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Intro
CI/CD Fundamentals
Introduction to CI/CD Pipelines
Benefits of Using GitLab CI/CD
GitLab CI/CD Components
Practical Implementation of CI/CD Pipelines
.gitlab-ci.yml Basics
How to Create a .gitlab-ci.yml File
Basic Structure of a .gitlab-ci.yml File
Step by Step Guide to Creating a .gitlab-ci.yml File
Advanced Configuration
Full Example
GitLab Runners
GitLab Runners
Choosing the Right Runners
Runner Configuration
Runner Management Best Practices
Why Use Runners?
GitLab Executors
What Are GitLab Executors?
Why Are Executors Important?
Docker Executor
Shell Executor
Specific Runners
Installing Specific Runners
Installing GitLab Runner on Linux
Installing GitLab Runner on macOS
Installing GitLab Runner on Windows
Creating the Runner
Registering the Runner
Verifying the Runner
Configuring the Runner
Artifacts
Artifacts in GitLab CI/CD
Storing Artifacts in .gitlab-ci.yml
Retrieving Artifacts
Using Artifacts in Subsequent Jobs
Advanced Artifact Management
Conclusions
Documentation Generation
Documentation Generation in GitLab CI/CD Pipelines
Setting Up MkDocs
Configuring MkDocs
Creating Documentation Pages
Summary
Monitoring
Basic Monitoring in GitLab CI/CD
Enable Pipeline Monitoring
Add Notifications for Pipeline Events
Add Notifications for Pipeline Events

GitLab Executors

Why Are Executors Important?

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4.2. Why Are Executors Important?

Executors play a crucial role in the CI/CD process by:

  • Providing Isolation: Each job runs in a clean and isolated environment, preventing conflicts and ensuring consistent results.
  • Offering Flexibility: Different projects have different requirements. Executors allow you to choose the most suitable environment for your jobs, whether it’s a lightweight Docker container or a fully-fledged virtual machine.
  • Enhancing Scalability: Executors can be configured to run on scalable infrastructure, allowing CI/CD pipelines to handle large workloads and complex tasks.

Overview of Executor Types

Here are the main executor types used for GitLab CI/CD pipelines:

  1. Shell Executor: Runs jobs directly on the host machine’s shell.
  2. Docker Executor: Runs jobs inside Docker containers, providing a consistent and isolated environment.
  3. Docker Machine Executor: Spins up and manages Docker containers on demand, offering scalable execution.
  4. Kubernetes Executor: Runs jobs in a Kubernetes cluster, ideal for containerized workloads.
  5. SSH Executor: Runs jobs on remote machines over SSH.
  6. Custom Executor: Allows for highly customized execution environments.
  7. VirtualBox Executor: Runs jobs in VirtualBox virtual machines, useful for environments requiring full operating system virtualization.
  8. Parallels Executor: Runs jobs in Parallels virtual machines, similar to the VirtualBox executor but using Parallels for virtualization.

Each executor type has its unique features and use cases, allowing you to tailor your CI/CD environment to meet the specific needs of your projects.

In this module, we will introduce 3 main executor types and the advantages and disadvantages of each of the executors.

Example with Data Analysis Project: For our Data Analysis, using Docker executors can help ensure that our application behaves consistently across different environments (development, testing, production). The isolation provided by Docker containers can prevent dependency conflicts and ensure that our application runs smoothly in various scenarios. However, the choice of executor ultimately depends on the project’s requirements and the desired level of isolation and scalability.