GES-C01 Exam Dumps | A data engineer is reviewing the purpose of AI Observability's tracing feature within Snowflake Cortex.

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Question 10/171

A data engineer is reviewing the purpose of AI Observability's tracing feature within Snowflake Cortex. Which of the following statements accurately describe the benefits or functionality of tracing in this context?

A. Tracing records only the final output of an LLM inference call, not the intermediate steps.

B. It allows debugging individual records by showing every step of application executions, including input prompts, retrieved context, and tool use.

C. Tracing primarily focuses on aggregating performance metrics like accuracy and latency across multiple application runs for comparison, rather than step-by-step execution details.

D. It enables refinement of the application for improved accuracy, latency, and cost.

E. Tracing requires manual logging of each application step through custom SQL INSERT statements into an event table.

Correct Answer: B,D

Tracing, as a feature of AI Observability, is designed to 'trace every step of application executions across input prompts, retrieved context, tool use, and LLM inference'. This detailed visibility is used to 'debug individual records and refine the app for accuracy, latency, and cost'. Option A is incorrect because tracing captures all steps, not just the final output. Option C describes 'Evaluations' and 'Comparison', which are separate features of AI Observability, though related to performance measurement. Option E is incorrect because the TruLens SDK is used for instrumentation to generate traces, and Cortex Analyst logs requests to an event table automatically.

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