NCA-GENL Question 151
Select 3As part of a team deploying a large language model (LLM) into production, you are tasked with evaluating its scalability, performance, and reliability. Under the guidance of a senior team member, which of the following actions would be most appropriate to ensure a successful deployment?
- A
Monitor system resource usage such as GPU memory and CPU utilization during high-load scenarios.
- B
Implement version control for the model and deployment pipeline to track changes and ensure reproducibility.
- C
Manually test the model on a few sample inputs to validate its accuracy.
- D
Run stress tests to simulate the expected workload and analyze the system's performance under peak conditions.
- E
Deploy the model directly into production without pre-deployment testing to save time.
Show answer and explanation
Correct answers: A, B, D
Explanation
In the context of evaluating scalability, performance, and reliability, it is critical to focus on system metrics (like resource usage), implement mechanisms to track changes (like version control), and simulate real-world scenarios (like stress testing). These practices ensure the model can handle production workloads reliably and efficiently. Manual testing or skipping testing altogether does not adequately address these concerns.
- A. Correct.
Monitoring system resource usage is essential to assess the scalability and performance of the model under various load conditions. This helps identify potential bottlenecks or resource limitations.
- B. Correct.
Version control ensures that changes to the model or pipeline are tracked, enabling reproducibility and easier debugging in case of issues. It is a critical part of reliable deployments.
- C. Incorrect.
While manual testing can provide some insight into model accuracy, it is not sufficient to evaluate scalability, performance, or reliability in a production environment.
- D. Correct.
Stress testing simulates high-load scenarios, providing valuable information about the system's ability to handle peak loads. This is crucial for ensuring reliability and scalability.
- E. Incorrect.
Deploying a model directly into production without testing is a risky practice that can lead to system failures or poor user experiences. Pre-deployment testing is critical for ensuring reliability.