AI & LLM Systems
Architecture for machine learning, generative AI, and large language model systems.
Browse articles by system design area.
Architecture for machine learning, generative AI, and large language model systems.
API design, service communication, protocols, and integration contracts.
Reusable architectural approaches for structuring software systems.
Caching strategies, invalidation, and performance-oriented data access.
Cloud platforms, infrastructure design, and deployment foundations.
Data modeling, persistence engines, indexing, and data platform trade-offs.
Coordination, consistency, and failure handling across distributed services.
Queues, event streams, brokers, and asynchronous processing.
Monitoring, logging, tracing, alerting, and production diagnostics.
Capacity planning, latency reduction, and scaling techniques.
Fault tolerance, graceful degradation, recovery, and dependable system operation.
Identity, access control, threat modeling, and secure system architecture.
Practical system design analyses and lessons from real implementations.
Core system design concepts and foundational engineering principles.
Interview frameworks, exercises, and techniques for communicating design decisions.