#architecture
29 articles tagged architecture.
System Design: Building a Notification Service for 50 Million Users
A complete system design walkthrough — from blank page to production architecture — covering fan-out, multi-channel delivery, rate limiting, retry logic, and the trade-offs engineers get wrong in interviews and production.
The Modular Monolith: The Java Architecture Most Teams Should Be Using
A practical guide to the modular monolith in Java and Spring Boot — package structure, enforced module boundaries, domain events, and the honest case for why it beats microservices for most teams.
Designing the AI Request Pipeline: 8 Layers Between User Input and Your LLM
A production architecture blueprint for every layer between a user's message and a safe, reliable LLM response — with Spring Boot code you can actually use.
Feature Flags for AI: The Deployment Pattern That Saved Us From 3 Production Disasters
Why LLM features need flags more than anything else you've ever shipped — and the four flag patterns that let us swap models, A/B test prompts, and kill broken AI features in under 60 seconds.
Event-Driven AI: How Kafka Streams Changed the Way We Run LLMs in Production
From blocking HTTP calls to async event streams — the architecture shift that halved user-visible latency, eliminated 3AM pages, and lets us process 2M AI requests a day without hitting rate limit walls.
You Can't Debug What You Can't See: Observability, Monitoring & Logging in Microservices
Most microservices teams add logging as an afterthought and call it observability. After running distributed systems at scale, here's what actually separates teams that debug in minutes from teams that debug in days.
Why Most Enterprise AI Projects Die in Production (And the 5 Patterns That Actually Survive)
I've deployed AI systems to 10,000+ enterprise users across healthcare, logistics, and financial services. The projects that failed didn't fail because of the model. They failed because of decisions made before the first line of model code was written.
Microservices Done Right: Patterns I've Learned from 12 Years of Enterprise Architecture
Real-world patterns, anti-patterns, and hard lessons from designing and delivering microservices for global enterprises — from service decomposition to event-driven architecture to the observability you'll wish you had from day one.
Why Apigee is the Missing Layer in Every Microservices Architecture
After years of building enterprise microservices at scale — from Herbalife to HCA Healthcare — here's why I believe API management isn't optional anymore, and what Apigee-X brings to the table that raw gateways simply can't.
CCA Professional Complete Study Guide: Everything You Need to Pass
A comprehensive module-by-module study guide for the Claude Certified Architect – Professional exam. All five modules, every decision table, every framework, all 12 trap patterns, the 42-term glossary, and the 15-item final checklist — in one place.
Claude Certified Architect – Professional: Complete Exam Prep Guide
A detailed preparation guide for the Anthropic CCA Professional exam — all 7 domains with weights, the master pattern behind every module, domain-by-domain breakdown, trap patterns, and a 4-phase study approach.
Spring Boot Complete Architecture Guide: From Foundation to Spring AI
A comprehensive end-to-end guide to Spring Boot architecture for experienced developers — IoC, AOP, security, data, resilience, testing, Spring AI, and production deployment — with diagrams and production-quality code throughout.
MCP vs Function Calling: What's the Difference (and When to Use Each)
Model Context Protocol and function calling both give LLMs access to tools — but they solve different problems. A clear comparison with guidance on when to use which.
Building an AI Gateway with Apigee (LLM Proxy)
Put Apigee in front of your LLM providers to centralize API keys, cost control, quotas, logging, and guardrails. A practical blueprint for an enterprise AI gateway.
What's New in Modern Java — and How to Build AI With It
Modern Java (21→25) brings virtual threads, structured concurrency, records, and the FFM API. Here's what's new and how it powers AI apps.
Spring AI: From Beginner to Expert — Course Overview
A complete Spring AI course for Java teams: setup, prompting, tool calling, RAG, MCP, choosing an LLM, and production architecture.
Claude Certified Architect (Foundations): Complete Exam Prep Course
A complete, hands-on prep course for the Claude Certified Architect — Foundations exam: the five domains, curriculum with code, and a four-week plan.
Apigee API Management: Beginner to Advanced — Course Overview
A complete Apigee course: architecture, API proxies, policies & security, environments, CI/CD, and Apigee as an AI gateway — beginner to advanced.
Zero to Production: Building Your First Enterprise LLM Application
A four-phase guide to taking an LLM prototype to a production enterprise app — RAG, caching, observability, cost control, and multi-model routing.
Building Fault-Tolerant AI Systems
Resilience patterns for production AI — circuit breakers, fallback chains, and graceful degradation so systems survive provider outages and rate limits.
RAG Systems Explained
A complete guide to Retrieval Augmented Generation — how it works, why each component matters, and how to build production-grade RAG pipelines.
Spring AI Enterprise Integration Guide
A practical guide to building enterprise-grade AI applications with Spring AI — from chat clients and RAG pipelines to production observability.
Microservices Best Practices
Enterprise-grade practices for designing, deploying, and operating microservices systems that actually scale — from domain modelling to runtime resilience.
Kafka Scalability Patterns
Practical patterns for designing highly scalable Kafka-based enterprise systems — from partition strategy to consumer group tuning.
Building Enterprise AI Agents
Architecture patterns and best practices for building production-grade AI agents that scale — from orchestration to observability.
RAG Chunking Strategies That Actually Improve Retrieval
Your RAG quality is capped by how you chunk. A practical comparison of fixed, recursive, semantic, and structural chunking, with sizing and overlap tips.
AI Gateways: Managing LLM Traffic in the Enterprise
As LLM usage spreads across an org, you need a control point. What an AI gateway is, the problems it solves, and the capabilities to look for.
Fine-tuning vs RAG vs Prompting: How to Choose
Teams reach for fine-tuning when they need RAG, or RAG when a better prompt would do. A decision framework for choosing the right approach by problem type.
Securing LLM Apps: Guardrails for Production
LLM features open new attack surfaces — prompt injection, data leakage, unsafe tool use. A practical guardrails checklist for shipping AI to production safely.