PCDOE Implementing service monitoring strategies Practice Question
This PCDOE practice question tests your understanding of implementing service monitoring strategies. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 is defining an SLO for a web application that runs on Compute Engine behind an HTTP Load Balancer. They need to measure the proportion of requests that complete within 300ms. Which Cloud Monitoring metric is most appropriate as the SLI?
The SLI must measure the proportion of requests completing within 300ms, which is a latency distribution metric. The `total_latencies` metric from the HTTPLoad Balancer provides a histogram of request latencies, allowing you to compute the percentage of requests below a threshold (e.g., 300ms). This directly supports the SLO definition.
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.
This metric gives latency distribution, including percentiles, making it ideal for a latency SLI.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between latency metrics (histogram-based) and simple counters or byte metrics, expecting candidates to recognize that only a distribution metric like `total_latencies` can compute percentile-based SLIs.
Detailed technical explanation
How to think about this question
The `total_latencies` metric is a distribution metric that records request latency from the load balancer's perspective, including network, backend processing, and load balancer overhead. It uses a histogram bucket structure, and you can query it with `compute_percentile` or `rate` to derive the exact fraction of requests under 300ms. This is essential for accurate SLO monitoring because it captures the end-to-end user experience as seen by the load balancer.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
Implementing service monitoring strategies — This question tests Implementing service monitoring strategies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: loadbalancing.googleapis.com/https/total_latencies — The SLI must measure the proportion of requests completing within 300ms, which is a latency distribution metric. The `total_latencies` metric from the HTTP Load Balancer provides a histogram of request latencies, allowing you to compute the percentage of requests below a threshold (e.g., 300ms). This directly supports the SLO definition.
What should I do if I get this PCDOE 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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