Consensus algorithms at scale: Part 3 - Use cases

The concept of consensus systems is explored, with a focus on durability as the primary reason for using such systems. The original properties of a consensus system are modified to make them more practical and usable in real-world scenarios. A new set of rules is introduced that are agnostic of durability requirements, allowing for flexibility in deploying nodes and making durability decisions. Various use cases are presented, including large numbers of replicas spread across multiple data centers, four zones with one node in each zone, and six nodes spread over three zones. The configurations in these scenarios are uncomfortable for traditional majority-based consensus systems but allow for creative combinations that achieve better trade-offs. A way to reason about flexibility is proposed, which involves a common view shared by the Request and Election algorithms. The Worst Case Scenario highlights the potential for stall or loss of data if two nodes fail without being known, leading to compromise and mitigation strategies. Practical Balance emphasizes the low likelihood of certain failure modes, such as a replica node failing after an acknowledgment, and orders of magnitude are discussed in terms of request completion versus leader election frequency.

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