Modelling Postgres Performance Degradation on Burstable Cloud Instances

Many developers run Postgres on "burstable" cloud instances (like Azure B-series or AWS T-series) to optimise costs. While cost-effective, these instances operate on a CPU credit model that introduces non-linear performance risks.

The danger is not a system crash, but throughput exhaustion. When CPU credits are depleted, the cloud provider throttles the CPU to its base frequency. Because Postgres is unaware of this external throttling, it continues to accept connections it can no longer process in a timely manner. This leads to a cascading failure, i.e. connection pools saturate, p99 latencies skyrocket, and the app layer eventually times out. The database will effectively be unavailable despite being "online."

In this session, I will demonstrate how to model the exact saturation point of a throttled Postgres instance. I will show you a simple simulation method to calculate your "Base Performance Ceiling" without the need for expensive load-testing infrastructure, allowing you to right-size your database before the credits run out.