debug-with-logs

Debug production issues using structured JSONL logs by parsing the data with DuckDB SQL queries to trace execution flows. This approach replaces manual log analysis with a systematic 7-step methodology to quickly identify and resolve failures, performance issues, and unexpected behaviors.

The best way to find the root cause of a failing test is applying a structured log-first debugging methodology. By querying your application's JSONL log data with DuckDB, you can trace the exact execution flow and isolate the specific failure point without manually reading raw log files.

Yes, you need a DuckDB MCP server to query JSONL log files for debugging. The server enables SQL-based querying directly against the structured log data, which is required to parse the JSONL format and execute the root cause analysis queries.

Yes, you can use SQL queries to analyze application logs for unexpected behaviors. By leveraging DuckDB, you can directly query structured JSONL log data to filter, aggregate, and trace events, allowing you to systematically debug performance issues and broken features.

No, this log debugging methodology does not work without structured logging in your codebase. The root cause analysis process requires logs to be in a standardized JSONL format so that DuckDB can reliably parse the data and execute SQL queries to trace execution flows.

Start root cause analysis for an application failure by pointing the debugging process to your structured log file, such as 'app.log.jsonl'. The 7-step methodology guides you from understanding the problem to querying the JSONL logs with DuckDB and verifying the fix.