Catch vulnerabilities early by integrating security scanning into your CI workflow.
Read more →Month: October 2024
Building Production RAG Applications with LangChain: From Document Ingestion to Conversational AI
Introduction: LangChain has emerged as the dominant framework for building production Retrieval-Augmented Generation (RAG) applications, providing abstractions for document loading, text splitting, embedding, vector storage, and retrieval chains. By late 2023, LangChain reached production maturity with improved stability, better documentation, and enterprise-ready features. After deploying LangChain-based RAG systems across multiple organizations, I’ve found that its […]
Read more →Mastering AWS EKS Deployment with Terraform: A Comprehensive Guide
Introduction: Amazon Elastic Kubernetes Service (EKS) simplifies the process of deploying, managing, and scaling containerized applications using Kubernetes on AWS. In this guide, we’ll explore how to provision an AWS EKS cluster using Terraform, an Infrastructure as Code (IaC) tool. We’ll cover essential concepts, Terraform configurations, and provide hands-on examples to help you get started […]
Read more →Tips and Tricks – Implement Trunk-Based Development with Feature Flags
Ship code continuously while controlling feature rollout with runtime flags.
Read more →Enterprise Generative AI: A Solutions Architect’s Framework for Production-Ready Systems
After two decades of building enterprise systems, I’ve witnessed numerous technology waves—from SOA to microservices, from on-premises to cloud-native. But nothing has matched the velocity and transformative potential of generative AI. The challenge isn’t whether to adopt it; it’s how to do so without creating technical debt that will haunt your organization for years. The […]
Read more →Vector Databases: Why They Matter in the Age of Generative AI
After two decades of architecting enterprise systems and spending the past year deeply immersed in Generative AI implementations, I can state with confidence that vector databases have become the cornerstone of modern AI infrastructure. If you’re building anything involving Large Language Models, semantic search, or Retrieval-Augmented Generation (RAG), understanding vector databases isn’t optional—it’s essential. This […]
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