Introduction
Every engineering team has been there. A product manager says the search results are "off." Users are complaining. Someone suggests tweaking the field boost or adding a synonym. And then someone else says, "That requires a code change, a PR review, and a deployment."
What if it didn't? What if search tuning was a configuration change, not a code change? What if you could experiment with different search strategies, compare them side-by-side, and deploy the winner without touching a single line of production code?
This is exactly what the OpenSearch Search Relevance plugin enables through its search configuration management system. In this post, I will show you how to treat search as a configurable layer, how to version and test configurations safely, and how to move from guesswork to data-driven search tuning.
The Problem: Search Tuning Is Too Slow
