The correct answer is to create a metric alert rule with a dynamic threshold and scope it to a resource group containing Production VMs. This solution works because a single metric alert rule can be scoped to a resource group and then filtered by a tag, such as Environment=Production, allowing you to monitor the average CPU usage across all tagged VMs without needing individual rules for each machine. On the Microsoft Azure Solutions Architect Expert AZ-305 exam, this scenario tests your understanding of how to efficiently aggregate metrics across a dynamic set of resources using Azure Monitor’s alert rules and tag-based filtering, a common design pattern for cost-effective monitoring at scale. A frequent trap is creating separate alerts per VM, which wastes time and resources; instead, remember that scoping by resource group and filtering by tag lets one rule handle the entire set. Memory tip: think “one rule, one tag, one group” to avoid alert sprawl.
AZ-305 Practice Question: Design identity, governance, and monitoring solutions
This AZ-305 practice question tests your understanding of design identity, governance, and monitoring solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Your company has an Azure subscription with 100 virtual machines. You need to monitor the performance of these VMs and be alerted when the average CPU usage across a set of VMs exceeds 80% for 10 minutes. The set of VMs is defined by a tag (Environment=Production). Which Azure Monitor solution should you implement?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a metric alert rule with a dynamic threshold and scope it to a resource group containing Production VMs.
Option B is correct because a single metric alert rule with a static threshold can be scoped to a resource group and filtered by a tag (e.g., Environment=Production) using a dynamic threshold or static threshold, allowing you to monitor the average CPU usage across all VMs in that group without creating individual rules. This approach efficiently meets the requirement to alert when the average CPU usage across the set of VMs exceeds 80% for 10 minutes, as it aggregates metrics across the tagged VMs.
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 Azure Monitor VM Insights to visualize performance and set alerts per VM.
Why it's wrong here
VM Insights provides visualization but not aggregated alerts across multiple VMs.
✓
Create a metric alert rule with a dynamic threshold and scope it to a resource group containing Production VMs.
Why this is correct
Dynamic thresholds adapt to patterns and can be applied to a group of resources.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create a metric alert rule with a static threshold of 80% for each Production VM individually.
Why it's wrong here
Individual rules are not scalable and do not aggregate average across VMs.
✗
Use a Log Analytics query to calculate average CPU and set a log alert.
Why it's wrong here
Log alerts are for log data, not real-time metrics; they add latency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume they need to use VM Insights (Option A) or individual alerts (Option C) for per-VM monitoring, but the question specifically asks for an alert based on the average across a set of VMs, which is best achieved by a single metric alert rule scoped to a resource group with tag filtering.
Detailed technical explanation
How to think about this question
Azure Monitor metric alerts support static and dynamic thresholds, and can be scoped to a resource group or subscription with optional tag filtering. When you create a metric alert rule with a static threshold of 80% and scope it to the resource group containing Production VMs, the alert evaluates the average CPU percentage across all VMs in that scope over the aggregation window (e.g., 10 minutes). Under the hood, the alert rule uses the 'Percentage CPU' metric from the Microsoft.Compute/virtualMachines resource type, and the 'Average' aggregation is computed across all matching resources, not per VM. This avoids the need for log ingestion and reduces latency.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-305 question in full detail.
Design identity, governance, and monitoring solutions — This question tests Design identity, governance, and monitoring solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a metric alert rule with a dynamic threshold and scope it to a resource group containing Production VMs. — Option B is correct because a single metric alert rule with a static threshold can be scoped to a resource group and filtered by a tag (e.g., Environment=Production) using a dynamic threshold or static threshold, allowing you to monitor the average CPU usage across all VMs in that group without creating individual rules. This approach efficiently meets the requirement to alert when the average CPU usage across the set of VMs exceeds 80% for 10 minutes, as it aggregates metrics across the tagged VMs.
What should I do if I get this AZ-305 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 →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This AZ-305 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-305 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.