Security & Threat Intelligence · 25.07.2026, 15:29 UTC
Introducing Meerkat: an experiment in global consensus
| Schweregrad | info |
|---|---|
| Kategorie | Security & Threat Intelligence |
| Quelle | Cloudflare Blog ↗ |
| Veröffentlicht | 25.07.2026 UTC |
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Many internal services at Cloudflare need to read and modify the same control-plane state from across our 330+ global data centers. They need guarantees that different readers never see inconsistent state, and that the system remains available for writes even when some data centers or links fail. But Cloudflare’s network runs across the entire Internet, and the Internet is an unpredictable place. Servers and data centers go down. Queues fill up. Links and cables get cut. These conditions make it difficult to run a globally available data system that guarantees strong consistency (e.g., that all readers are guaranteed to read all prior writes) because hostile conditions hinder distributed system replicas’ ability to reliably synchronize data with one another.One way to synchronize data safely despite adverse network conditions is via a consensus algorithm, which allows a set of machines to agree on the same sequence of values, such as key-value store put and get operations, as long as a majority remains alive and able to communicate. Unfortunately, commonly deployed consensus algorithms like Raft suffer in wide-area networks like Cloudflare’s because they rely on leaders and timeouts. The leader is the only replica allowed to make writes, and if it fails due to a crash or network degradation, the system becomes unavailable until some other replica times out and a new leader is elected. And these timeout values are hard to configure in networks with unpredictable latencies.We have experienced multiple incidents caused by unavailable leaders in consensus-driven systems.And …