NCA-GENL exam dumps

NCA-GENL practice question 156 of 228

NVIDIA-Certified Associate - Generative AI LLMs. Associate level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-GENL Question 156

Select 3

You are assisting a senior team member in deploying a large language model (LLM) for a high-traffic e-commerce platform. The team wants to ensure the model performs reliably under peak traffic conditions while maintaining scalability. Which of the following steps should you prioritize during deployment and evaluation?

  1. A

    Implement load testing to simulate peak traffic scenarios and monitor model response times.

  2. B

    Deploy the model to a single low-resource server to save costs during testing.

  3. C

    Analyze system resource utilization (e.g., GPU memory, CPU usage) during test runs to identify bottlenecks.

  4. D

    Enable automatic scaling policies to dynamically allocate resources based on traffic demand.

  5. E

    Ignore latency metrics during testing as they are less relevant for model performance.

Show answer and explanation

Correct answers: A, C, D

Explanation

To ensure the LLM is scalable, performs well, and remains reliable under high traffic, it is essential to conduct load testing, monitor resource utilization for bottlenecks, and implement dynamic scaling policies. These steps collectively help assess and optimize the deployment process for real-world conditions.

  • A. Correct.

    Load testing is critical to evaluate how the model performs under peak traffic conditions. This step helps identify any performance degradation or failure points.

  • B. Incorrect.

    Deploying to a single low-resource server may save costs temporarily but would not provide an accurate representation of real-world performance under high traffic.

  • C. Correct.

    Analyzing resource utilization helps identify hardware or system bottlenecks that could affect scalability and reliability during deployment.

  • D. Correct.

    Enabling automatic scaling ensures the system can dynamically adjust resources to handle fluctuations in traffic demand, improving scalability and reliability.

  • E. Incorrect.

    Ignoring latency metrics is a poor practice as response time is a key measure of model performance, especially for real-time applications like e-commerce.

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