Volume 3: The Modern Frontier: Scale, Intelligence, and What Comes Next1/10
Chapter 01 of 10
Systems at Scale 201-210
10 lessons51 min readingParts 201-210
- 01Finding the Real BottleneckWhen a system slows down, how do engineers know what to improve?5 min read5 min read
- 02Vertical and Horizontal Scaling RevisitedWhat deeper trade-offs appear when capacity grows?6 min read6 min read
- 03Database ReplicationHow can several database copies improve availability and read capacity?5 min read5 min read
- 04Database ShardingHow can a dataset be divided when one database cannot hold or serve it efficiently?5 min read5 min read
- 05Consistent HashingHow can distributed caches or stores add nodes without moving nearly every key?5 min read5 min read
- 06Leader ElectionHow do distributed nodes agree on which one coordinates shared work?5 min read5 min read
- 07ConsensusHow can several machines agree despite failures and delayed messages?5 min read5 min read
- 08QuorumsWhy do distributed systems often require responses from a majority?5 min read5 min read
- 09BackpressureWhat should a system do when work arrives faster than it can be processed?5 min read5 min read
- 10Graceful DegradationHow can a product remain partly useful during component failures?5 min read5 min read