- A
A single Azure VM with an autoscale setting
Why wrong: A lone VM cannot scale horizontally into multiple identical instances by itself.
- B
A virtual machine scale set with autoscale enabled
VM scale sets are designed for many identical instances and work naturally with autoscale profiles.
- C
An availability set with manual VM resizing
Why wrong: Availability sets improve resilience but do not provide automatic horizontal scaling.
- D
Azure Container Instances running one container per request
Why wrong: Container instances do not match the requirement for Windows VM-based deployments and scale-set management.
AZ-104 Deploy and Manage Azure Compute Practice Question
This AZ-104 practice question tests your understanding of deploy and manage azure compute. 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.
A stateless API must run 4 to 12 identical Windows VMs, scale out automatically when average CPU stays above 70% for 10 minutes, and distribute instances to improve resiliency. Deployments are defined in Bicep. Which Azure compute service should be used?
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
A virtual machine scale set with autoscale enabled
A virtual machine scale set (VMSS) with autoscale enabled is the correct choice because it supports running multiple identical Windows VMs, can automatically scale out when average CPU exceeds 70% for 10 minutes, and distributes instances across fault domains and availability zones for resiliency. Bicep deployments natively define VMSS configurations, making it the ideal compute service for stateless, scalable API workloads.
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.
- ✗
A single Azure VM with an autoscale setting
Why it's wrong here
A lone VM cannot scale horizontally into multiple identical instances by itself.
When this WOULD be correct
If the question required a single, stateless VM with automatic scaling within that VM (e.g., scaling application threads) and no need for multiple instances, a single VM with autoscale (via Azure Automation or similar) could be correct.
- ✓
A virtual machine scale set with autoscale enabled
Why this is correct
VM scale sets are designed for many identical instances and work naturally with autoscale profiles.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
An availability set with manual VM resizing
Why it's wrong here
Availability sets improve resilience but do not provide automatic horizontal scaling.
When this WOULD be correct
For a stateful application requiring high availability with a fixed number of VMs (e.g., 3 VMs) that must be manually resized to handle planned load changes, an availability set with manual VM resizing would be correct.
- ✗
Azure Container Instances running one container per request
Why it's wrong here
Container instances do not match the requirement for Windows VM-based deployments and scale-set management.
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.
✓A virtual machine scale set with autoscale enabledCorrect answer▾
Why this is correct
VM scale sets are designed for many identical instances and work naturally with autoscale profiles.
✗A single Azure VM with an autoscale settingWrong answer — click to see why▾
Why this is wrong here
A single Azure VM cannot scale out to 4-12 instances; autoscale requires a scale set to add or remove VMs, not a single VM.
★ When this WOULD be the correct answer
If the question required a single, stateless VM with automatic scaling within that VM (e.g., scaling application threads) and no need for multiple instances, a single VM with autoscale (via Azure Automation or similar) could be correct.
Why candidates choose this
Candidates may think 'autoscale' applies to any VM, confusing VM-level scaling (e.g., resizing) with instance-level scaling (adding/removing VMs).
✗An availability set with manual VM resizingWrong answer — click to see why▾
Why this is wrong here
An availability set does not provide autoscaling; it only distributes VMs across fault and update domains for high availability. Manual resizing cannot automatically scale out based on CPU thresholds.
★ When this WOULD be the correct answer
For a stateful application requiring high availability with a fixed number of VMs (e.g., 3 VMs) that must be manually resized to handle planned load changes, an availability set with manual VM resizing would be correct.
Why candidates choose this
Candidates may confuse availability sets with scale sets, thinking that distributing VMs for resiliency automatically includes scaling capabilities, or they may overlook the requirement for automatic scaling based on CPU metrics.
✗Azure Container Instances running one container per requestWrong answer — click to see why▾
Why this is wrong here
Azure Container Instances (ACI) does not support autoscaling based on CPU metrics for Windows containers, nor does it provide a VM-based environment for running Windows VMs; it runs containers, not VMs.
★ When this WOULD be the correct answer
A question requiring a serverless container service to run stateless Linux containers that scale per request (e.g., HTTP triggers) and do not require VM-level control or Windows OS would make ACI correct.
Why candidates choose this
Candidates may confuse container instances with VM scale sets, thinking ACI can autoscale VMs, or they may assume 'stateless API' implies containers are always the best choice without considering the requirement for Windows VMs.
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 confuse autoscale settings (which only apply to scale sets or PaaS services) with individual VMs, or assume an availability set provides autoscaling, when in fact it only ensures fault tolerance for a static number of VMs.
Detailed technical explanation
How to think about this question
Under the hood, VMSS uses an autoscale profile with a scale-out rule that triggers when the 'Percentage CPU' metric exceeds 70% for a 10-minute aggregation window (using the 'Average' statistic and a 10-minute 'TimeGrain'). The scale set distributes VMs across fault domains (up to 3) and, if configured, availability zones to meet a 99.95% SLA. In real-world scenarios, you must also configure a scale-in rule to avoid thrashing, and use a 'cool-down' period (e.g., 5 minutes) between scaling events to stabilize the 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.
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FAQ
Questions learners often ask
What does this AZ-104 question test?
Deploy and Manage Azure Compute — This question tests Deploy and Manage Azure Compute — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: A virtual machine scale set with autoscale enabled — A virtual machine scale set (VMSS) with autoscale enabled is the correct choice because it supports running multiple identical Windows VMs, can automatically scale out when average CPU exceeds 70% for 10 minutes, and distributes instances across fault domains and availability zones for resiliency. Bicep deployments natively define VMSS configurations, making it the ideal compute service for stateless, scalable API workloads.
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 →
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Last reviewed: Jun 11, 2026
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