- A
Create a diagnostic setting on the scale set and build a log query alert for CPU samples.
Why wrong: This sends or queries data after ingestion and is unnecessary for a native CPU threshold.
- B
Create an Azure Monitor metric alert on the scale set CPU metric and attach an action group.
Metric alerts evaluate platform metrics directly, so no extra log ingestion is needed. An action group is the correct notification mechanism for email, webhook, SMS, or other responses. This design is the lowest-overhead way to detect sustained CPU pressure on a VM scale set and notify operators quickly.
- C
Configure an autoscale rule and rely on its notification settings for alerting.
Why wrong: Autoscale can react to load, but it is not the best fit for a dedicated operational alert requirement.
- D
Install a monitoring extension that writes CPU readings to storage for later review.
Why wrong: Writing custom CPU samples to storage adds management overhead and does not provide native Azure alerting behavior.
CPU Metric Alert for Scale Sets Without Extra Ingestion
This AZ-104 practice question tests your understanding of monitor and maintain azure resources. 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.
An operations team manages an Azure virtual machine scale set that hosts a stateless API. They already collect guest logs in Log Analytics, but they do not want to ingest extra performance data just to watch CPU. They need an alert when average CPU across the scale set stays above 80% for 10 minutes, and the notification must support email and a webhook. What should they configure?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Create an Azure Monitor metric alert on the scale set CPU metric and attach an action group.
Option B is correct because Azure Monitor metric alerts can directly evaluate the 'Percentage CPU' metric from a virtual machine scale set without ingesting additional performance data into Log Analytics. By setting the aggregation to 'Average' and the threshold to 80% for a duration of 10 minutes, the alert triggers when the condition is met. An action group attached to the alert can send notifications via email and webhook simultaneously, meeting all requirements without extra data ingestion.
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.
- ✗
Create a diagnostic setting on the scale set and build a log query alert for CPU samples.
Why it's wrong here
This sends or queries data after ingestion and is unnecessary for a native CPU threshold.
When this WOULD be correct
If the question required alerting based on custom CPU metrics or complex conditions that can only be expressed via log queries (e.g., combining CPU with memory or application logs), and the team was already collecting guest logs in Log Analytics, then a log query alert would be appropriate.
- ✓
Create an Azure Monitor metric alert on the scale set CPU metric and attach an action group.
Why this is correct
Metric alerts evaluate platform metrics directly, so no extra log ingestion is needed. An action group is the correct notification mechanism for email, webhook, SMS, or other responses. This design is the lowest-overhead way to detect sustained CPU pressure on a VM scale set and notify operators quickly.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure an autoscale rule and rely on its notification settings for alerting.
Why it's wrong here
Autoscale can react to load, but it is not the best fit for a dedicated operational alert requirement.
When this WOULD be correct
A question that asks: 'You need to automatically add instances to a scale set when average CPU exceeds 80% for 10 minutes. What should you configure?' In that case, an autoscale rule would be the correct answer.
- ✗
Install a monitoring extension that writes CPU readings to storage for later review.
Why it's wrong here
Writing custom CPU samples to storage adds management overhead and does not provide native Azure alerting behavior.
When this WOULD be correct
If the question asked for a method to collect historical CPU performance data for compliance or auditing purposes, without the need for real-time alerting, then installing a monitoring extension to write CPU readings to storage would be appropriate.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The AZ-104 exam frequently reuses these exact scenarios with slightly different constraints.
✓Create an Azure Monitor metric alert on the scale set CPU metric and attach an action group.Correct answer▾
Why this is correct
Metric alerts evaluate platform metrics directly, so no extra log ingestion is needed. An action group is the correct notification mechanism for email, webhook, SMS, or other responses. This design is the lowest-overhead way to detect sustained CPU pressure on a VM scale set and notify operators quickly.
✗Create a diagnostic setting on the scale set and build a log query alert for CPU samples.Wrong answer — click to see why▾
Why this is wrong here
The question states they do not want to ingest extra performance data just to watch CPU, and a log query alert requires CPU samples to be sent to Log Analytics, which would incur additional cost and data ingestion.
★ When this WOULD be the correct answer
If the question required alerting based on custom CPU metrics or complex conditions that can only be expressed via log queries (e.g., combining CPU with memory or application logs), and the team was already collecting guest logs in Log Analytics, then a log query alert would be appropriate.
Why candidates choose this
Candidates may think that since they already collect guest logs, extending that to include CPU metrics is a natural step, and they may not realize that Azure Monitor provides a built-in CPU metric that can be used without additional data ingestion.
