The correct approach is to implement a custom sampler in your application code using the OpenTelemetry SDK, which allows you to sample a specific endpoint at 100% while keeping the default rate for others. This works because Cloud Trace’s sampling decision is made per-request by a sampler interface; by writing a custom sampler that inspects the request path—for example, checking if the route matches your high-traffic endpoint—you can return a sampling probability of 1.0 for that endpoint and delegate all other requests to the default sampler (e.g., 0.1). On the Google Professional Cloud Developer exam, this tests your understanding of fine-grained trace configuration in distributed systems, often appearing as a scenario where a team needs targeted observability without overwhelming the tracing backend. A common trap is assuming you can set this via environment variables or GKE annotations alone, but the key is that custom sampling logic must live in the code. Memory tip: think “path-check, then override”—your sampler checks the route first, then decides the rate.
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 development team is using Cloud Trace to analyze performance bottlenecks in a Node.js application deployed on GKE. They have enabled trace sampling at 10% and can see some traces, but many requests are not captured. They want to increase the sampling rate to 100% for a specific high-traffic endpoint while keeping the default sampling rate for other endpoints. How can they achieve this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement a custom sampler in the application code to sample the specific endpoint at 100%.
Option C is correct because Cloud Trace allows you to implement a custom sampler in your application code to override the default sampling rate for specific endpoints. By using the OpenTelemetry SDK, you can create a sampler that checks the request path and returns a sampling decision of 1.0 (100%) for the high-traffic endpoint while delegating to the default sampler (e.g., 0.1) for all other requests. This gives you fine-grained control without affecting the global sampling configuration.
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.
✗
Use a separate trace exporter for the high-traffic endpoint.
Why it's wrong here
Multiple exporters are not a standard approach and cannot selectively sample within the same application.
✗
Increase the quota for trace spans per request.
Why it's wrong here
Quota does not control sampling rate; it limits total spans.
✓
Implement a custom sampler in the application code to sample the specific endpoint at 100%.
Why this is correct
A custom sampler allows per-endpoint sampling rates as needed.
Related concept
Read the scenario before looking for a memorised answer.
✗
Set the global trace sampling rate to 100% in the application configuration.
Why it's wrong here
Global 100% sampling would capture all requests, increasing cost and storage.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between sampling rate configuration (which controls which requests are traced) and quota or exporter settings (which control data transmission limits), leading candidates to confuse increasing span quotas with increasing sampling probability.
Detailed technical explanation
How to think about this question
Under the hood, Cloud Trace uses the OpenTelemetry SDK's Sampler interface, which includes a `shouldSample` method that receives the SpanContext, TraceId, SpanKind, attributes, and links. A custom sampler can inspect attributes like `http.route` or `url.path` to decide the sampling probability per endpoint. In a real-world scenario, a high-traffic endpoint like `/api/checkout` might need 100% sampling for detailed latency analysis, while `/api/health` can remain at 10% to reduce overhead and cost.
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.
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: Implement a custom sampler in the application code to sample the specific endpoint at 100%. — Option C is correct because Cloud Trace allows you to implement a custom sampler in your application code to override the default sampling rate for specific endpoints. By using the OpenTelemetry SDK, you can create a sampler that checks the request path and returns a sampling decision of 1.0 (100%) for the high-traffic endpoint while delegating to the default sampler (e.g., 0.1) for all other requests. This gives you fine-grained control without affecting the global sampling configuration.
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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