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Answer: Configure Cloud Trace to capture the requests from the load testing clients. Review the timings in Cloud Trace.
Cloud Trace is Google's native distributed tracing system designed to help identify latency issues in applications. When load testing a Cloud Run application with microservices, configuring Cloud Trace allows capturing detailed timing data for each request as it flows through the services. This provides a clear view of where bottlenecks occur (e.g., slow database calls or service delays). Option B aligns with Google's recommendation for tracing and latency analysis. Other options involve custom code changes (A, D) or less direct monitoring tools (C), making them less optimal compared to Cloud Trace's purpose-built capabilities.
Author: LeetQuiz Editorial Team
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You are building a discussion portal deployed on Cloud Run. External requests are routed through multiple microservices, some of which interact with databases, before returning a response. To identify potential bottlenecks under load, you plan to conduct a load test while adhering to Google's recommended best practices. What steps should you take?
(Note: The original question was already clear, but this version improves flow and conciseness while preserving technical accuracy.)
A
Modify the response to include a time series that shows elapsed time per service. Use Log Analytics in Cloud Logging to create a heatmap that exposes any service that could be a bottleneck.
B
Configure Cloud Trace to capture the requests from the load testing clients. Review the timings in Cloud Trace.
C
Expose the latency metrics per service for each request. Configure Google Cloud Managed Service for Prometheus, and use it to scrape and analyze the metrics.
D
Add log statements that capture elapsed time. Analyze the logs and metrics by using BigQuery.
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