End-to-End Project Delivery with GitLab: From Issue Creation to Deployment Pipelines

The document describes a full‑stack GitLab CI/CD implementation for a Java service, covering the entire lifecycle from requirement preparation to production deployment.

1. Overall Planning – The workflow begins with creating issues, linking them to milestones, and generating feature branches whose names follow a numeric convention.

2. Requirement Preparation – Milestones are created, and for each issue a corresponding feature branch is opened.

3. Pipeline Preparation – Templates and reusable jobs are stored in a separate repository. Example template inclusion:

include:
  - project: 'cidevops/cidevops-newci-service'
    ref: master
    file: 'jobs/build.yml'
  - project: 'cidevops/cidevops-newci-service'
    ref: master
    file: 'jobs/test.yml'
  - project: 'cidevops/cidevops-newci-service'
    ref: master
    file: 'jobs/codeanalysis.yml'

4. Submit Pipeline Design – Developers push code to a feature branch, triggering a pipeline that compiles, tests, scans, builds a Docker image, and deploys to a dedicated feature environment. The stages are:

.build:
  stage: build
  script:
    - ${BUILD_SHELL}

.test:
  stage: test
  script:
    - ${TEST_SHELL}

.code_analysis:
  stage: code_analysis
  script:
    - sonar-scanner ${GLOBAL_PROJECT_ARGS} ${GLOBAL_SERVER_ARGS} ${SONAR_SCAN_ARGS}

5. Build Image Stage – After a successful build, a Docker image is created and pushed:

.build-docker:
  stage: buildimage
  script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWD $CI_REGISTRY
    - docker build -t ${IMAGE_NAME} -f ${DOCKER_FILE_PATH} .
    - docker push ${IMAGE_NAME}
    - docker rmi ${IMAGE_NAME}

6. Kubernetes Deployment Stage – Deployment manifests are templated and applied with kubectl . Example deployment job:

.deploy_k8s:
  stage: deploy
  script:
    - kubectl config set-cluster my-cluster --server=${KUBE_URL} --certificate-authority="${KUBE_CA_PEM_FILE}"
    - kubectl config set-credentials admin --token=${KUBE_TOKEN}
    - sed -i "s#__namespace__#${NAMESPACE}#g" ${DEPLOY_FILE}
    - sed -i "s#__appname__#${APP_NAME}#g" ${DEPLOY_FILE}
    - sed -i "s#__imagename__#${IMAGE_NAME}#g" ${DEPLOY_FILE}
    - kubectl apply -f ${DEPLOY_FILE}
  environment:
    name: "${ENV_NAME}"
    url: "http://${ENV_NAME}.${CI_PROJECT_NAMESPACE}.${CI_PROJECT_NAME}.devops.com"
    on_stop: "${ROLL_NAME}"

7. Pipeline Trigger Control – Workflow rules prevent pipelines from running on newly created branches (where CI_COMMIT_BEFORE_SHA is all zeros) and enable manual triggers for release branches:

workflow:
  rules:
    - if: $CI_COMMIT_BEFORE_SHA == "0000000000000000000000000000000000000000"
      when: never
    - when: always

Additional rules allow merge‑request pipelines and web‑triggered pipelines, and restrict automatic execution for feature branches unless manually approved.

8. Post‑Release Steps – After a successful release, the version branch is merged into master , a Git tag is created, and related issues and milestones are closed.

The guide concludes with a reminder to follow the DevOps Cloud Academy for more practical examples.