Drive Team Excellence with GitLab CI-CD Corporate Training

The primary aim of CI is to detect and fix integration issues earlier in the development cycle, thereby improving software quality and reducing the time taken to validate and release new software updates. The CD approach enables a more agile deployment process and ensures end-users can quickly benefit from new features, bug fixes, and updates. GitLab CI/CD pipelines are highly customizable, supporting complex workflows tailored to different project needs.

The GitLab CI-CD instructor-led training course focuses on setting up basic CI/CD pipelines, understanding pipeline architecture, and working with GitLab runners. It includes practical applications like deploying applications to Docker Container registries and utilizing GitLab's security scanners. Our virtual/onsite GitLab CI-CD training course equips professionals with the skills to stay at the forefront of software development and DevOps trends.

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Skills Your Employees Will Gain

These are the core, hands-on capabilities your team builds during the program.

  • Security Scanning
    Security Scanning is the process of identifying vulnerabilities in systems and networks. this skill is important for cybersecurity roles to proactively protect against threats.
  • Pipeline Configuration
    Pipeline Configuration is the process of setting up and managing automated workflows for data processing and deployment. This skill is important for DevOps and data engineering roles, as it ensures efficient, reliable, and scalable software delivery.
  • Performance Analysis
    Performance Analysis involves assessing and interpreting data to evaluate efficiency and effectiveness. This skill is important for roles in management, sports, and finance, as it drives informed decision-making and enhances productivity.
  • Automated Testing
    Automated Testing is the use of software tools to execute tests automatically, ensuring code quality and functionality. This skill is important for developers and QA engineers as it enhances efficiency, reduces errors, and accelerates the release cycle.
  • Advanced Optimization
    Advanced Optimization is the process of enhancing systems or processes for maximum efficiency and performance. this skill is important for roles in data analysis, engineering, and operations, as it drives cost reduction, improves productivity, and enhances decision-making.
  • Cloud Integration
    Cloud Integration is the process of connecting various cloud services and applications to streamline data flow and enhance functionality. This skill is important for IT professionals, as it enables seamless collaboration, improves efficiency, and supports scalable solutions in modern business environments.

What Your Team Will Achieve After This Training

  • Evaluate security vulnerabilities and implement security scanning within the CI/CD pipelines
  • Configure complex CI/CD pipelines in GitLab, tailoring them to specific project requirements
  • Analyze the performance and efficiency of existing pipelines to identify areas for improvement
  • Create and manage automated tests within the CI/CD process, ensuring code quality and reliability
  • Apply advanced features of GitLab CI/CD to optimize software development and deployment processes
  • Integrate GitLab CI/CD with various cloud platforms and containerization tools for streamlined deployment
  • Demonstrate proficiency in using GitLab Runners and effectively manage their deployment in diverse environments
  • Design effective strategies for continuous integration and continuous deployment, aligning them with organizational goals and practices

Topics & Program Outline

The curriculum is organized into focused modules built by industry experts and delivered virtually or on-premise. Interactive sessions reflect the evolving demands of the workplace, keeping the learning both relevant and practical.

