Most Python applications log like this: logger . info ( f " Processing order { order_id } for user { user_id } " ) logger . error ( f " Payment failed for order { order_id } : { str ( e ) } " ) Enter fullscreen mode Exit fullscreen mode It works fine in development. In production, it falls apart. When you're debugging a latency spike at 2am, grep-ing through gigabytes of unstructured log strings is painful. When you want to correlate a log line with the trace that generated it, you can't — the trace ID isn't in the log. When you want to count how many payment failures happened for a specific product in the last hour, you can't — the data is buried in a string. Structured logging fixes all of this. Instead of log strings, you emit log events — dictionaries of key-value pairs that your log aggregator can index, query, and alert on.…