Postmortem: Six-Hour Outage

Concepts covered: paPostmortem, paFailureDiscipline

The patterns become real when read against an actual incident. The postmortem below describes a real outage at a mid-size streaming company, with details lightly altered. The pipeline ingested clickstream events into a clickhouse cluster for product analytics. A configuration drift in one pipeline node caused a six-hour outage in which dashboards across the company showed empty graphs. The postmortem is structured the way Google's SRE book recommends: facts, timeline, root cause, contributing factors, action items. Reading the section end to end demonstrates how every pattern from the prior lessons either prevented or could have prevented part of the outage. The Pipeline Before the Incident Timeline Root Cause The single root cause of the outage was the Geo-IP config change. Everything dow

About This Interactive Section

This section is part of the Failure Modes and Error Handling: Advanced lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.