  1. What is GitLab
    • Introduction to GitLab
    • GitLab features and benefits
    • GitLab as a DevOps platform
  2. Today's software delivery landscape
    • Challenges of traditional software delivery
    • Agile and DevOps methodologies
    • CI/CD as a key component of DevOps
  3. GitLab workflow & example
    • GitLab's unified development platform
    • GitLab project lifecycle
    • Example of a GitLab workflow
  4. What is CI/CD
    • Continuous Integration (CI) and Continuous Delivery (CD) concepts
    • Benefits of CI/CD
    • CI/CD pipeline stages
  5. GitLab's CI/CD workflow
    • GitLab's built-in CI/CD capabilities
    • GitLab pipeline configuration
    • Triggering CI/CD pipelines
  6. Why use CI/CD
    • Improved software quality
    • Faster release cycles
    • Reduced risk of deployment failures
  7. Dogfooding: building GitLab with GitLab
    • GitLab's commitment to dogfooding
    • Benefits of dogfooding
    • How GitLab uses CI/CD to build itself
  8. Demo/Lab: review a sample CI/CD section
    • Hands-on exploration of a sample CI/CD configuration file
    • Understanding the different stages and jobs in the pipeline
    • Analyzing the use of variables and triggers
  1. Configuration file & GitLab runners
    • Introduction to the .gitlab-ci.yml configuration file
    • Role of GitLab Runners in executing pipeline jobs
    • Interaction between the configuration file and Runners
  2. Runner architecture
    • Overview of the GitLab Runner architecture
    • Components of a GitLab Runner
    • Deploying and managing Runners
  3. Runner characteristics & types
    • Different types of GitLab Runners
    • Choosing the appropriate Runner type for a project
    • Scalability of GitLab Runners
  4. Runner options
    • Configuring runner options for specific needs
    • Runner tagging and labeling
    • Resource constraints and limitations
  5. Runner executors
    • Understanding runner executors and their role in pipeline jobs
    • Common executor types and their compatibility
    • Configuring and managing runner executors
  6. Demo/Lab: register a GitLab Runner for a simple pipeline
    • Hands-on experience with registering and configuring a GitLab Runner
    • Setting up the Runner to execute a simple pipeline job
    • Verifying the Runner's successful registration and connection
  1. Anatomy of a CI/CD pipeline
    • Breakdown of a CI/CD pipeline into stages and jobs
    • Understanding the flow of data and artifacts through the pipeline
    • Interdependencies between stages and jobs
  2. Basic pipeline builds
    • Creating a simple CI/CD pipeline for a basic project
    • Defining stages and jobs using the .gitlab-ci.yml file
    • Running and monitoring the pipeline
  3. Directed acyclic graph pipelines
    • Introducing Directed Acyclic Graph (DAG) pipelines
    • Structuring pipelines with multiple branches and dependencies
    • Benefits of using DAG pipelines
  4. Child & parent pipelines
    • Concept of child and parent pipelines in GitLab CI/CD
    • Decoupling pipeline stages using child pipelines
    • Reusing pipeline jobs across multiple parent pipelines
  5. GitLab pipeline graph
    • Visual representation of CI/CD pipelines using the GitLab Pipeline Graph
    • Understanding the pipeline flow and dependencies from the graph
    • Identifying potential bottlenecks and optimization opportunities
  6. Basic keywords: definitions & examples
    • Introduction to essential keywords used in CI/CD pipeline configuration
    • Understanding the purpose and syntax of each keyword
    • Examples of using keywords to define pipeline stages, jobs, and dependencies
  7. .gitlab-ci.yml example
    • In-depth analysis of a real-world .gitlab-ci.yml file
    • Understanding the structure and organization of the configuration file
    • Recognizing the use of keywords and pipeline elements
  8. Demo/Lab: create a basic CI/CD configuration
    • Hands-on experience with creating a basic CI/CD configuration file
    • Defining stages and jobs for a simple project
    • Including scripts and commands for specific pipeline tasks
  9. Demo/Lab: display environment variables in a pipeline
    • Understanding the concept of environment variables in CI/CD pipelines
    • Accessing and displaying environment variables within
  1. Advanced keywords
    • Exploring advanced keywords for more complex pipeline configurations
    • Utilizing conditional execution and loops in pipelines
    • Handling errors and failures gracefully
  2. Writing maintainable CI/CD configuration files
    • Principles of writing maintainable and reusable CI/CD configuration files
    • Techniques for organizing and commenting the configuration file
    • Leveraging GitLab's features for managing and versioning configuration files
  1. Variable scope & priority
    • Understanding the different scopes of variables in GitLab CI/CD
    • Variable precedence and priority rules
    • Overriding and setting variable values effectively
  2. Lab: variable hierarchy
    • Hands-on practice with variable scoping and priority
    • Defining variables at different levels (project, job, and stage)
    • Observing the impact of variable precedence on pipeline execution
  1. Lab: job policy pattern
    • Hands-on experience with implementing job policy patterns
    • Using rules and conditions to control job execution
    • Enforcing job requirements and constraints
  2. Microlearning game: pipeline review
    • Interactive review of CI/CD pipeline concepts and strategies
    • Analyzing and optimizing pipeline configurations for different scenarios
    • Identifying potential issues and areas for improvement
  1. Lab: using artifacts
    • Hands-on experience with managing artifacts in CI/CD pipelines
    • Creating, caching, and sharing artifacts between pipeline stages
    • Optimizing artifact storage and usage
  • What are package & container registries?
    • Introduction to package and container registries in the CI/CD workflow
    • Role of registries in storing and managing software artifacts
    • Integrating registries with GitLab CI/CD
  • Lab: GitLab docker registry
    • Hands-on practice with GitLab's integrated Docker registry
    • Pushing and pulling Docker images to the registry
    • Utilizing the registry for automated deployments

