A fleeting mayfly in the world, a single grain in the boundless sea.
The article revisits microservice design by explaining how Domain‑Driven Design determines business boundaries, why each service must own its data, how Service Mesh and unified governance handle communication, and how logs, metrics and traces provide observability for distributed systems.
The article explains how a retail company’s fragmented CRM, ERP, warehouse, logistics and store systems cause point‑to‑point integration chaos, and shows how Service‑Oriented Architecture—through stable service contracts, a service registry, ESB mediation, and BPEL orchestration—provides a loosely‑coupled, scalable solution while contrasting SOA with micro‑services.
Moving an application to cloud VMs and Docker does not automatically grant cloud‑native capabilities; this article explains the seven cloud‑native principles—service‑orientation, elasticity, observability, resilience, full automation, zero‑trust, and continuous evolution—using concrete e‑commerce scenarios, tables, and step‑by‑step guidance to show how each principle solves specific problems and how they interrelate.
An order interface that mixes parameter validation, discount calculation, stock checks, and raw SQL may work initially, but without separating presentation, business logic, data access, and data storage into distinct layers—while controlling dependencies, avoiding the sinkhole anti‑pattern, and understanding MVC—the code quickly becomes unmaintainable and hard to scale.
This article explains how enterprise architects should start from business objectives, define the four architecture domains—business, data, application, and technology—apply TOGAF’s ADM phases B/C/D, perform baseline‑to‑target gap analysis, and craft a phased migration roadmap, using a retail chain case study to illustrate common pitfalls and exam‑ready answers.
This article links the six previous days of architecture training into a complete reasoning chain, applies it to a city‑wide emergency command platform case, and walks through stakeholder analysis, quality‑attribute scenarios, architectural decisions, 4+1 view modeling, ATAM evaluation, and scoring guidance.
Before investing heavy coding effort, the article shows how to evaluate an architecture by mapping high‑priority quality‑attribute scenarios to design decisions, using utility trees and distinguishing SAAM, ATAM, and CBAM, and then identifying sensitivity points, trade‑offs, risks and non‑risks through a concrete internet‑hospital case study.
The article explains a systematic architecture design method that starts from business goals, functional requirements, quality attributes, and constraints, extracts architecture‑driving factors, applies ABSD or ADD processes, maps components and interfaces, and records decisions with clear rationale and trade‑offs, illustrated with an internet‑hospital case study.
This article introduces the five classic software architecture styles—data‑flow, call/return, data‑centric, virtual‑machine, and independent component—explaining their core mechanisms, advantages, drawbacks, real‑world examples, and a five‑step method for selecting the appropriate style in system design and exams.
The article explains why vague quality goals like "fast, stable, secure" are insufficient for architecture design and shows how to turn them into measurable quality‑attribute scenarios using six fixed elements—stimulus source, stimulus, environment, artifact, response, and response metric—illustrated with concrete healthcare system examples.
