Debugging

Nicole discusses a systematic debugging process, which is applicable to various systems. The process involves understanding the symptoms, reproducing the bug, grasping the system, forming a bug location hypothesis, testing it, and ultimately fixing the bug. Key questions include when the bug started, its occurrence frequency, and related changes. Reproducing the bug is crucial, even for elusive ones. Understanding the system helps form connections between components. Hypothesizing the bug's location narrows down the search space. Testing the hypothesis is nuanced, requiring modifications and thorough validation. Fixing the bug comes after comprehensive understanding, but it may necessitate revisiting earlier stages.

Julia goes over some practical tips for debugging, including: • How to reproduce your bug • How to do so quickly • Experimenting in order to understand the bug • Checking your assumptions • Writing code to be easier to debug • Understanding error messages

Greg provides a framework for fixing even the trickiest bugs: • Always structure your investigations using hypotheses • Leverage your teammates and previous written communication • Be realistic that not every bug can be fixed

Paul recalls a challenging bug encountered at the observability tool company that required teamwork and good observability to resolve. A customer reported that a specific query was generating a timeout error, and the error message indicated a problem with Honeycomb's datastore. However, the issue was not with the database availability but with the data itself, as the same query with different time windows produced no error. After further investigation, the team found that a segment was missing from S3, which was causing the error. The article provides technical details of how Honeycomb's systems work and how the custom instrumentation helped identify the issue.