Who Should Attend?

This program suits professionals at many levels across the organization, including:

  • DevOps Engineers
  • Software Developers
  • QA Engineers
  • System Administrators
  • DevOps Managers
  • Release Engineers
  • Automation Engineers
  • CI/CD Engineers
  • Release Managers
  • Infrastructure Engineers
  • Software Engineers
  • IT Managers

What are the Prerequisites?

The GitLab CI-CD training can be taken by professionals with a basic understanding of Git and GitLab.

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We design training your teams actually engage with, and deliver it the way that suits you best. Through a vetted global trainer network, Edstellar runs sessions in 10+ languages with consistent quality anywhere.

Virtual GitLab CI-CD Training

Virtual / online: expert-led live sessions delivered anywhere, with consistency and easy scheduling.

We deliver anywhere worldwide
Standardized content for consistent outcomes
Join from own workspace, no travel
We scale to large groups across sites
Interactive tools keep remote learners engaged
On-site GitLab CI-CD Training

On-site (in-house): immersive, instructor-led learning at your office.

Our trainers run face-to-face at your office
We tailor setup/content to your workplace and tools
Group exercises drive collaboration
Live demos +  hands-on practice
Direct trainer access to clarify doubts
Off-site GitLab CI-CD Training

Off-site: focused, instructor-led group learning away from everyday workplace distractions.

We host your teams at a venue of your preferred choice
Built-in group activities for bonding
Full uninterrupted schedule for focus/retention
Boosts morale and signals commitment

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        "The GitLab CI-CD training exceeded my expectations in every way. As a Senior Software Engineer, I gained comprehensive knowledge of industry best practices that transformed my approach to professional and immediately applicable. I've successfully implemented these advanced techniques in production environments with measurable impact. The instructor's expertise in real-world case studies made complex concepts crystal clear and actionable.”

        Buford Hawkins

        Senior Software Engineer,

        Collaborative Development Platform

        "The GitLab CI-CD training enhanced my ability to architect and implement sophisticated technical mastery strategies. Understanding practical applications through intensive practical simulations exercises proved invaluable for client projects. to optimize enterprise initiatives. Our client satisfaction scores improved by 35% across all accounts. The detailed exploration of interactive labs provided methodologies I leverage in every engagement.”

        Marcin Wisniewski

        Senior Software Engineer,

        DevSecOps Platform Solutions Provider

        "As a Senior Software Engineer overseeing strategic implementation initiatives, the GitLab CI-CD training significantly elevated our team's capabilities. The course expertly covered strategic frameworks, expert-led workshops, our operational effectiveness. Our stakeholder satisfaction and NPS scores reached unprecedented all-time highs. Our department has achieved remarkable improvements, demonstrating this course's lasting organizational impact.”

        Balaji Thakur

        Senior Software Engineer,

        Git-Based CI/CD Solutions Firm

        “Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

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