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In this video, I have successfully completed Phase IV: Local Kubernetes Deployment of my Cloud-Native Todo Chatbot π―. The goal of this phase was to deploy both frontend and backend applications on a local Kubernetes cluster using Minikube, following a Spec-Driven, Agentic Dev Stack workflow β without manual coding. π Whatβs covered in this video: Containerizing frontend and backend using Docker Desktop AI-assisted Docker operations using Docker AI Agent (Gordon) Creating and deploying Helm Charts Deploying the application on Minikube Using kubectl-ai for intelligent Kubernetes commands Using Kagent for cluster health analysis and optimization Managing replicas, scaling, and debugging pods with AI assistance π§ Tools & Technologies Used: Docker & Docker Desktop Docker AI Agent (Gordon) Kubernetes (Minikube) Helm Charts kubectl-ai Kagent Claude Code (Agentic Dev Stack) π‘ Development Approach: Write Spec β Generate Plan β Break into Tasks β Implement via AI Agents (No manual coding involved β fully AI-assisted workflow) This phase demonstrates how Spec-Driven Development can be extended beyond application code into infrastructure automation and AI-powered DevOps. If youβre learning Kubernetes, DevOps, Cloud-Native apps, or AI-assisted development, this video will give you real hands-on insight with zero cloud cost. π Like, Share & Subscribe for upcoming phases and advanced cloud-native workflows.