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Google ACE Practice Question: Ensuring Successful Operation of a Cloud Solution

You have a Cloud Run service that experiences intermittent high latency. You want to analyze the latency of specific request paths to identify bottlenecks. You enable Cloud Trace and instrument your application with OpenTelemetry. Which tool or feature should you use to view a waterfall diagram of latencies across services for a single request?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Cloud Trace Trace List and Trace Details

Cloud Trace provides distributed tracing capabilities, including waterfall diagrams that show the latency of each span in a request. Cloud Logging shows logs, not trace details. Error Reporting aggregates errors. Metrics Explorer shows aggregated metrics, not per-request traces.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Error Reporting

    Why it's wrong here

    Error Reporting is designed to aggregate application errors and exceptions into a centralized view, focusing on crash frequency, stack traces, and error grouping. It does not capture or display per-request latency breakdowns, nor does it provide waterfall diagrams of service calls. For diagnosing intermittent latency, you need trace data, not error logs, so this tool wouldn't reveal where time is spent within a request.

  • Cloud Trace Trace List and Trace Details

    Why this is correct

    Cloud Trace Trace List and Trace Details is the correct service because the Trace List displays each sampled request as a row with its overall latency, while Trace Details opens a waterfall chart that breaks the request into individual spans. In a Cloud Run service, this shows time spent in container startup, internal logic, and downstream calls, making it possible to pinpoint exactly which span causes an intermittent slowdown. The per-request, span-level granularity directly matches the need to diagnose variable performance.

  • Cloud Monitoring Metrics Explorer

    Why it's wrong here

    Cloud Monitoring Metrics Explorer is for querying aggregated time-series metrics, such as request count, p95 latency, or CPU utilization, plotted over a selected time window. It cannot show individual request traces or the internal hierarchy of spans within a single request, which is necessary to see the exact bottleneck. While it might reveal a latency spike, it will not indicate whether the delay came from a specific downstream call, so it is insufficient for request-level analysis.

  • Cloud Logging Logs Explorer

    Why it's wrong here

    The Logs Explorer lets you search through structured and unstructured log entries, filtering by resource, severity, or text, but it does not display request-level trace waterfall diagrams. Logs may contain trace IDs and individual span log entries, yet they lack the consolidated visual timeline that shows how long each step took relative to the whole request. To see a request's latency breakdown across services, you need Cloud Trace's trace visualization, not raw log entries.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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