Learn GITLAB-CI with Real Code Examples

Build and test Python project with pytest

Build Docker image and push to registry

Deploy to staging environment via SSH

Run parallel tests for multiple environments

Trigger downstream pipeline on merge request

Check pipeline logs for failed jobs

Verify runner availability and registration

Ensure correct syntax in `.gitlab-ci.yml`

Inspect environment variables and secrets

Validate Docker images or dependencies

Use 'gitlab-ci lint' to validate YAML syntax

Run pipeline in staging before production

Test job scripts locally before committing

Check artifacts and cache usage

Verify triggers and schedules execute correctly

Manual deployment using 'when: manual'

Automatic deployment on merge to main branch

Deploy via Kubernetes executor

Docker-based deployment pipelines

Multi-environment deployment with review apps

GitLab Runner CLI

GitLab Auto DevOps

GitLab Container Registry

GitLab Environments and Deployments

GitLab Pipeline Editor and Lint tools

Docker and Kubernetes

Terraform and Ansible for infrastructure deployment

Slack or email notifications for pipelines

Monitoring tools like Prometheus and Grafana

External CI/CD systems via triggers and webhooks

Use templates for reusable jobs

Leverage caching and artifacts

Parallelize jobs where possible

Use variables for dynamic configurations

Monitor pipelines for bottlenecks and optimize

Debugging complex pipelines

Managing multiple runners and executors

Optimizing pipeline speed and resource usage

Securing secrets and variables

Maintaining pipeline readability and maintainability