Portfolio / Home.
Hey, I'm Harshhaa
Building scalable developer platforms, production AI infrastructure, autonomous AI agents, MCP ecosystems, and AI products.
- Platform Engineering
- DevOps & GitOps
- AI Infrastructure
- LLMOps
- GenAI & AI Agents
- Model Context Protocol (MCP)
- AI Product Development
- Kubernetes & Cloud
About.
Building scalable developer platforms, production AI infrastructure, autonomous AI agents, MCP ecosystems, and AI products.
Platform & DevOps Foundation: 5+ years of engineering hands-on internal developer platforms (IDPs), declarative infrastructure with Terraform, Kubernetes container orchestration, and automated GitOps CI/CD pipelines across AWS and Azure.
AI Infrastructure & LLMOps: Building scalable inference infrastructure, GPU-accelerated Kubernetes nodes, model deployment with vLLM and Ollama, vector search retrieval (Qdrant, pgvector), and MLflow experiment tracking.
GenAI, AI Agents & MCP: Architecting autonomous agent workflows with LangGraph and LangChain, developing custom Model Context Protocol (MCP) servers to interface LLMs with cloud APIs and DevOps tooling, and multi-agent coordination (A2A).
AI Product Development: Leading the end-to-end design, implementation, and deployment of user-facing AI products, intelligent platform automation bots, and self-service developer portals.
Open-Source Impact: Prolific builder with 40+ production DevOps & AI project blueprints, educational docs, and open-source tooling empowering 250,000+ engineers globally.
GitHub Activity.
@NotHarshhaaTechnical Skills Taxonomy.
- •Platform Engineering
- •Internal Developer Platforms (IDP)
- •Backstage
- •Developer Experience (DevEx)
- •GitOps
- •ArgoCD
- •Self-Service Portals
- •Golden Paths
- •DevOps
- •CI/CD Pipelines
- •GitHub Actions
- •Azure DevOps
- •GitLab CI
- •Jenkins
- •Helm
- •Argo Rollouts
- •Release Automation
- •AI Infrastructure
- •LLMOps
- •MLOps
- •vLLM
- •Ollama
- •MLflow
- •Vector Databases (Qdrant/Milvus/pgvector)
- •RAG Pipelines
- •GPU Cluster Management
- •Generative AI
- •AI Agents
- •Agentic AI Systems
- •Model Context Protocol (MCP)
- •Agent2Agent (A2A)
- •LangGraph
- •LangChain
- •Prompt Engineering
- •Context Engineering
- •Autonomous Workflows
- •AI Product Development
- •Full-Stack AI Apps
- •FastAPI
- •Next.js AI SDK
- •Interactive AI Agents
- •Tool Calling & Function Calling
- •Semantic Search
- •Kubernetes (EKS/AKS)
- •Docker
- •AWS
- •Azure
- •GCP
- •Karpenter
- •Container Optimization
- •Terraform
- •OpenTofu
- •Ansible
- •Infrastructure as Code (IaC)
- •Terragrunt
- •Policy as Code (OPA)
- •Prometheus
- •Grafana
- •OpenTelemetry (OTel)
- •Loki
- •Alertmanager
- •Incident Management
- •Observability
- •Python
- •Bash / Shell Scripting
- •Go (Golang)
- •Linux Administration & Networking
- •REST & gRPC APIs
- •Open Source Leadership
- •Technical Writing
- •Community Mentorship
- •DevOps Blueprints
- •Platform Engineering
- •Internal Developer Platforms (IDP)
- •Self-Service Portals & Golden Paths
- •GitOps with ArgoCD & Flux
- •AI Infrastructure & GPU Orchestration
- •LLMOps with vLLM & Ollama
- •Vector Databases (Qdrant, pgvector)
- •Generative AI & Agentic AI Systems
- •Model Context Protocol (MCP)
- •Multi-Agent Coordination (Agent2Agent)
- •LangGraph & LangChain Workflows
- •AI Product Development & Tool Calling
- •Infrastructure as Code (Terraform & OpenTofu)
- •Zero-Trust Observability (OTel, Prometheus, Loki)
- •Developer Experience (DevEx)
- •Platform Engineering & IDP
- •Enterprise DevOps & CI/CD Pipelines
- •Production Kubernetes (EKS, AKS)
- •AI Infrastructure & GPU Clusters
- •LLMOps, vLLM & Local Model Serving
- •Autonomous AI Agents & Workflows
- •Model Context Protocol (MCP) Servers
- •RAG Architectures & Vector Search
- •Full-Stack AI Application Development
- •Infrastructure as Code (Terraform, Ansible)
- •Full-Stack Telemetry (OTel, Prometheus, Grafana)
- •Open-Source Engineering & Blueprints
System Architectures / Blueprints.
