The answer is the `istio_request_duration_milliseconds_bucket` metric from Cloud Monitoring. This metric is correct because it is a native histogram exported automatically by Cloud Service Mesh (Anthos Service Mesh) with Istio, providing the precise distribution of request latencies needed to build a latency SLI—for example, calculating the proportion of requests that complete within a target threshold like 200ms. On the Google Professional Cloud Developer exam, this tests your understanding that Istio’s pre-configured metrics eliminate the need for custom instrumentation; a common trap is choosing raw counter metrics like `istio_request_duration_milliseconds_count`, which lack the histogram buckets required for percentile-based SLIs. Remember that the word “bucket” is your clue—histograms bucket latencies into ranges, making them the standard data source for any latency SLI in Cloud Monitoring. A useful memory tip: “Buckets build SLIs” — if you need latency thresholds, look for the bucket metric.
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 company runs a multi-service application on GKE and wants to create a Service Level Indicator (SLI) for request latency. They have set up Cloud Service Mesh (Anthos Service Mesh) with Istio. Which metric should they use for the SLI?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
istio_request_duration_milliseconds_bucket metric from Cloud Monitoring.
Option A is correct because `istio_request_duration_milliseconds_bucket` is a native Istio metric automatically exported by Cloud Service Mesh (Anthos Service Mesh) to Cloud Monitoring. It provides a histogram of request latencies, which is the standard data source for building a latency-based SLI (e.g., the proportion of requests under a threshold). This metric is pre-configured and requires no custom instrumentation, making it the most direct and reliable choice for an SLI in this environment.
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.
✓
istio_request_duration_milliseconds_bucket metric from Cloud Monitoring.
Traces are sampled, not suitable for accurate SLI.
✗
Cloud HTTP Load Balancer latency metric.
Why it's wrong here
Covers only external requests, not internal service-to-service.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the load balancer latency metric (Option D) as the correct choice because it is a common SLI for external-facing services, but for a multi-service application inside GKE with Cloud Service Mesh, the correct metric must come from the service mesh itself to capture true request latency between services.
Detailed technical explanation
How to think about this question
Under the hood, Istio’s Envoy proxies emit the `istio_request_duration_milliseconds_bucket` metric as a Prometheus-style histogram with configurable buckets (e.g., 0.5, 1, 2, 5 seconds). In Cloud Monitoring, this metric is automatically ingested and can be used to compute the fraction of requests falling within a target latency threshold (e.g., < 200ms) using a distribution cut operation. A subtle behavior is that the metric includes all sidecar-to-sidecar traffic, so if the application uses mTLS or retries, those latencies are captured, which may affect SLI accuracy if not filtered by destination service or response code.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
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: istio_request_duration_milliseconds_bucket metric from Cloud Monitoring. — Option A is correct because `istio_request_duration_milliseconds_bucket` is a native Istio metric automatically exported by Cloud Service Mesh (Anthos Service Mesh) to Cloud Monitoring. It provides a histogram of request latencies, which is the standard data source for building a latency-based SLI (e.g., the proportion of requests under a threshold). This metric is pre-configured and requires no custom instrumentation, making it the most direct and reliable choice for an SLI in this environment.
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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Question Discussion
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