// The Problem
Real-Time Vulnerability Intelligence at Scale
Organizations struggle to stay current with 240,000+ Common Vulnerabilities and Exposures (CVEs) and need intelligent, real-time vulnerability analysis to prioritize security responses effectively.
// My Role
DevOps Engineer & Infrastructure Lead
Designed and implemented the entire production infrastructure on AWS EKS, including custom Kubernetes operators, event streaming pipelines, CI/CD automation, security hardening, and full-stack observability. Built a self-hosted RAG-based LLM system with enterprise-grade reliability and security.
// Architecture
AWS EKS Infrastructure
Production Kubernetes cluster on AWS EKS with multi-AZ deployment, auto-scaling, and Istio service mesh
System Architecture
Event-driven architecture with Kafka streaming, custom K8s operator, and PostgreSQL + Pinecone data layer
RAG Pipeline Architecture
Retrieval-Augmented Generation pipeline with LLaMA 3.1, Pinecone vector search, and LangChain integration
// Tech Stack
Infrastructure & Orchestration
CI/CD & Automation
Data Pipeline
AI/ML Stack
Security
Observability
// Key Achievements
Custom Kubernetes Operator
Developed a Go-based operator to monitor 240K+ CVEs in real-time
Event-Driven Architecture
Engineered Kafka-based streaming pipeline processing 240K+ CVE records
RAG Pipeline
Built Retrieval-Augmented Generation system with Ollama LLM and LangChain
Semantic Search
Implemented AI query system using Hugging Face embeddings
Production-Grade Security
Deployed Istio mTLS, multi-AZ architecture, and IAM encryption
CI/CD Automation
Automated pipelines with Jenkins, Helm linting, and semantic versioning
Full-Stack Observability
Integrated Prometheus + Grafana for real-time monitoring