Topic
Microservices
Learn Microservices as a connected topic across chapters, concepts, simulations, and interview reasoning.
10 Concepts12 Articles4h
Overview
Learn Microservices as a connected topic across chapters, concepts, simulations, and interview reasoning.
How this topic helps
Architecture
System Design
Distributed Systems
#cqrs
Learning Path in this Topic
Series that contain articles from Microservices. Select a path to filter the article list.
Articles
12 matched articles
Article 1Microservices Architecture: Decomposition, Communication, and Trade-offsTLDR: Microservices let teams deploy and scale services independently — but every service boundary you draw costs you a network hop, a consistency challenge, and an operational burden. The architectur22 minArticle 2Microservices Data Patterns: Saga, Transactional Outbox, CQRS, and Event SourcingTLDR: Microservices get risky when teams distribute writes without defining how business invariants survive network delays, retries, and partial failures. Patterns like transactional outbox, saga, CQR14 minArticle 3System Design HLD Example: API Gateway for MicroservicesTLDR: An API Gateway centralizes "cross-cutting concerns" like authentication, rate limiting, and routing at the edge of your infrastructure. The architectural crux is the separation of the Control Pl16 minArticle 4Service Mesh Pattern: Control Plane, Data Plane, and Zero-Trust TrafficTLDR: A service mesh intercepts all service-to-service traffic via injected Envoy sidecar proxies, letting a platform team enforce mTLS, retries, timeouts, and circuit breaking centrally — without cha15 minArticle 5Saga Pattern: Coordinating Distributed Transactions with CompensationTLDR: A Saga replaces fragile distributed 2PC with a sequence of local transactions, each backed by an explicit compensating transaction. Use orchestration when workflow control needs a single brain; 15 minArticle 6CQRS Pattern: Separating Write Models from Query Models at ScaleTLDR: CQRS works when read and write workloads diverge, but only with explicit freshness budgets and projection reliability. The hard part is not separating models — it is operating lag, replay, and r16 minPage 1 of 2