Model Context Protocol (MCP) Multi-Agent Pipeline with Real-time Tool Orchestration
Production architecture for autonomous multi-agent systems using MCP servers for dynamic tool execution, contextual vector retrieval, and LLM inference.
Protocol: Agent2Agent (A2A)
Maintains agent state machines, plan-and-solve loops, and multi-agent coordination.
Execution Engine
Async Event Workers, Redis Queue
Sandboxed Python runtime, Ephemeral state
Langfuse Tracing, Step Latency
Featured Projects.
All projectsInternal Developer Platform (IDP)
Self-service platform with Backstage, ArgoCD, and Kubernetes
Kubernetes Master Reference
Production EKS/AKS cluster patterns and GitOps architecture
DevOps Monitoring in a Box
Zero-trust observability with Prometheus, Grafana, and Loki
DevOps Tools Collection
Curated developer experience tooling and golden paths
DevOps Real-Time Projects Hub
40+ production CI/CD, Terraform, and Kubernetes deployments
AWS Real-Time Deployments
Terraform IaC with multi-tier VPC, EKS, and ALB architectures
CI/CD Pipeline for AWS EKS
Automated GitHub Actions + Helm + ArgoCD release pipeline
Into the DevOps
Production architecture blueprints and interview master guide
AI Platform Engineering Handbook
GPU orchestration, Kubernetes inference, and vLLM serving
LLMOps Production Pipeline
End-to-end model serving with vLLM, Ollama, and MLflow
Vector Search & RAG Infrastructure
Low-latency retrieval with Qdrant, pgvector, and Milvus
MLOps Project Generator
Scaffolding for reproducible ML and model registry workflows
DevOps Model Context Protocol (MCP) Server
Exposing Kubernetes & cloud API tool calling to LLM agents
DevOps Incident Response Agent
Autonomous AI agent troubleshooting cluster alerts via MCP
Mainframe MCP Server
Bridging AI assistants with IBM z/OS enterprise workflows
Multi-Agent Orchestration Engine
Agent2Agent (A2A) state machines powered by LangGraph
Full-Stack Agentic AI Applications
Interactive AI web apps with Next.js AI SDK, FastAPI, and MCP
Interactive Portfolio AI Assistant
In-browser agent with semantic intent resolution & system telemetry
DevOps Project Generator CLI
Automated scaffolding generator for production platforms
Ultimate DevOps & AI Documentation Portal
Knowledge portal serving 250,000+ engineers globally
Learning Hub.
Docs Portal
DevOps, Cloud & AI documentation
Projects Hub
Hands-on real-world projects
Kubernetes Learning
Beginner → CKA
Docker to Kubernetes
Complete container journey
MLOps Generator
Production-ready MLOps templates
DevOps Generator
DevOps project scaffolding
AWS Infra Generator
AWS infrastructure templates
Monitoring in a Box
Observability stack
AI Platform Engineering
AI infrastructure resources
Agentic AI
AI Agent learning resources
MCP Learning
Model Context Protocol resources
Repositories Hub
Open-source projects