System Architecture

← Series hub ← Previous | Next → In the early phase of the AI wave (2023-2024), the default architecture for most startups and enterprises was API-Centric: routing every single request to OpenAI’s GPT-4 or Anthropic’s Claude. While highly convenient for proof-of-concept (PoC) phases, this model rapidly falls apart under production loads when encountering two massive walls: data privacy regulations and astronomical operational costs. By 2026, the rise of Small Language Models (SLMs) ranging from 2B to 14B parameters has dramatically shifted the landscape. Models such as Microsoft’s Phi-4 (14B), Qwen 2.5/3.5 Coder (7B/14B), and Llama 3 8B, when properly fine-tuned, achieve performance close to—or even exceeding—commercial frontier models on domain-specific, narrow tasks. ...

Answer-first: Complete architectural blueprint of a Go 21-service e-commerce platform. Covers domain boundaries, traffic flow, and event-driven patterns. What You’ll Learn That AI Won’t Tell You Practical latency and memory metrics comparing an Envoy-based API Gateway to a custom Go reverse proxy under 100k concurrent connections. How to tune circuit breaker thresholds (go-resiliency/breaker) to prevent premature service isolation during temporary network jitters. When transitioning from a monolithic platform to a distributed microservice setup, the hardest question isn’t “How do we write the code?” — it’s “How do these moving parts talk to each other safely, and why is each boundary drawn exactly where it is?” ...