Why this blog exists
Most system design material fails in one of two directions. Blog posts stay at the level of boxes and arrows — “add a cache, add a queue” — without ever saying what breaks if you don’t. Papers go the other way and assume you already know why the problem is hard.
Neither helps when you’re staring at a whiteboard, or at a production incident.
So I write the version I wanted: each design worked out end to end, with the reasoning left in. Not just what the architecture is, but what the obvious approach was, exactly where it fell over, and what the fix costs you. A design you can’t defend under questioning isn’t a design you understand.
How these articles are written
Every case study follows the same shape, because that’s the shape of the actual work:
- Requirements first — scope the problem, then commit to numbers. Vague requirements produce vague designs.
- Capacity on the back of an envelope — QPS, storage, bandwidth. The arithmetic decides the architecture far more often than taste does.
- A high-level design that’s deliberately naive — the version most people would draw.
- The deep dive, where it breaks — the celebrity account that kills fan-out on write, the single inserted byte that invalidates every block hash, the ID collision that only shows up at 10,000 writes per second.
- What real systems actually shipped — with links to the papers and engineering posts, so you can check my work.
Diagrams are treated as part of the argument, not decoration. If a picture doesn’t show a mechanism you couldn’t have explained in a sentence, it doesn’t earn its place.
What’s covered
- Scaling fundamentals — how a system grows from one server to millions of users: replication, caching, CDNs, stateless tiers, sharding.
- Estimation — turning “design Twitter” into concrete storage, throughput, and memory budgets in under five minutes.
- Distributed systems core — consistent hashing, quorums and CAP in practice, vector clocks, gossip, anti-entropy.
- Building blocks — rate limiters, unique ID generation, message queues, notification pipelines.
- Full product designs — news feed, chat, search autocomplete, web crawler, video streaming, file sync.
- Interview technique — a repeatable four-step framework, time budgets, and the failure modes that sink otherwise strong candidates.
Everything is indexed in chapter order in the Complete Guide — that’s the best place to start if you’re new here.
Background
I’m a Principal Software Engineer. I’ve spent my career building and operating systems that had to keep working while they grew, which is where most of this material comes from.
Cloud & infrastructure
Containers & orchestration
Application development
Data stores
Delivery
Certifications
Get in touch
I read everything. If an explanation didn’t land, if you think I got something wrong, or if there’s a system you’d like to see taken apart — tell me. Corrections are especially welcome; several articles are better because a reader pushed back.