The Quest to Understand Metric Movements
Article Summary
Your key metric just tanked 20%. Was it a code change? An OS update? A data pipeline bug? Pinterest built a platform to answer this question at scale.
Pinterest's engineering team shares how they built a root-cause analysis (RCA) platform to diagnose metric movements across their system. The platform combines three complementary approaches to narrow down why metrics shift, from performance regressions to engagement drops.
Key Takeaways
- Slice and Dice: Tree-based segmentation inspired by LinkedIn's ThirdEye algorithm
- General Similarity: Four correlation factors to find metrics moving together
- Experiment Effects: Reverse A/B testing across 2,000+ metrics dynamically
- Discovered link between content shifts and latency via statistical signals
Critical Insight
Pinterest's RCA platform combines dimensional analysis, correlation detection, and experiment impact analysis to systematically diagnose metric movements across thousands of metrics.
