What is your experience working with GitLab CI?

Worked with GitLab CI in projects related to automation of build, testing, and deployment of applications.

Main tasks:

• Creating and configuring pipelines: Describing build, test, and deploy stages using .gitlab-ci.yml.
• Managing runners: Setting up, registering, and scaling Shared and Specific runners (Docker Executor, Shell Executor).
• Integration with tools: Connecting SonarQube for code analysis, Docker Registry for image storage, Helm for managing deployment in Kubernetes.
• Pipeline optimization: Speeding up builds through dependency caching and parallel task execution.
• Implementing CI/CD: git flow Developing continuous integration and delivery strategies, including automatic deployment to various environments (staging, production) upon successful tests.
• Handling artifacts: Configuring storage and access to build and test results.
• Deployment automation: Using dpl, GitLab Pages, integrating with Ansible and Terraform for infrastructure.

Configuration examples:

image: docker:latest # Using Docker image for build

services:
  - docker:dind # Running Docker in Docker for container builds

variables:
  DOCKER_REGISTRY: $CI_REGISTRY # Variable for GitLab registry path

stages:
  - build
  - test
  - deploy

build_image:
  stage: build
  script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY # Registry login
    - docker build -t $DOCKER_REGISTRY/$CI_PROJECT_NAMESPACE/$CI_PROJECT_NAME:$CI_COMMIT_SHA-$CI_COMMIT_REF_SLUG . # Build image with tag
    - docker push $DOCKER_REGISTRY/$CI_PROJECT_NAMESPACE/$CI_PROJECT_NAME:$CI_COMMIT_SHA-$CI_COMMIT_REF_SLUG # Push image to registry
  only:
    - main

run_tests:
  stage: test
  image: python:latest # Using Python image for tests
  script:
    - pip install -r requirements.txt # Install dependencies
    - pytest # Run tests
  only:
    - merge_requests

deploy_staging:
  stage: deploy
  environment:
    name: staging
    url: https://staging.example.com # Staging environment URL
  needs: ["run_tests"] # Dependency on successful tests
  script:
    - # Commands for deploying to staging (e.g., via Helm)
  only:
    - main

deploy_production:
  stage: deploy
  environment:
    name: production
    url: https://example.com # Production URL
  needs: ["deploy_staging"] # Dependency on successful staging deployment
  script:
    - # Commands for deploying to production (manual or scheduled)
  when: manual # Manual trigger for production deployment
  only:
    - main

Aspects worked with:

Aspect	Experience
runnersExecutors	Docker, Shell
cache	Used to speed up builds
artifacts	Saving logs, reports, collected artifacts
environments	Defining environments for deployment
variables	Secret variables, CI/CD variables
rules/only/except	Conditional job execution
include	Splitting configuration into smaller files
triggers	Starting pipelines based on external events
child pipelines	Nested pipelines for complex projects
job dependencies	Configuring dependencies between jobs

I have a solid understanding of CI/CD principles and can apply GitLab CI to build reliable and automated development and deployment processes.