✗Configure an autoscale rule and rely on its notification settings for alerting.Wrong answer — click to see why▾
Why this is wrong here
Autoscale rules are designed to automatically adjust the number of instances based on metrics, not to send alerts. Their notification settings are for scaling events, not for alerting on sustained high CPU, and they lack the flexibility of action groups (e.g., email and webhook).
★ When this WOULD be the correct answer
A question that asks: 'You need to automatically add instances to a scale set when average CPU exceeds 80% for 10 minutes. What should you configure?' In that case, an autoscale rule would be the correct answer.
Why candidates choose this
Candidates may confuse autoscale notifications with alerting capabilities, or think that autoscale rules can serve as a substitute for metric alerts because both involve CPU thresholds.
✗Install a monitoring extension that writes CPU readings to storage for later review.Wrong answer — click to see why▾
Why this is wrong here
This option requires writing CPU data to storage and later reviewing it, which does not provide real-time alerting with email and webhook notification as required by the question.
★ When this WOULD be the correct answer
If the question asked for a method to collect historical CPU performance data for compliance or auditing purposes, without the need for real-time alerting, then installing a monitoring extension to write CPU readings to storage would be appropriate.
Why candidates choose this
Candidates may think that any monitoring extension can provide alerting capabilities, or they may confuse diagnostic settings with metric collection, overlooking that the question specifically requires real-time alerting with notifications.
Analysis generated from the official AZ-104blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse metric alerts with log query alerts, assuming CPU monitoring requires Log Analytics ingestion, when in fact platform metrics are available natively and can be alerted on directly without extra data collection.
Detailed technical explanation
How to think about this question
Azure Monitor metric alerts use a time-series database that stores platform-level metrics (like Percentage CPU) at 1-minute granularity for up to 93 days, enabling evaluation of rolling windows (e.g., 10 minutes) without additional cost. The alert rule evaluates the average CPU across all instances in the scale set by aggregating the metric over the specified window, and when the condition is met, it fires the action group, which can invoke an Azure Function or Logic App via webhook for custom remediation. A real-world scenario is a stateless API that must maintain responsiveness; a metric alert can trigger an autoscale rule or notify an on-call engineer without the overhead of log ingestion.
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
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FAQ
Questions learners often ask
What does this AZ-104 question test?
Monitor and Maintain Azure Resources — This question tests Monitor and Maintain Azure Resources — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an Azure Monitor metric alert on the scale set CPU metric and attach an action group. — Option B is correct because Azure Monitor metric alerts can directly evaluate the 'Percentage CPU' metric from a virtual machine scale set without ingesting additional performance data into Log Analytics. By setting the aggregation to 'Average' and the threshold to 80% for a duration of 10 minutes, the alert triggers when the condition is met. An action group attached to the alert can send notifications via email and webhook simultaneously, meeting all requirements without extra data ingestion.
What should I do if I get this AZ-104 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on AZ-104
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. The operations team manages several Azure VMs in one resource group. They need an alert whenever average CPU percentage on any VM in the group stays above 80% for 10 minutes, and the alert must send email and SMS to the on-call team. What should the administrator configure?
medium- A.Create a Log Analytics query alert on the Activity log and manually notify the on-call team.
- ✓ B.Create an Azure Monitor metric alert rule at the resource-group scope and attach an action group.
- C.Export VM diagnostics to a storage account and have operators review the files after each incident.
- D.Create a resource lock on the VMs and use Azure Policy to notify the team about CPU spikes.
Why B: Option B is correct because Azure Monitor metric alerts can be created at the resource-group scope, which allows a single alert rule to monitor the 'Percentage CPU' metric across all VMs in that group. The alert triggers when the average CPU stays above 80% for 10 minutes (evaluated using a fixed aggregation window). An action group attached to the alert rule sends email and SMS notifications to the on-call team, meeting all requirements without manual intervention.
Variation 2. A production VM is using too much CPU. You want Azure to notify the operations team by email when Average Percentage CPU stays above 80 percent for 5 minutes. What should you configure?
easy- A.A diagnostic setting on the VM
- ✓ B.A metric alert rule linked to an action group
- C.A Log Analytics workspace only
- D.An Azure Policy assignment
Why B: A metric alert rule monitors a specific metric (e.g., Percentage CPU) and triggers when a condition (e.g., above 80% for 5 minutes) is met. Linking the alert to an action group allows Azure to send email notifications to the operations team. This is the correct Azure Monitor feature for threshold-based, metric-driven notifications.
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Last reviewed: Jun 11, 2026
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