The article discusses the challenges data engineers face with existing analytics tools, which often fail to ensure behavioral integrity amid product updates. Traditional observability tools like Datadog and Sentry focus on system errors but neglect tracking issues. The author describes the development of a behavioral analytics debugger to enhance visibility, allowing for tracing event drift and validating tracking logic. This tool aims to solve problems stemming from behavioral blindness, ensuring alignment between expectations and actual tracking metrics.
Every team has one. A dashboard that "mostly works." An adoption chart that spikes when someone coughs on the tracking plan. A funnel that's technically complete, just not accurate, recent, or reproducible.
We had observability tools. Logs, metrics, dashboards. But they weren't built for this. Our issue wasn't pipeline failure, it was behavioral blindness.
The problem wasn't the data pipeline. It was that no one, including me, could easily verify if what we were tracking was what we thought we were tracking.
My goal was to build something quick, internal, and brutal in its clarity.
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