Expanding the CAP tradeoff frontier at scale

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Distributed systems must balance their needs for high availability and low latency with consistency guarantees; providing a mostly hit happy path for requests enables these systems to push the boundaries of this tradeoff. By Audrey Cheng.

At scale, there are three particular concerns a distributed system must address when providing a mostly hit happy path:

  • Performance isolation by ensuring that clients do not affect each other
  • Hotspot tolerance so that hot keys do not affect availability
  • Bounding the worst-case since tail latency can slow overall user interaction. We provide examples below on how the three systems tackle these issues

Given challenging, real-world workloads, any performance degradation resulting from enforcing stronger consistency guarantees for one client should not affect others. Insulating performance effects is also crucial to protecting against misbehaving users.

Ultimately, finding the right balance between availability / latency and consistency depends on application needs. To push the limits of what can be achieved in this tradeoff, distributed systems should identify and leverage local information to provide a mostly hit happy path for requests. This approach can be especially impactful at global scale. Nice one!

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Tags database big-data data-science performance devops