Kqr Row Cache Contention Check Gets May 2026

From that day on, KQR’s monitoring dashboard had a new rule: If row cache contention check gets > 1000 per second — flip on single-flight mode. And the team learned a valuable lesson: sometimes, the most dangerous lock isn’t in your database — it’s in your cache’s eagerness to help .

def get(key): if key in cache: return cache[key] else: value = db.query("SELECT * FROM items WHERE id = ?", key) // slow cache[key] = value return value Because the cache was empty, all 10,000 threads saw a at the exact same moment. They all rushed to the database.

She hot-patched KQR’s logic to use :

, the on-call engineer, saw the alert: kqr row cache contention check gets = CRITICAL She’d seen this before. It wasn’t a database problem — it was a thundering herd problem.

But they didn’t just rush to the database — they collided at the . You see, KQR’s cache was protected by a single, global synchronized block for writes. kqr row cache contention check gets

In the bustling data center of the e-commerce platform, there lived a tired but loyal piece of infrastructure: a PostgreSQL database named KQR (Key-Query-Resolver).

KQR’s cache logic looked like this (pseudocode): From that day on, KQR’s monitoring dashboard had

KQR> ROW CACHE CONTENTION CHECK GETS It printed: