Title: Quiz 13 — Load Testing, Right-Sizing, and Performance Tuning
Course: AIINFRA 303: Capstone Project > Section: Week 13 — Load Testing, Right-Sizing, and Performance Tuning

Q: Which metric best exposes the tail-latency problems that real users actually experience?
- Average response time
- p99 latency
- Total requests sent
- Median CPU usage
A: p99 latency

Q: Reporting only the average response time from a load test is sufficient to understand user-perceived performance.
- True
- False
A: False

Q: For a streaming LLM endpoint, which two metrics does a generic "total response time" measurement hide?
- CPU and memory usage
- Time-to-first-token (TTFT) and inter-token latency
- Replica count and pod restarts
- Request count and error rate
A: Time-to-first-token (TTFT) and inter-token latency

Q: In the right-sizing method described this week, what do you commonly add to the measured normal-load p99 latency when setting an SLO?
Feedback: Sample/expected answer: About 20% headroom/margin above the measured normal-load p99

Q: During a load test, GPU utilization is measured at 35% while p99 latency is already spiking. What should you investigate first?
- Immediately provision a larger or additional GPU
- Batching/concurrency configuration, since the GPU is underused
- Switch cloud providers
- Increase the Locust wait_time to zero
A: Batching/concurrency configuration, since the GPU is underused

Q: A Locust test that sends identical requests back-to-back with zero think-time from the same machine as the server will reliably predict production performance.
- True
- False
A: False

Q: What is Locust, as used in this week's lab?
- A managed cloud load-balancing service
- A Python-scripted, greenlet-based load-testing tool with a web UI
- A GPU monitoring dashboard
- A Kubernetes autoscaler
A: A Python-scripted, greenlet-based load-testing tool with a web UI

Q: Name the alternative load-testing stack mentioned this week for OpenAI-compatible endpoints, built on k6, Grafana, and InfluxDB.
Feedback: Sample/expected answer: The "periscope" toolkit (k6 + Grafana + InfluxDB)