#architecture
30 articles tagged architecture, from AI, System Design, Java Engineering. Latest: “I Rebuilt Our AI Agents on Kafka Instead of REST — Here's the Full Java Architecture”.
I Rebuilt Our AI Agents on Kafka Instead of REST — Here's the Full Java Architecture
REST between AI agents works until agent #4 shows up. The full Java/Spring Kafka topic design, the ReAct loop as a state machine, and a free audit trail.
System Design: Building a Notification Service for 50 Million Users
A complete system design walkthrough, from blank page to production architecture — fan-out, multi-channel delivery, rate limiting, and retry logic.
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, module boundaries, domain events, and why it beats microservices.
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 you've shipped — the four flag patterns that let us swap models, A/B test prompts, and kill broken features fast.
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 latency, eliminated 3AM pages, and lets us process 2M AI requests a day.
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. What 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)
Why enterprise AI projects fail in production: it is rarely the model. The failures happen earlier, in scope, data, cost control and ownership.
Microservices Done Right: Patterns I've Learned from 12 Years of Enterprise Architecture
Real-world patterns, anti-patterns, and hard lessons delivering microservices for global enterprises — from decomposition to observability done right.
Why Apigee is the Missing Layer in Every Microservices Architecture
After years building enterprise microservices and integration platforms, here is why API management isn't optional and what Apigee X brings to the table.
CCA Professional Complete Study Guide: Everything You Need to Pass
A module-by-module study guide for the CCA Professional exam — all five modules, every decision table, all 12 trap patterns, and the 15-item checklist.
Claude Certified Architect – Professional: Complete Exam Prep Guide
A detailed prep guide for the CCA Professional exam — all 7 domains with weights, the master pattern behind every module, and a 4-phase study approach.
Spring Boot Complete Architecture Guide: From Foundation to Spring AI
An end-to-end guide to Spring Boot architecture for experienced developers — IoC, AOP, security, data, resilience, testing, Spring AI, and deployment.
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 solve different problems — a clear comparison and guidance on when to use each.
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 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 7-lesson Spring AI course for Java teams: setup, prompting, tool calling, RAG, MCP, choosing a model and running AI features in production.
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 Overview
An 11-lesson Apigee course: architecture, products, proxies, security, traffic, observability, deployment, CI/CD, AI gateway and a capstone Orders API.
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.