TechPrufer
Get started
GitHub
GitHub logoGitHub · Feature trail

Iterative Simplification for Availability

1 post · Jul 2024

What this trail covers

This feature thread tracks the evolution of improving system availability through iterative simplification and performance optimization. Initially, the focus was on addressing specific performance bottlenecks and removing unused code. This post details the application of tools like Datadog, Splunk, Scientist, and Flipper to identify and resolve slow database queries, optimize redirect endpoints by removing unnecessary access checks, and generally improve performance and reliability through controlled rollouts and iterative code improvements.

All GitHub trails
  1. How we improved availability through iterative simplificationThis post details specific instances of improving availability through iterative simplification. It describes optimizing a SQL query for GitHub's Command Palette by reordering joins, resulting in an 80-90% performance improvement, and further optimizing a filtering query by batching, yielding another 20-80% improvement. It also covers simplifying a redirect endpoint by removing unnecessary access checks, controlled via a Flipper feature flag, which improved P75/P99 request latency and reduced max latency. The post highlights the use of Datadog, Splunk, Scientist, and Flipper as key tools in this process.