GitHub vs GitLab vs Agro Workflow
Platform Engineering

Github Vs Gitlab Vs Argo Workflow

GitHub, GitLab, and Argo Workflow are three powerful tools with unique capabilities for managing pipelines in software development.
Sanya Sawlani

As developers strive to deliver high-quality code at a rapid pace, the use of CI/CD pipelines has become increasingly essential. CI/CD Pipelines automate the process of building, testing, and deploying software, enabling teams to streamline their development workflows and deliver value to customers quickly. While there could be several version control systems that allow seamless CI/CD pipeline automation, GitLab and Argo Workflow are some of the most popular CI/CD platforms. GitHub, on the other hand, is a leading version control system that provides Github Actions as a strong CI/CD tool. Each platform has its strengths and features, making them suitable for different use cases and project requirements. In this article, we will explore the capabilities of each platform and compare them in the context of building Continuous Integration and Continuous Deployment pipelines for faster software releases. Also, we will discuss how engineering platforms like Atmsoly further make your application deployment pipelines easier, faster, and more secure.

What is GitHub?

GitHub is a web-based platform used for version control and collaboration on software projects. It allows developers to store and manage their code repositories, track changes to their code over time, and collaborate with other developers on projects. GitHub uses Git, a distributed version control system, to manage code changes.

Key Features of GitHub:

Key Features of GitHub
  1. Repository Management: GitHub allows you to create and manage Git repositories for your projects. You can create repositories for individual projects or collaborate with others on team projects.
  2. Collaboration Tools: GitHub provides tools for collaboration, such as pull requests, issues, and project boards. These tools help developers coordinate their work, review code changes, and track project progress.
  3. CI/CD Capabilities: GitHub Actions, GitHub's built-in CI/CD tool, allows you to automate your software development workflows. You can define custom workflows in YAML files to build, test, and deploy your code.
  4. Issue Tracking: GitHub includes a built-in issue-tracking system that allows developers to track bugs, feature requests, and other tasks related to their projects.
  5. Project Management: GitHub offers project management tools, such as project boards and milestones, to help teams organize and track their work.
  6. Continuous Integration: GitHub integrates with continuous integration (CI) tools, allowing developers to automate the testing and deployment of their code.
  7. Workflow Automation: GitHub provides integrations with other tools and services, allowing you to automate repetitive tasks and streamline your development process.
  8. Community and Support: GitHub has a large and active community of developers. You can find open-source projects, contribute to projects, and get help from other developers through forums and discussions.

What is GitLab?

GitLab is a web-based DevOps platform that provides Git repository management, CI/CD pipelines, issue tracking, and more. It offers a complete DevOps lifecycle toolchain in a single application, allowing teams to collaborate more efficiently and deliver software faster.

Key Features of GitLab:

Key Features of GitLab
  1. Repository Management: GitLab provides Git repository hosting with features such as branches, tags, and merge requests. It also supports code review workflows to facilitate collaboration among team members.
  2. CI/CD Pipelines: GitLab includes built-in CI/CD pipelines that allow you to automate the build, test, and deployment process of your applications. You can define pipelines using a YAML file in your repository.
  3. Issue Tracking: GitLab offers a robust issue-tracking system that allows you to create, assign, and track issues and bugs. You can also link issues to merge requests and track their status.
  4. Code Quality and Security: GitLab includes features for code quality and security, such as code review tools, static code analysis, and vulnerability scanning. These tools help you ensure that your code is of high quality and secure.
  5. Integrated DevOps Platform: GitLab provides a complete DevOps platform with features for collaboration, CI/CD, issue tracking, and more, all integrated into a single application. This allows teams to streamline their DevOps processes and work more efficiently.

What is Argo Workflows?

Argo Workflows is an open-source workflow engine for orchestrating parallel jobs on Kubernetes. It allows you to define complex workflows as code and execute them on Kubernetes cluster, making it ideal for managing data processing, machine learning, and CI/CD workflows. It offers a range of features and benefits that make it a popular choice for orchestrating parallel jobs in Kubernetes environments.

