GitOps for ML Deployments - Interactive Visualization

GitOps applies the Git workflow to infrastructure and deployment management: the repository is the single source of truth, and a controller (ArgoCD or Flux) continuously reconciles the cluster to match what is declared in Git. For ML systems, this means model deployments, GPU allocations, and serving configurations are all managed through pull requests with code review, CI checks, and instant rollback by reverting a commit. When someone manually changes the cluster, GitOps detects the drift and auto-heals it.

• Inject a config drift (replicas: 3→2, memory: 8Gi→6Gi) to simulate someone manually editing the cluster outside of Git
• Watch the ArgoCD flow: Git Repo → Watch → Detect Drift → Sync Cluster → Notify - each stage animates in sequence
• View the desired vs actual state comparison side by side - drifted fields highlighted in red
• Trigger a sync to reconcile the cluster back to the Git-declared state, or roll back to HEAD~1

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.