Worked on the apple/axlearn repository to enhance observability and performance safety by developing a configurable goodput monitoring flag within the GoodputRecorder class. This feature, implemented in Python, allows goodput monitoring to be toggled on or off, defaulting to disabled to prevent performance regressions. The technical approach involved updating the class constructor, refining flag parsing logic, and creating comprehensive unit tests to ensure backward compatibility and validate new behavior. Emphasizing backend development and configuration management, the work provided a safe, low-overhead mechanism for performance tuning, with clear traceability through CI-visible changes and end-to-end validation of the new monitoring capability.