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why we need gitops in K8s project

GitOps is a methodology that uses Git as a single source of truth for managing infrastructure configurations and application deployments. Here’s a simple example to illustrate why GitOps is beneficial and what might happen if you do not use it:

Example Scenario: Deploying a Web Application

With GitOps:

  1. Setup:

    • You define your Kubernetes manifests (deployment.yaml, service.yaml, ingress.yaml) for deploying a web application.
    • These manifests are stored in a Git repository along with configuration files (values.yaml) that define settings like environment variables or replicas.
  2. Deployment Process:

    • Changes to your application or infrastructure are made by updating the YAML files in your Git repository.
    • You commit and push these changes to the Git repository.
  3. Automated Deployment:

    • A GitOps tool (e.g., Flux, Argo CD) monitors the Git repository for changes.
    • Upon detecting a change, the GitOps tool automatically synchronizes the Kubernetes cluster with the desired state defined in Git.
    • It applies the changes (e.g., updates deployments, services) to the cluster, ensuring that the deployed state matches the configuration stored in Git.
  4. Benefits:

    • Consistency: Ensures that the deployment across different environments (dev, staging, prod) remains consistent because configurations are version-controlled and managed through Git.
    • Auditability: Provides a clear audit trail of who made changes, what changes were made, and when they were applied, enhancing transparency and accountability.
    • Reliability: Automates deployment processes, reducing human error and ensuring that deployments are reproducible and predictable.

Without GitOps:

  1. Manual Deployment:

    • Changes to configurations or deployments are made directly on the Kubernetes cluster using kubectl apply or similar tools.
    • Configurations might be managed locally or through scripts, making it harder to track changes and maintain consistency.
  2. Challenges:

    • Configuration Drift: Over time, configurations on the cluster may diverge from what is stored in version control, leading to inconsistencies.
    • Difficulty in Rollbacks: Without version control and automated processes, rolling back changes to a previous stable state becomes challenging and error-prone.
    • Visibility and Control: Limited visibility into who made changes and what exactly changed, making troubleshooting and debugging more difficult.
  3. Operational Risks:

    • Human Error: Manual deployments increase the risk of human errors during updates or rollbacks, potentially causing downtime or instability.
    • Scalability Issues: Managing deployments manually becomes increasingly complex as the number of applications and environments grows.
Published on: Jul 08, 2024, 05:53 AM  


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