Key Features of Argo Workflows:

Key Features of Argo Workflows
  1. Workflow Orchestration: Argo Workflows allows you to define and run workflows as directed acyclic graphs (DAGs), enabling you to specify dependencies between tasks and orchestrate complex workflows with ease. Argo Workflows provides a declarative way to define workflows and ensures that they are executed correctly.
  2. Workflow Definition: Argo Workflows uses YAML files to define workflows, making it easy to version control and manage your workflows as code.
  3. Container-Native: Being container-native, Argo Workflows can run on both self-managed Kubernetes clusters and managed Kubernetes services like Amazon EKS, AKS, or GKE. This makes it a flexible choice for various deployment scenarios.
  4. Infrastructure as Code (IaC): With Argo Workflows, you can define your workflows using YAML, providing the benefits of infrastructure as code. This makes it easy to version control, share, and manage your workflows alongside your application code.
  5. Event-Driven Workflows: Argo Workflows supports event-driven workflows, allowing you to trigger workflows based on external events such as webhook notifications or changes to a Git repository.
  6. Multiple Command Execution: Argo Workflows allows you to run multiple commands with different parameters in a single workflow pipeline YAML definition. This simplifies the process of defining and executing complex workflows with varying requirements.
  7. Visualization and Monitoring: Argo Workflows provides a web-based user interface for visualizing and monitoring workflows. You can see the status of each step in your workflow and troubleshoot any issues that arise.
  8. Easy Management: Argo Workflows is implemented using Kubernetes custom resource definitions (CRDs), which means you can manage your workflows using familiar Kubernetes tools like kubectl. This makes it easy to create, monitor, and manage your workflows alongside your other Kubernetes resources.

Comparison of Pipeline Capabilities

This section let’s dive into the CI/CD pipeline functionalities offered by GitHub, GitLab, and Argo Workflows to help you choose the best fit for your development projects. It will focus on how they handle the CI/CD process, not version control itself.

GitHub: Streamlining Workflows with GitHub Actions

GitHub Actions is GitHub's CI/CD solution which allows you to automate workflows in your GitHub repository. Using YAML syntax, you can define workflows triggered by events like pushes or pull requests. It seamlessly integrates with GitHub features and offers a marketplace for custom actions, making it easy to automate your development workflow.

GitLab: Comprehensive CI/CD Capabilities

GitLab is renowned for its comprehensive DevOps platform, which includes robust CI/CD capabilities as a core feature. GitLab's CI/CD simplifies pipeline management with YAML configuration files in your repository. It speeds up pipelines with parallel job execution, offers dependency caching, integrates with external services, and provides built-in monitoring. Its seamless integration with other DevOps tools makes it a top choice for organizations.

Argo Workflow: Orchestrating Complex Workflows on Kubernetes

Argo Workflow is a Kubernetes-native engine for managing complex workflows. It uses directed acyclic graphs (DAGs) to define tasks and their dependencies, making it easy to orchestrate workflows in Kubernetes clusters. Argo Workflow integrates tightly with Kubernetes, offering scalability and resilience for running large-scale workflows. It's great for managing multi-step processes, dependencies, and conditional logic. With support for defining workflows in YAML and advanced features like templates and parameterization, Argo Workflow is a powerful tool for orchestrating pipelines in Kubernetes.

Github, Gitlab, and Argo Workflow Comparison 

Below are comparison metrics or factors you should watch out for;

Workflow Comparison

Combining Argo Workflow and ArgoCD

By definition, ArgoCD is a declarative, GitOps continuous delivery tool for Kubernetes. It allows you to maintain and manage Kubernetes resources using Git repositories as the source of truth for the declared desired states of applications. Typically, ArgoCD simplifies application deployment, configuration management, and GitOps practices.  But what makes ArgoCD truly compelling is its ability to integrate seamlessly with other tools like GitHub, GitLab, and Argo Workflows. WIth ArgoCD, you can build your Kubernetes workflow. 

ArgoCD offers you the following features that would be beneficial:

GitOps Model:

  • ArgoCD follows the GitOps model, where desired configuration changes are pushed to Git repositories.
  • The cluster state automatically syncs to the desired state defined in Git.
  • This ensures consistency and traceability.

Declarative Configuration Synchronization:

  • ArgoCD synchronizes application state with declarative configuration stored in Git.
  • Any drift between desired and actual states is automatically corrected.

