X-Ray ML Tracing Quiz

Quiz covering Troubleshooting ML

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

1. 1

   What is the primary purpose of distributed tracing in an ML pipeline?

2. 2

   In the context of X-Ray tracing for ML, what does a 'span' represent?

3. 3

   You notice that your inference service is slow, but the model inference itself is fast. Which X-Ray feature would best help you identify the bottleneck?

4. 4

   If you are debugging a production ML service and need to correlate a specific inference request to its corresponding trace, what is the best practice?

5. 5

   When implementing custom instrumentation for an ML model inference container, why might you choose to wrap the 'predict' method in a subsegment rather than just the whole function?