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Argo CD

  • Install minicube:
curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64
sudo install minikube-linux-amd64 /usr/local/bin/minikube
  • Start minikube:
minikube start
  • Install ArgoCD
kubectl create namespace argocd

kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml
  • Port forward ArgoCD:
kubectl port-forward svc/argocd-server -n argocd 8080:443
  • Open UI at:
http://localhost:8080
  • Default password:
kubectl -n argocd get secret argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d
  • Apply argocd application
kubectl apply -f k8s/argocd-app.yml

PoC :

POC No. Description Difficulty
1 Deploy a simple ML model API (FastAPI) using ArgoCD Basic app GitOps deployment 🟢 Easy
2 GitOps-driven Model Versioning Deployments Rolling out new models automatically 🟡 Medium
3 Argo Rollouts + ArgoCD for Canary Model Rollouts Canary releasing new ML models safely 🟡 Medium
4 Multi-tenancy setup for ML environments Different namespaces per team 🟠 Medium-Hard
5 Full Kubeflow Pipelines GitOps Deployment with ArgoCD Production-grade ML platform GitOps 🔴 Advanced
6 Secure Secret Management (model creds, DB creds) with ArgoCD + External Secrets Secret management in GitOps 🔴 Advanced
7 Self-Healing ML Inference Service Auto-sync + health check + rollback broken models 🔴 Advanced

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Argo CD use cases in ML Platform

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