Architecture Styles and Patterns: A Practical Guide
Compare layered, hexagonal, event-driven, and service architectures using boundaries, deployment needs, failure modes, and a concrete selection method.
Posts tagged with #system-design
Layered Architecture: A Guide to Responsibility Tiers
Learn layered architecture's responsibility tiers, dependency rules, code examples, and trade-offs for separating presentation, domain, and infrastructure.
Quality Attributes and Architecture Trade-offs
Turn goals like reliability, security, and performance into measurable scenarios, then compare architectural choices with explicit costs and constraints.
Network Performance: Latency, Throughput, Jitter & Loss
Understand bandwidth, throughput, latency, RTT, jitter, and packet loss with practical measurements, tail percentiles, and production diagnostic guidance.
Cache Stampede Prevention: Protecting Your Cache
Learn how single-flight, request coalescing, and probabilistic early expiration prevent cache stampedes that can overwhelm your database.
Distributed Systems Primer: Key Concepts for Modern Architecture
A practical introduction to distributed systems fundamentals. Learn about failure modes, replication strategies, consensus algorithms, and the core challenges of building distributed software.
The Eight Fallacies of Distributed Computing
Explore the classic assumptions developers make about networked systems that lead to failures. Learn how to avoid these pitfalls in distributed architecture.
Gossip Protocol: Scalable State Propagation
Learn how gossip protocols enable scalable state sharing in distributed systems. Covers epidemic broadcast, anti-entropy, SWIM failure detection, and real-world applications like Cassandra and Consul.
Microservices vs Monolith: Choosing the Right Architecture
Understand the fundamental differences between monolithic and microservices architectures, their trade-offs, and how to decide which approach fits your project.
Database Design Roadmap: From Schema Basics to Distributed Data Architecture
A practical learning path covering relational modeling, NoSQL patterns, indexing strategies, query optimization, and distributed data systems — everything you need to design databases that actually hold up under production load.