Distributed Systems Series — Part 5.12: Scalability & Performance The End of the Beginning This is the forty-third and final post in a series that began with a simple question: what does it mean to build distributed systems correctly? Not just systems that work in development, not just systems that pass their tests, but systems … Read more
Distributed Systems Series — Part 5.11: Scalability & Performance Why Synchronous Communication Does Not Scale Every communication pattern covered in Post 2.1 falls into one of two categories: synchronous (the producer waits for the consumer to respond before proceeding) or asynchronous (the producer sends a message and continues immediately without waiting). Synchronous communication is the … Read more
Distributed Systems Series — Part 5.10: Scalability & Performance Scalability Without Cost Awareness Is Not Sustainable Every scalability mechanism in Part 5 — partitioning, load balancing, caching, autoscaling, geo-distribution — has a cost. Partitioning requires running multiple database nodes rather than one. Load balancers add infrastructure. Caches require memory. Autoscaling provisions capacity that may not … Read more
Distributed Systems Series — Part 5.9: Scalability & Performance When Single-Region Is No Longer Sufficient Every scalability mechanism covered so far in Part 5 — partitioning, load balancing, caching, backpressure, indexing, autoscaling — operates within a single geographic region. These mechanisms collectively allow a system to handle enormous load within one region. But they cannot … Read more
Distributed Systems Series — Part 5.8: Scalability & Performance Why Manual Scaling Fails at Production Scale Post 5.1 established that horizontal scaling — adding instances to handle growing load — is the foundation of distributed systems scalability. Posts 5.3 through 5.7 covered the mechanisms that make horizontal scaling possible: partitioning, load balancing, caching, backpressure, and … Read more
Distributed Systems Series — Part 5.7: Scalability & Performance Why Indexing Is a Scalability Problem, Not Just a Database Problem Post 5.3 established that partitioning distributes data across nodes so that each node owns a subset of the key space. Partitioning solves the write scalability problem — ten shards means ten independent write paths. But … Read more