Data systems at scaleCHAPTER 10
PART C / Data systems at scale
Step 153 of 252
CHAPTER 10GUIDED READING

Data systems at scale

Reason about caches, replication, partitioning, streams, and coordination.

Add capacity without losing the meaning of the data

Two hundred readers miss the same cache entry. A replica has yesterday’s version. A single tenant overwhelms one partition while the fleet average remains low. Each case requires a different boundary and a different measurement.

Start with the cache and consistency models, then study projections, partition skew, and the larger design briefs. State coordination scope, freshness, and write authority. Local examples demonstrate protocols, while AWS adapters and real capacity measurements remain explicit deployment work.

CHOOSE YOUR NEXT LESSON

Parts group related chapters. Each lesson has a chapter.lesson address, such as 4.07. Open a title below, or use Next to follow the reading sequence. Within a lesson, On this page lists its sections.

  1. 10.01
  2. 10.02
  3. 10.03
  4. 10.04

    Expiring key-value store

    Concepts and examples

  5. 10.05
  6. 10.06
  7. 10.07
  8. 10.08
  9. 10.09
  10. 10.10
  11. 10.11
  12. 10.12
  13. 10.13
  14. 10.14
  15. 10.15
  16. 10.16
  17. 10.17
  18. 10.18
  19. 10.19
  20. 10.20

    Stage 3: Add durable jobs and bounded caching

    Projects and practical assessment