System Design
Designing systems that scale: trade-offs in architecture, storage, and reliability.
Subject: Systems & Architecture · Roles: AI Engineer, Cloud Architect, Cybersecurity Engineer, Data Architect, Data Engineer, DevOps Engineer, Identity and Access Management (IAM) Engineer, Machine Learning Engineer, Platform Engineer, Security Architect, Site Reliability Engineer, Software Engineer, Solutions Architect, Technical Product Manager
Concepts
Scalability Fundamentals
Vertical vs. horizontal scaling, and load balancing — the baseline vocabulary every other system-design topic builds on.
Caching Strategies
Storing a fast copy of expensive-to-compute or expensive-to-fetch data — write policies, eviction, and the invalidation problem.
Database Scaling (Sharding & Replication)
Splitting data across machines (sharding) and copying it across machines (replication) — solving two different scaling problems.
Message Queues & Async Processing
Decoupling a slow or unreliable step from the request path by handing it to a queue and processing it separately.
CAP Theorem & Consistency Models
Why a distributed system can't have perfect consistency, availability, and partition tolerance all at once — and what real systems trade off.