Web User Interface (UI) and CLI:

  • ArgoCD provides both a visual web UI and a command-line interface (CLI).
  • The UI allows easy management of applications and monitoring of sync status.

Configuration Drift Detection:

  • ArgoCD detects configuration drift and alerts when the actual state deviates from the desired state.
  • It helps maintain consistency across environments.

Role-Based Access Control (RBAC):

  • Fine-grained RBAC ensures secure multi-cluster management.
  • Control who can manage applications and access resources.

Single Sign-On (SSO):

  • ArgoCD integrates with identity providers (e.g., GitLab, GitHub, OAuth2).
  • Users log in using existing credentials.

Webhooks for Automation:

  • ArgoCD supports webhooks triggered by Git events.
  • Automate synchronization and deployment based on changes.

Integration with CI Pipelines:

  • ArgoCD seamlessly integrates with existing CI/CD pipelines.
  • It automates application deployment based on GitOps workflows.

Setting Up and Configuring Pipelines with Github, Gitlab, and Argo workflow

Setting up your first GitHub pipeline:

  1. Accessing GitHub Actions: Navigate to your GitHub repository and click on the "Actions" tab.
  2. Creating a Workflow: Click on "Set up a workflow yourself" to create a new workflow file.
  3. Defining Workflow Steps: Define the steps for your workflow in YAML format, specifying actions, triggers, and conditions.
  4. Testing the Workflow: Commit and push your workflow file to your repository to trigger the workflow and test its functionality.
  5. Customizing Workflows: Explore the GitHub Actions marketplace for pre-built actions and workflows to customize your pipelines.

Setting up your first Gitlab pipeline:

In this tutorial, we'll walk through the process of creating a new project in GitLab and pushing your first file to the repository.

  1. Log in to GitLab

First, log in to your GitLab account at

  1. Create a New Project

Once logged in, create a new project by clicking on the "New project" button. Choose a name for your project, add a description, and select whether you want it to be private or publicly visible.

  1. Configure Git

Open your Git Bash and configure your user name and email ID using the following commands:

git config --global "Your Name"
git config --global ""
  1. Create a Local Repository

Create a new directory for your project and navigate into it:

mkdir my-project
cd my-project
  1. Initialize a Git Repository

Initialize a Git repository in your project folder:

git init
  1. Create a New File

Create a new file in your project folder. For example, you can create a text file using the following command:

touch input.txt
  1. Add and Commit Changes

Add the new file to the staging area and commit it to the repository:

git add .
git commit -m "Add input.txt"
  1. Push to GitLab

Push your changes to the GitLab repository. Copy the remote repository URL from your GitLab project page and use it in the following command:

git remote add origin <repository-url>
git push -u origin master
  1. Verify Changes

Check your GitLab project page to verify that the file has been successfully pushed to the repository.

Setting up your first Agro Workflow pipeline:

In this guide, we'll walk you through the process of getting started with Argo Workflows, from installation to setting up advanced workflows.

  1. Installing Argo Workflows

To install Argo Workflows, you'll need access to a Kubernetes cluster. You can install Argo Workflows using Helm, a package manager for Kubernetes. First, add the Argo Workflows Helm repository:

helm repo add argo

Then, install Argo Workflows:

helm install argo-workflows argo/argo
  1. Accessing the Argo Workflows UI

Argo Workflows comes with a web-based user interface that you can use to manage your workflows. To access the UI, you'll need to set up port forwarding to the Argo Workflows server:

kubectl port-forward svc/argo-server 2746:2746

You can now access the Argo Workflows UI by opening a web browser and navigating to http://localhost:2746.

  1. Creating Your First Workflow

To create a new workflow, you'll need to define a workflow template in YAML format. Here's an example of a simple workflow that runs a single job:

kind: Workflow
 generateName: hello-world-
 entrypoint: whalesay
 - name: whalesay
 image: docker/whalesay
 command: [cowsay]
 args: ["Hello, Argo Workflows!"]

Save this YAML file as hello-world.yaml and submit it to Argo Workflows:

“argo submit hello-world.yaml”

  1. Monitoring Your Workflow

You can monitor the progress of your workflow using the Argo Workflows UI or the command line. To list all running workflows, use the following command:

argo list

To get more detailed information about a specific workflow, use the following command:

argo get <workflow-name>
  1. Advanced Workflow Features

Argo Workflows supports many advanced features, such as parallelism, conditionals, and loops. You can use these features to create complex workflows that orchestrate multiple jobs.

