napkin math
A newsletter about using napkin math and first-principle thinking to estimate systems performance — fast, and without writing any code! However, on a good day posts will include code to test whether the napkin math lines up with reality.
A table of performance ballpark numbers:
https://github.com/sirupsen/napkin-math#numbers
The archive page is a bit difficult to parse, as it has non-napkin-math posts scattered in it.
1: logging cost
2: database query latency
3: membership intersection service
4: redis throughput
5: composite primary keys
6: in-memory search
7: revision history
8: data synchronization
9: inverted index perf and merkle tree sync
10: mysql transactions per second vs fsyncs per second
11: circuit breakers
12: recommendations
13: filtering with inverted indexes
14: using checksums to verify syncing 100m database records
15: increase HTTP performance by fitting in the initial TCP window
16: when to write a simulator
17: neural network from scratch