System Design
What to do when one machine is no longer enough Every system starts simple enough to run on a single computer. Then it grows, more users, more data, more requests, and that one machine begins to strain. Scaling is the craft of handling that growth, and once you commit to
System Design
Keep the popular stuff close, and everything feels fast Caching is the single most common trick for making a slow system fast, and the idea is something you already do every day. You keep the things you use most within arm's reach: the coffee mug on your desk,
TPM Knowledge
Make every dependency explicit, tracked, and owned Unmanaged dependencies are the number-one cause of preventable program slips. Not technical complexity, not headcount, not changing requirements. Dependencies. And here is the frustrating part: they are also the most predictable risk in any large program. A dependency that slips rarely surprises
System Design
Where your files actually sit, and why the cloud bill is usually a storage bill Databases hold the structured records, the accounts, the orders, the messages. But a huge share of what a system keeps is not records at all. It is files: photos, videos, backups, log files, documents, machine-
System Design
Where your app's memory lives, and why this one choice shapes everything for years Every app remembers things: your account, your messages, your orders, your photos. All of that memory lives in a database. It is the most important box in almost every system diagram, and the choice
System Design
How a click crosses the world and comes back, and why "the app is slow" is usually a traffic problem When you tap a link, it feels instant. Behind that tap, your request finds an address, opens a connection, crosses the planet, gets handled, and comes all the
System Design
How software talks to software, from the first request to a payment that never double-charges Almost nothing you use is a single program. Your banking app is dozens of programs. So is your ride app, your email, the website you bought coffee filters from last night. They are built
TPM Knowledge
Centralize the information, decentralize the work When I joined the a major tech company in 2022, reliability worked the way it does at a lot of places that copied the early Google model: a large site reliability engineering organization, with SREs embedded across every product. The split was simple on
TPM Knowledge
You have no authority over them. Trust is the only currency you actually have. A technical program manager runs work through people who do not report to them. No one on the engineering teams has to do what I ask. They have their own managers, their own roadmaps, their own