This is part 2 of our three-part series where we make sense of the alphabet soup of acronyms for database consistency models.
In this episode of Mobycast, we learn how the explosion of the Internet created new challenges for strongly consistent systems, leading to the "discovery" of the CAP theorem. The CAP theorem reminds us that as systems scale, errors will become more likely, forcing us to choose our priorities.
We also learn what Chris shares in common with Eric Brewer, the creator of the CAP theorem. It's a roller coaster ride that comes to a crashing halt.
- In this new series, we are discussing database consistency models explained in three acts. This episode is "Act II: The arrival of the Internet creates new challenges (circa 1998)".
- Problems with building large scale-out systems led to the "discovery" of the CAP theorem (by Eric Brewer of Inktomi). We explain what the CAP theorem postulates and break it down in understandable terms.
- The three properties of the CAP theorem are consistency, availability and partition tolerance. What exactly is meant by "partition tolerance"?
- A key implication of the CAP theorem is that must choose your priorities. As a system scales, it cannot be both available and consistent.
- We discuss Physalia, a technology developed by AWS for making Elastic Block Service (EBS) more resilient. The design of Physalia was inspired by the principles of the CAP theorem.
- We then take a personal story detour that is (mostly) related to the CAP theorem. It turns out, Eric Brewer and Chris share a common experience during the first Internet bubble.
What is Mobycast?
A Podcast About Cloud Native Software Development, AWS, and Distributed Systems