Why You Should Add Observability to Your Data Extraction with OpenTelemetry

TL;DR: This is a step-by-step tutorial on the quickest way to add observability to any data ingestion pipeline — whether you’re scraping or using an API. Anything that fetches data at scale has a class of failure that error handling won’t catch. Not because your error handling code is bad (it probably isn’t) but because retries that eventually succeed, queries that take 10x longer than average, and domains that silently time out — don’t throw exceptions because they’re not technically errors. And you’ll never know. The solution is actually adding proper observability. Overkill? Not at all. Because a data pipeline — any data pipeline — with network calls, retries, timeouts, and wildly variable latency across different queries and domains is a textbook distributed system. It has all the same failure modes, and so it deserves the same tooling. In this post, we’ll build a SERP pipeline on top of Bright Data’s API and instrument it with OpenTelemetry (See: Python docs), the open-source stan