Pins

Cloudflare Research's writeup on Meerkat, an experimental consensus service that keeps control-plane state strongly consistent across their 330+ data centers. The interesting part is that it drops the leader entirely: instead of Raft-style leader election through timeouts, which the post argues are hard to tune on the wide-area internet and have caused availability incidents, Meerkat builds on the QuePaxa algorithm where any replica can accept writes at any time and concurrent proposals interfere constructively rather than fighting. It maintains a linearizable log split into slots, and this is the first industrial deployment of QuePaxa at global scale. Worth reading if you care about how consensus actually behaves across unpredictable wide-area links rather than in a single datacenter.

Ulrich Drepper's classic long-form guide to how modern memory hardware actually works: CPU caches, cache coherency, virtual memory, NUMA, and the concrete techniques you can use to write cache-friendly code. Dated in a few specifics but still the single best foundation for reasoning about memory performance on today's machines.

A retrospective USENIX ATC paper on how DynamoDB evolved from the original Dynamo design into a fully managed service. It's a rare, candid look at the operational lessons behind a system running at enormous scale: predictable performance, admission control, durability, and the trade-offs made to keep tail latencies flat. Good reading if you care about how distributed storage behaves in production rather than on paper.

A clear walkthrough of the Generic Cell Rate Algorithm (GCRA), the mechanism behind the leaky-bucket rate limiter. Instead of tracking a counter that has to be refilled on a timer, GCRA stores a single timestamp — the theoretical arrival time of the next conforming request — and decides admission with a bit of arithmetic. The post builds the intuition step by step and shows why this is both memory-cheap and pleasant to implement.