What the nines actually mean, how to eliminate single points of failure, active-active vs active-passive redundancy, multi-region failover, and setting RPO/RTO targets that match the business, not just the architecture diagram.
Delivery guarantees, Kafka partitions and consumer groups, RabbitMQ exchanges, dead letter queues, and how to decide when async processing is the right call and when it just adds latency.
How distributed tracing actually works — span propagation, correlation IDs, sampling strategy, and how to go from 'the API feels slow' to the exact service and query causing it.
How production systems survive dependency failures — circuit breaker states, timeout strategy, bulkhead isolation, retries with jitter, and fallback design, with real Resilience4j code.
A practical guide to cache layers, invalidation strategies, cache stampede protection, and the consistency-vs-performance trade-offs that decide whether caching helps or quietly corrupts your data.
A practical walkthrough of how real-time updates actually reach a client — the TCP handshake underneath every connection, why Layer 4 load balancers exist, and a working WebSocket architecture like the one behind live location tracking.
A practical system design walkthrough for scaling a product from a single server to 1 million requests per day, covering load balancing, caching, database bottlenecks, queues, observability, and operational trade-offs.
A complete walkthrough of designing a production-ready URL shortener on AWS — covering hashing strategies, database selection, caching, and scaling to billions of redirects.