Question 136 of 500
Managing application performance monitoringhardMultiple SelectObjective-mapped

Quick Answer

The correct answer involves deploying the OpenTelemetry Collector as a sidecar or external service and configuring it to export metrics to Cloud Monitoring using the Cloud Monitoring exporter, along with creating a custom distribution metric to enable percentile calculations. This is necessary because standard Cloud Run metrics only provide aggregated latency data, not the histogram-based distribution required to compute the 99th percentile. By using a custom distribution metric, the OpenTelemetry Collector captures the full distribution of request latencies, allowing Cloud Monitoring to calculate precise percentiles for alerting. On the Google Professional Cloud Developer exam, this scenario tests your understanding of how OpenTelemetry integrates with Cloud Monitoring for serverless workloads, and a common trap is assuming that default Cloud Run metrics can support percentile-based alerts. Remember the key pairing: distribution metric for percentile calculations plus the Cloud Monitoring exporter for data delivery. A useful memory tip is “Distro for Percentile, Exporter for Pipeline”—you need both the distribution metric type and the correct exporter to bridge OpenTelemetry to Cloud Monitoring.

PCD Managing application performance monitoring Practice Question

This PCD practice question tests your understanding of managing application performance monitoring. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A DevOps team wants to set up custom metrics for a serverless application running on Cloud Run. The application emits metrics using OpenTelemetry. They need to collect these metrics and create an alerting policy that triggers when the 99th percentile latency exceeds 500ms for 5 minutes. Which TWO actions must they take? (Choose two.)

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

Create a custom distribution metric for the latency data and set up a metric threshold alert using the 99th percentile value.

Option A is correct because to alert on the 99th percentile of latency, you must create a custom distribution metric, which stores a histogram of values and allows percentile calculations. A metric-threshold alert policy can then be configured to evaluate the 99th percentile value against the 500ms threshold over a 5-minute window.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

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

  • Create a custom distribution metric for the latency data and set up a metric threshold alert using the 99th percentile value.

    Why this is correct

    Distribution metrics support percentile calculations in alert policies.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Deploy the OpenTelemetry Collector as a sidecar or external service and configure it to export metrics to Cloud Monitoring using the Cloud Monitoring exporter.

    Why this is correct

    The OpenTelemetry Collector can export to Cloud Monitoring.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Install the Cloud Monitoring agent on the Cloud Run instance to collect custom metrics.

    Why it's wrong here

    Cloud Run is serverless; you cannot install an agent.

  • Define a log-based metric from the application logs that captures latency entries.

    Why it's wrong here

    Log-based metrics are for logs, not for custom OpenTelemetry metrics.

  • Configure the Cloud Monitoring dashboard to query the metrics using PromQL.

    Why it's wrong here

    Cloud Monitoring uses MQL, not PromQL.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the misconception that log-based metrics can replace custom distribution metrics for percentile alerts, but logs lack the histogram structure required for precise percentile calculations.

Detailed technical explanation

How to think about this question

OpenTelemetry metrics are typically exported via OTLP (OpenTelemetry Protocol). The OpenTelemetry Collector, when configured with the Google Cloud Monitoring exporter, can receive OTLP data and directly write distribution metrics to Cloud Monitoring's custom metric API. This preserves the histogram buckets, enabling accurate percentile computation without sampling or approximation.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PCD question test?

Managing application performance monitoring — This question tests Managing application performance monitoring — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Create a custom distribution metric for the latency data and set up a metric threshold alert using the 99th percentile value. — Option A is correct because to alert on the 99th percentile of latency, you must create a custom distribution metric, which stores a histogram of values and allows percentile calculations. A metric-threshold alert policy can then be configured to evaluate the 99th percentile value against the 500ms threshold over a 5-minute window.

What should I do if I get this PCD question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 11, 2026

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