Engineering researcher. APIs, databases, infrastructure, systems design.
Most container health checks confuse three different questions into one endpoint, and the result is restarts during initialization, traffic to unready instances, and outages caused by the health check itself. The three-probe pattern fixes this.
Most API documentation is written for the wrong audience. Customers do not read sequentially. They scan for the four sections that answer their actual questions. The patterns that produce docs developers use and the discipline that keeps them from rotting.
The pulley does not invent itself. The chronology from rope-on-a-tree-branch to compound block-and-tackle spans 3000 years, and the most consequential invention in the lineage came in 1853 when a man stood on a platform in New York and cut the rope holding it up.
The default pool size in most ORMs is wrong for your workload. Little's Law gives you the right answer, the metrics that confirm it, and the failure modes that come from getting it wrong in either direction.
Application-layer tenant isolation works until somebody forgets a WHERE clause. Row-level security moves the enforcement to the database, where it cannot be bypassed by accident. The patterns that make it work and the costs that come with it.
Modern cities depend on a quiet network of pipes that almost nobody thinks about. The history of those pipes is older than most countries and includes some of the more consequential public health innovations in human history.
A test mode that customers do not trust is worse than no test mode at all. The patterns that produce a sandbox developers actually use, and the anti-patterns that produce one they tolerate while wishing they could skip.
Postgres autovacuum defaults are tuned for tables with predictable update rates and modest sizes. Production tables almost never match those assumptions. The parameters that matter and how to tune them per-table.
HTTP/2 and HTTP/3 are deployed everywhere but most teams treat them as transparent infrastructure. They are not. The configuration choices that matter and the assumptions from the HTTP/1.1 era that break.
Disk-level encryption protects data at rest from physical theft. TLS protects it in transit. Neither protects sensitive fields from the queries you accidentally write or from compromised application code. Field-level encryption fills the gap, with patterns and costs that matter.
A cache works perfectly until the moment it does not, and the moment of failure is rarely graceful. When a popular cache entry expires under load, thousands of requests can hit the origin simultaneously. The patterns that prevent the outage.
Window functions were added to standard SQL in 2003 and to most production databases by 2010, yet many engineers still write running totals and ranked-by-group queries as nested subqueries. The patterns that should be in every backend developer's toolbox.