  1. Integrating with Other Tools

Argo Workflows can be integrated with other tools and services to further automate your workflows. For example, you can use Argo Events to trigger workflows based on external events, or use Argo CD to automatically deploy your application after a successful workflow run.

Factors to Consider for Choosing a Pipeline Platform

Project Requirements:

  • Size and Complexity: Consider the size and complexity of your project. Larger projects may require more robust pipeline capabilities, such as parallel builds and distributed testing.
  • Development Workflow: Evaluate your development workflow and determine how a pipeline platform can fit into it seamlessly. Look for platforms that offer integrations with your existing tools and services.

Team Size and Collaboration Needs:

  • Collaboration Tools: Consider the collaboration tools offered by each platform, such as code review features, issue tracking, and team dashboards. Choose a platform that facilitates effective communication and collaboration among team members.
  • User Permissions: Look for platforms that offer granular user permissions, allowing you to control access to pipelines and sensitive information.

Integration Requirements:

  • Third-Party Integrations: Consider the third-party integrations offered by each platform. Look for platforms that integrate with your existing tools and services, such as version control systems, issue trackers, and deployment tools.
  • Customization: Evaluate the customization options available for pipelines. Look for platforms that allow you to customize pipelines to fit your specific needs and requirements.

Cost Implications and Pricing Models:

  • Free Tiers: Consider the free tiers offered by each platform. Evaluate the features and limitations of the free tiers to determine if they meet your needs.
  • Paid Plans: Look at the paid plans offered by each platform and evaluate their pricing and features. Consider factors such as the number of pipelines, parallel builds, and storage limits included in each plan.

Atmosly: A Streamlined CI/CD Automation Platform

Streamlined CI/CD Automation Platform

Atmosly acts as a DevOps automation platform built by developers, for developers, offering a unified experience to streamline your CI/CD workflow and boost your productivity.

Atmosly goes beyond basic Git integration with GitHub, Bitbucket and GitLab. Its killer feature is the Workflow Creation, a powerful toolset designed to supercharge your development process:

  • DevSecOps Integration: The Workflow Feature facilitates the seamless integration of DevSecOps tools within your pipelines. This allows you to incorporate security best practices and automated testing throughout the development lifecycle.
  • Complete CI/CD Engine: Atmosly isn't just an integration platform. It boasts its own built-in CI/CD engine, enabling you to define and execute your entire continuous integration and continuous delivery pipeline within a single platform.
  • Advanced YAML Configuration: For those comfortable with YAML syntax, Atmosly offers advanced configuration options. This allows you to integrate with existing CI pipelines defined in GitHub Actions or GitLab Pipelines. Atmosly then handles the deployment (CD) portion of the pipeline.

Benefits of Atmosly:

Benefits of Atmosly

In addition to the previously mentioned advantages, Atmosly's Workflow Feature unlocks further benefits:

  • Enhanced Security: By integrating DevSecOps tools, Atmosly promotes a security-conscious development environment, helping to identify and address vulnerabilities early in the pipeline.
  • Flexibility and Control: The ability to leverage both Atmosly's CI/CD engine and existing YAML configurations provides developers with greater flexibility and control over their workflows.

Atmosly remains a valuable tool for:

Atmosly: A Valuable Tool
  • Enhanced Collaboration: Centralized pipeline management fosters collaboration and knowledge sharing among development teams.
  • Workflow Automation: Automating pipeline tasks frees developers to focus on core coding activities.
  • Improved Visibility: Real-time pipeline monitoring ensures prompt identification and resolution of issues.
  • Scalability: Atmosly scales to meet the demands of projects of all sizes.
  • Cost-Effectiveness: Flexible pricing plans make Atmosly accessible for startups and large enterprises alike.


GitHub, GitLab, and Argo Workflow are three powerful tools with unique capabilities for managing pipelines in software development. GitHub offers streamlined workflows with GitHub Actions, integrating seamlessly with GitHub repositories. GitLab provides comprehensive CI/CD capabilities, supporting parallel execution of jobs and offering built-in monitoring and metrics. Argo Workflow excels in orchestrating complex workflows on Kubernetes, allowing you to define workflows as directed acyclic graphs (DAGs) and manage them with ease.

