The answer is using the OpenTelemetry Collector with the Google Cloud Monitoring exporter, along with the Cloud Monitoring API via `projects.timeSeries.create`, and the `gcloud logging write` command with a structured log entry containing a `logging.googleapis.com/monitoring` metric. These three approaches are valid because they all provide a direct path for custom application metric monitoring in Cloud Monitoring: the OpenTelemetry Collector offers a vendor-neutral pipeline with native GCP export, the API allows programmatic ingestion of arbitrary time series data without an intermediary agent, and the logging-based method leverages structured logs to automatically generate metrics. On the Google Professional Cloud DevOps Engineer exam, this question tests your understanding of the distinction between agent-based, API-based, and log-based metric ingestion, often trapping candidates who confuse Cloud Monitoring’s built-in agent metrics with custom metric sources. A key memory tip is to remember the three “P”s: Pipeline (OpenTelemetry), Programmatic (API), and Parse (structured logs).
PCDOE Implementing service monitoring strategies Practice Question
This PCDOE practice question tests your understanding of implementing service monitoring strategies. 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.
Which THREE of the following are valid approaches to monitor a custom application metric in Cloud Monitoring? (Choose 3)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the Cloud Monitoring API to write time series data directly.
Option B is correct because the Cloud Monitoring API allows you to write custom metric data directly via the `projects.timeSeries.create` endpoint. This is the most direct programmatic approach, supporting arbitrary metric descriptors and time series data without requiring any agent or intermediary.
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.
✗
Install the Stackdriver Monitoring agent on a Windows VM and configure custom metric collection in the agent configuration file.
Why it's wrong here
The legacy Stackdriver agent does not support custom metrics on Windows.
✓
Use the Cloud Monitoring API to write time series data directly.
Why this is correct
The API allows writing custom metrics.
Related concept
Read the scenario before looking for a memorised answer.
✓
Create a logs-based metric from application logs that contain the metric value.
Why this is correct
Logs-based metrics can extract values from log entries.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use the built-in JMX plugin in the Cloud Monitoring agent to collect Java application metrics.
Why it's wrong here
Cloud Monitoring agent does not have a JMX plugin.
✓
Use the OpenTelemetry Collector with the Google Cloud Monitoring exporter.
Why this is correct
OpenTelemetry is a supported way to send metrics.
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 predefined agent-collected metrics (like JMX plugin metrics) and custom metrics that require explicit API or logs-based creation, leading candidates to incorrectly select agent-based options for custom metric monitoring.
Detailed technical explanation
How to think about this question
Under the hood, the Cloud Monitoring API uses the `MetricDescriptor` and `TimeSeries` resources, where you must first create a custom metric descriptor (via `projects.metricDescriptors.create`) before writing data points. The API enforces a 24-hour retention for custom metrics and a maximum of 10,000 metric descriptors per project, which is critical for large-scale monitoring designs.
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: Use the Cloud Monitoring API to write time series data directly. — Option B is correct because the Cloud Monitoring API allows you to write custom metric data directly via the `projects.timeSeries.create` endpoint. This is the most direct programmatic approach, supporting arbitrary metric descriptors and time series data without requiring any agent or intermediary.
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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