Interactive Capacity Estimator
Slide DAU, requests per user, payload size and read/write ratio and watch QPS, storage per year, bandwidth, shard count and cache memory recompute live — every number with the formula behind it. The napkin math interviewers expect, made interactive.
How it works
- Average QPS = DAU × requests/user ÷ 86,400 seconds in a day.
- Peak QPS = average QPS × your peak-to-average factor.
- Storage/year = write QPS × bytes/write × ~31.5M seconds × replication.
- Shard count ≈ total storage ÷ capacity per node (rounded up).
Frequently asked questions
What is back-of-the-envelope estimation in system design?
It is the quick capacity math you do early in a system-design interview to size a system: turning daily active users and per-user activity into queries per second, then into storage, bandwidth, and the number of servers, shards and cache nodes you will need. The goal is the right order of magnitude, not a precise number.
How do you calculate QPS from daily active users?
Average QPS = (DAU × requests per user per day) ÷ 86,400 seconds. Because traffic is bursty, you multiply by a peak factor (often 2–3×) to get peak QPS, which is what you actually provision for. This tool does both for you as you move the sliders.
Why multiply by a peak factor?
Traffic is never evenly spread across the day — there are busy hours and quiet hours. If you size only for the average you will fall over at peak. A peak-to-average factor of roughly 2–3× is a common starting assumption; raise it for spiky workloads like ticket on-sales.
How is yearly storage estimated?
Storage per year = writes per second × bytes per write × seconds per year (≈ 31.5 million). Multiply by your replication factor for the real footprint on disk, since each write is stored on multiple replicas for durability.