When choosing a pipeline platform, consider factors such as project requirements, team size and collaboration needs, integration requirements, and cost implications. Additionally, integrating these platforms with Atmosly can enhance collaboration, automate workflows, improve visibility, and scale pipelines, making it an ideal choice for managing pipelines in the modern software development environment.

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What are the key differences between GitHub, GitLab, and Argo Workflows?

GitHub and GitLab are both web-based platforms for version control using Git, but they have distinct features and capabilities. GitHub, known for its strong community and extensive integrations, is widely used for open-source projects. GitLab, on the other hand, offers a comprehensive DevOps platform with built-in CI/CD, which makes it popular for end-to-end software development lifecycle management. Argo Workflows, however, is a Kubernetes-native workflow engine for orchestrating parallel jobs on Kubernetes. Unlike GitHub and GitLab, which focus on version control and CI/CD, Argo Workflows is designed specifically for creating and managing complex workflows in a Kubernetes environment.

How do CI/CD capabilities differ between GitHub, GitLab, and Argo Workflows?

GitHub provides CI/CD capabilities through GitHub Actions, which allows users to automate workflows directly from their repositories. GitLab offers a more integrated approach with GitLab CI/CD, which is deeply embedded within the platform, providing extensive configuration and monitoring options. Argo Workflows focuses on orchestrating containerized tasks on Kubernetes, offering powerful workflow automation but requiring more infrastructure setup compared to GitHub Actions and GitLab CI/CD. While GitHub and GitLab cater to a broader audience, Argo Workflows is more suited for Kubernetes-based CI/CD pipelines.

Which platform offers better security features: GitHub, GitLab, or Argo Workflows?

GitLab generally leads in security features, offering a robust set of security tools including static application security testing (SAST), dynamic application security testing (DAST), dependency scanning, container scanning, and more. GitHub also provides solid security features like code scanning and secret detection, enhanced by its acquisition of Dependabot. Argo Workflows, while secure in its execution within Kubernetes, relies on the security of the underlying Kubernetes environment and the configurations set by the user. Thus, GitLab and GitHub offer more out-of-the-box security features for version control and CI/CD.

How do GitHub, GitLab, and Argo Workflows handle scalability?

GitHub and GitLab are designed to handle large-scale projects with extensive collaboration features. GitHub's cloud infrastructure supports large repositories and high-traffic projects, while GitLab's self-managed and SaaS options provide flexibility for scaling. Argo Workflows, being Kubernetes-native, excels in scalability within Kubernetes clusters, allowing users to manage thousands of workflows and tasks concurrently. However, setting up and managing a scalable Argo Workflows environment requires Kubernetes expertise.

Can GitHub, GitLab, and Argo Workflows integrate with other tools and services?

Yes, all three platforms offer extensive integration capabilities. GitHub integrates with a vast ecosystem of tools and services through GitHub Marketplace and APIs. GitLab provides integrations with numerous third-party tools and also supports custom integrations via its API. Argo Workflows integrates well with Kubernetes-native tools and services and can be extended using custom templates and scripts. The choice of platform often depends on the specific tools and workflows a team uses.

What are the differences in user interface and user experience among GitHub, GitLab, and Argo Workflows?

GitHub is known for its clean, user-friendly interface that emphasizes collaboration and ease of use. GitLab's interface is comprehensive, offering a wide range of features in an integrated manner, which can be overwhelming for new users but powerful for experienced users. Argo Workflows, being a workflow orchestrator, has a more technical and less polished interface, primarily accessed through a command-line interface (CLI) or Kubernetes-native tools, appealing more to DevOps engineers familiar with Kubernetes.

How do GitHub, GitLab, and Argo Workflows support collaboration among team members?

GitHub excels in collaboration with features like pull requests, issues, project boards, and GitHub Discussions. GitLab also offers strong collaboration tools, including merge requests, issue tracking, and milestone tracking, with the added advantage of integrated CI/CD and DevOps capabilities. Argo Workflows, while not a collaboration tool per se, supports collaborative workflow development through versioned templates and workflows, but lacks the integrated social and project management features of GitHub and GitLab.

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