GitLab Advanced CI/CD Training
This advanced class extends the knowledge and concepts of the foundational CI/CD class, adding the skills needed to implement CI/CD best practices across more complex use cases. Throughout this hands-on session, participants will explore GitLab CI/CD features like feature flags, review apps, canary deployments, and runner scaling/distribution strategies. The curriculum covers additional configuration options such as multi-project pipelines, merge trains, and environment management. Optimization techniques like fail-fast testing, parallelization, and reference tags are examined for enhancing efficiency. Revisiting best practices and troubleshooting strategies round out the content, equipping learners to implement CI/CD pipelines leveraging the full scope of GitLab's capabilities.
What you will learn
- Implement CI/CD best practices for complex use cases
- Explore GitLab CI/CD features like feature flags, review apps, and canary deployments
- Understand runner scaling and distribution strategies
- Configure multi-project pipelines, merge trains, and manage environments
- Apply optimization techniques like fail-fast testing and parallelization
- Utilize advanced features like extends, hidden jobs, anchors, and reference tags
- Troubleshoot complex CI/CD pipeline issues
Prerequisites
- Topics covered in the GitLab CI/CD training or equivalent experience with GitLab
- This class is not appropriate for students with no CI/CD or GitLab knowledge
- Computer with internet access and Git installed
Target audience
- Development teams, Quality assurance teams, Release engineers
Training Program
9 modules to master the fundamentals
Topics covered
- →Quick review of GitLab CI/CD class concepts
- →Overview of what will be covered and the lab scenario
Topics covered
- →Runner scaling
- →Multi-zone / multi-region runner availability
- →Configuring a Kubernetes executor
- →Services
Topics covered
- →Pipeline efficiency
- →Caching
- →Dependency Proxy
- →Artifacts
Topics covered
- →Fail fast testing
- →Unit test reports
- →Parallelism/test splitting
Topics covered
- →Extends
- →Hidden Jobs
- →Anchors
- →Aliases
- →Map merging
- →Reference tags
Topics covered
- →Workflow
- →Merge trains
- →Multi-project pipelines, including sharing artifacts and variables
Topics covered
- →Review apps
Topics covered
- →Feature flags
- →Blue/Green Deployments (GitLab Canary)
- →Managing multiple environments
Topics covered
- →Addressing troubleshooting for more complex use cases
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Upcoming sessions
No date suits you?
We regularly organize new sessions. Contact us to find out about upcoming dates or to schedule a session at a date of your choice.
Register for a custom dateTrain multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote