CENTRAL UNIVERSITY
LectureCAP, PACELC and Consistency Models
A story about real trade-offs in distributed systems
/ CAP, PACELC and Consistency Models · Central University
Slide contents
1. CAP, PACELC and Consistency Models
A story about real trade-offs in distributed systems
2. Lecture Map
3. CAP Theorem in One Phrase
4. C, A, and P: What's Inside
5. Consistency in CAP = Linearizability
6. Availability in the Theorem
7. How CAP Emerged
8. The 'Pick 2 of 3' Myth
9. Partitions: Rare, Not Exotic
10. Decisions Are Made Per Operation
11. C/A/P Are Spectrums
12. Partition Mode as State Machine
13. Latency Governs CAP
14. ACID vs CAP: Different C
15. BASE Answers Availability
16. Gilbert–Lynch Formal Definitions
17. Asynchronous Impossibility
18. Partial Synchrony Doesn't Help
19. CAP Takeaways for Architecture
20. CAP: What to Do in Failure
21. PACELC Formula
22. Why PACELC Was Needed
23. Latency vs Consistency in Normal Mode
24. PACELC Categories
25. PA/EL: Speed and Availability First
26. PC/EC: Consistency First
27. PA/EC: Reliable and Strict
28. PC/EL: Rare but Important Profile
29. Map PACELC to Product Needs
30. Calculate Latency/Consistency Budget
31. What PACELC Adds to CAP
32. Jepsen: Stress-Testing Distributed Systems
33. Why Architects Read Jepsen
34. Jepsen's Five-Step Cycle
35. Jepsen Failure Models
36. Typical Jepsen Findings
37. Jepsen Model Map: Two Branches, One Apex
38. Serializable vs Linearizable
39. Choose a Model for Product
40. Overall Framework: CAP + PACELC + Jepsen
41. Cassandra Through CAP/PACELC
42. Cassandra Tunable Consistency
43. How Cassandra Maintains Scale and Availability
44. References and Materials
CAP: https://system-design.space/chapter/cap-theorem
PACELC: https://system-design.space/chapter/pacelc-theorem
Consistency Models (Jepsen): https://system-design.space/chapter/jepsen-consistency
Cassandra: https://system-design.space/chapter/cassandra
All 4 source chapters from system-design.space in one place.