Professional Imposter Syndrome

I’ve been shipping distributed systems for about a decade — and I still open a fresh tab to remind myself how consistent hashing works. So I write it down here: distributed systems, networking, and cryptography, explained the way I wish they’d been explained to me. I try to stay honest about what I actually understand, which is why every post carries a confidence rating. New here? Start with the CAP series →

Apr 21, 202612 mincommitted

Consistent Hashing 101

Why adding a server shouldn't ruin your entire cache.

Apr 08, 202612 mincommitted

Replication 101

Three ways to keep copies of your data, and the trade-offs of each.

Mar 31, 202615 mincommitted

How OpenAI Serves 800 Million Users Without Sharding Postgres

A look at one of the most interesting engineering decisions behind one of the largest single-primary PostgreSQL deployments in the world.

Mar 21, 20262 mincommitted

Start Here — A Guide to Professional Imposter Syndrome

New here? This is the best way to read the blog.

Mar 17, 202618 mincommittedCAP · 4/4

Beyond "Pick Two": Real-World Trade Offs

Why most systems live between CP and AP and how to choose where yours belongs.

Feb 24, 202621 mincommittedCAP · 3/4

AP Systems Explained: Stale Data Beats Dead Servers

How DynamoDB, Cassandra, and DNS stay available during network failures—and how they clean up the mess afterward.

Feb 03, 202621 mincommittedCAP · 2/4

CP Systems Explained: The Hidden Cost of Strong Consistency

Let's look at what CP systems actually do under the hood when they choose consistency over availability.

Jan 20, 202611 mincommittedCAP · 1/4

CAP Theorem Explained: Beyond the "Pick Two" Myth

Let's get to the bottom of what Consistency, Availability, and Partition Tolerance actually mean in production distributed systems.

Browse all 15 essays →Series: CAP (4) · Merkle (2)RSS