The document discusses the trade-offs between consistency, availability, and partition tolerance in distributed systems, as outlined by the CAP theorem. It emphasizes that achieving these attributes in a system often requires making choices that can impact latency, failure, computation, and durability. The text raises questions about the implications of these trade-offs for business decisions and communication protocols within organizations.

1. Consistency…!
Availability…!
Messages…!
& You…

2. AP!
C
theorem

3. ant
ACID Compli
Consistent
“…as if every request was executing on a single
node, responding to operations one at a time.”

4. Available
“…every request received by a non-failing node
in the system must result in a response.”

5. Partition Tolerant
“…the network will be allowed to lose arbitrarily
many messages sent from one node to another”

6. Pick Any Two!?!!
It’s complicated…

7. Consistent & Partition Tolerant
“…it is easy to achieve atomic data and partition
tolerance. The trivial system that ignores all
requests meets these requirements.”

8. Consistent & Available
“If there are no partitions, it is clearly possible to
provide atomic, available data.”

9. Available & Partition Tolerant
“If there are no consistency requirements, the
service can trivially return v0, the initial value, in
response to every request.”

10. t-Connected Consistent
2 ⋅ t message + t local

11. What has been
neglected?
 Latency
 Failure
 Computation
 Durability
 More™

12. Latency
Petite Partitions
the little deaths

13. When the available consistency exceeds the
required availability a choice must be made…

14. Raising the question, how are business
decisions made?

16. What protocols are used
to pass messages in
your organization?

18. n
H as your organizatio
chosen consistent, available
or pa rtition tolerant?

19. In any human interaction, the required
amount of communication is inversely
proportional to the level of trust…
@bhorowitz

20. Andrew Clay Shafer
@littleidea
work on stuff that matters