Napkin Math is a technical reference project for estimating software system performance from first principles. It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as rounded numbers for reasoning rather than exact performance guarantees. The repository is especially useful for system design interviews, architecture planning, capacity estimation, and infrastructure cost discussions. It encourages engineers to practice estimation as a skill so they can reason about systems before building or benchmarking them.
Features
- First-principles performance estimation
- Latency and throughput reference numbers
- System design calculation practice
- Storage, memory, network, and CPU estimates
- Benchmark-backed engineering intuition
- Newsletter and practice problem archive