using ephemeral environments for testing
- Measuring pipeline duration trends
- Identifying slowest stages for optimization
- Right-sizing runner resources
- Cleaning up artifacts to save storage
- Scheduling off-peak pipeline runs
- Documenting pipeline architecture and decisions
- Collecting feedback from developers
- Tracking pipeline incident root causes
- Updating tools and plugins safely
- Migrating to new CI platforms when needed
- Archiving deprecated pipelines
- Measuring developer satisfaction with CI
- Conducting pipeline retrospectives
- Integrating with incident response workflows
- Training new hires on pipeline ownership
- Automating pipeline health checks
- Planning for pipeline evolution over time
How this maps to your situation
- Current manual deployment cycles
- Frequent environment inconsistencies
- Slow feedback from testing
- Need for zero-downtime releases
Before vs. after
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: 90 minutes per week for 4 weeks, with hands-on implementation tasks designed to fit around full-time development work.
How this compares to the alternatives
Unlike generic DevOps courses, this program is tailored to Java developers working in enterprise consulting environments, with specific tools, frameworks, and deployment patterns used at firms like the firm.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.