PCD Managing application performance monitoring Practice Question
This PCD practice question tests your understanding of managing application performance monitoring. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 migrating an on-premises monitoring solution to Google Cloud. They need to collect custom application metrics from a batch processing job running on Compute Engine. Which two services can ingest custom metrics into Cloud Monitoring? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Logging with log-based metrics
Option C is correct because Cloud Logging can ingest any log entry, and log-based metrics allow you to extract numeric values from log content to create custom metrics that appear in Cloud Monitoring. Option E is correct because the Cloud Monitoring API lets you define custom metric descriptors and then write time-series data directly to those metrics, bypassing any agent or log pipeline.
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.
✗
Cloud Profiler API
Why it's wrong here
Profiler is for profiling CPU/memory, not custom metrics.
✗
Stackdriver Monitoring agent with custom plugin
Why it's wrong here
The Monitoring agent is deprecated and primarily collects system metrics; not recommended for custom metrics.
✓
Cloud Logging with log-based metrics
Why this is correct
Correct: log-based metrics can extract numerical values from logs and create custom metrics.
Related concept
Read the scenario before looking for a memorised answer.
✗
Cloud Trace API
Why it's wrong here
Cloud Trace is for distributed tracing, not custom metrics.
✓
Cloud Monitoring API with custom metric descriptors
Why this is correct
Correct: you can write custom metrics directly via the API.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that the Stackdriver Monitoring agent (Ops Agent) can ingest arbitrary custom metrics via plugins, when in fact it only collects predefined metrics and custom metrics require either log-based metrics or direct API calls.
Detailed technical explanation
How to think about this question
Log-based metrics work by defining a filter on log entries and then extracting a numeric value (e.g., via a counter or distribution) from a field in the structured log payload; the metric is then available in Cloud Monitoring with a 60-second resolution. The Cloud Monitoring API requires you to first create a MetricDescriptor (defining name, type, labels, and unit) and then use the timeSeries.create endpoint to write data points, which supports up to 10,000 time series per request. A real-world scenario is a batch job that logs processing duration per file; you can either parse the log with a log-based metric or have the job call the Monitoring API directly to report the duration as a custom metric.
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.
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: Cloud Logging with log-based metrics — Option C is correct because Cloud Logging can ingest any log entry, and log-based metrics allow you to extract numeric values from log content to create custom metrics that appear in Cloud Monitoring. Option E is correct because the Cloud Monitoring API lets you define custom metric descriptors and then write time-series data directly to those metrics, bypassing any agent or log pipeline.
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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