Question 485 of 1,031
Describe cloud conceptsmediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is elasticity, as it is the cloud computing characteristic that enables automatic resource adjustment to match fluctuating demand. In the given scenario, the Azure Virtual Machine Scale Set’s autoscale rule—adding VMs when CPU exceeds 75% and removing them when it drops below 30%—perfectly demonstrates this concept by dynamically scaling compute capacity up and down without manual intervention. On the Microsoft Azure Fundamentals AZ-900 exam, elasticity is frequently tested alongside scalability; a common trap is confusing the two, but remember that elasticity refers specifically to *automated* scaling in response to real-time load changes, while scalability is the broader ability to handle growth. For a quick memory tip, think of a rubber band: it stretches (scales up) when pulled and snaps back (scales down) when released—that’s elasticity in action.

AZ-900 Describe cloud concepts Practice Question

This AZ-900 practice question tests your understanding of describe cloud concepts. 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 company runs a web application on a set of Azure virtual machines. The application experiences unpredictable spikes in user traffic. The company configures an Azure Virtual Machine Scale Set with an autoscale rule that adds virtual machines when CPU usage exceeds 75% and removes virtual machines when CPU usage drops below 30%. This ability to automatically adjust compute resources to match demand best represents which characteristic of cloud computing?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "best"

    Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

Question 1mediummultiple choice
Full question →

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

Elasticity

Elasticity is the ability of a cloud system to automatically scale resources up or down to match demand. In this scenario, the Azure Virtual Machine Scale Set dynamically adds VMs when CPU exceeds 75% and removes them when CPU drops below 30%, directly demonstrating elasticity. This ensures the application has sufficient compute capacity during traffic spikes and avoids over-provisioning during low usage.

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.

  • Elasticity

    Why this is correct

    Correct. Elasticity is the ability to automatically provision and de-provision resources as demand changes. The autoscale rule that adds and removes VMs based on CPU usage is a textbook example of elasticity.

    Clue confirmation

    The clue word "best" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • High availability

    Why it's wrong here

    Incorrect. High availability ensures that applications remain accessible despite failures, typically through redundant components. While autoscaling can contribute to availability, the primary focus of this scenario is on adjusting capacity to meet workload changes, not on maintaining uptime through redundancy.

  • Fault tolerance

    Why it's wrong here

    Incorrect. Fault tolerance is the ability of a system to continue operating even if one or more of its components fail. The scenario describes scaling based on demand, not surviving component failures.

  • Disaster recovery

    Why it's wrong here

    Incorrect. Disaster recovery involves processes and tools to restore services after a major outage or disaster, such as by failing over to a secondary region. The autoscale rule described does not address recovery from disasters.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates confuse elasticity with high availability, but elasticity is specifically about scaling resources to meet demand, while high availability is about keeping the service running despite failures.

Trap categories for this question

  • Scenario analysis trap

    Incorrect. High availability ensures that applications remain accessible despite failures, typically through redundant components. While autoscaling can contribute to availability, the primary focus of this scenario is on adjusting capacity to meet workload changes, not on maintaining uptime through redundancy.

Detailed technical explanation

How to think about this question

Under the hood, Azure VMSS uses autoscale rules based on metrics like CPU percentage, which are collected by the Azure Monitor agent and evaluated by the Autoscale service. The scale-out and scale-in operations involve provisioning new VM instances from a configured image or removing instances gracefully, with a cooldown period (default 5 minutes) to prevent flapping. In real-world scenarios, elasticity is critical for e-commerce platforms during flash sales, where traffic can surge 10x in minutes and then drop just as quickly.

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-900 question test?

Describe cloud concepts — This question tests Describe cloud concepts — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Elasticity — Elasticity is the ability of a cloud system to automatically scale resources up or down to match demand. In this scenario, the Azure Virtual Machine Scale Set dynamically adds VMs when CPU exceeds 75% and removes them when CPU drops below 30%, directly demonstrating elasticity. This ensures the application has sufficient compute capacity during traffic spikes and avoids over-provisioning during low usage.

What should I do if I get this AZ-900 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Same concept, more angles

4 more ways this is tested on AZ-900

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. A startup runs a web application on Azure virtual machines. The application experiences sudden, short-lived spikes in traffic multiple times a day. The startup configures an autoscale rule that adds two additional VM instances when CPU usage exceeds 75% and removes them when CPU drops below 30%. This approach is designed to match resource consumption closely to demand. Which cloud computing characteristic does this scenario primarily demonstrate?

medium
  • A.High Availability
  • B.Elasticity
  • C.Fault Tolerance
  • D.Durability

Why B: Elasticity is the ability of a cloud system to automatically scale resources up or down based on real-time demand. In this scenario, the autoscale rule dynamically adds two VM instances when CPU exceeds 75% and removes them when CPU drops below 30%, closely matching resource consumption to traffic spikes. This on-demand provisioning and de-provisioning of compute capacity is the defining characteristic of elasticity.

Variation 2. A startup application experiences unpredictable traffic spikes. The application runs on Azure Virtual Machines. They want the VMs to automatically increase in number during peak times and decrease during low usage, without manual intervention. Which cloud characteristic does this requirement describe?

medium
  • A.Elasticity
  • B.High availability
  • C.Disaster recovery
  • D.Geo-redundancy

Why A: Elasticity is the cloud characteristic that enables resources to automatically scale out (increase) during high demand and scale in (decrease) during low demand, matching capacity to workload in real time. In this scenario, Azure Virtual Machines can be configured with autoscale rules (e.g., based on CPU > 75% for 5 minutes) to add or remove VM instances without manual intervention. This directly addresses the startup's need to handle unpredictable traffic spikes while optimizing cost.

Variation 3. A manufacturing company deploys a batch processing application on Azure. The processing workload is highly unpredictable; sometimes the application requires hundreds of virtual machines for a few hours to process a large queue of jobs, and at other times it requires only a handful of virtual machines. The company configures the application to automatically add and remove virtual machines based on the size of the processing queue, ensuring that they never pay for idle capacity. Which cloud characteristic does this scenario primarily demonstrate?

medium
  • A.High availability
  • B.Elasticity
  • C.Fault tolerance
  • D.Disaster recovery

Why B: The scenario describes automatically scaling the number of virtual machines up and down based on the queue size, which directly aligns with the cloud characteristic of elasticity. Elasticity allows resources to be dynamically provisioned and de-provisioned to match workload demand, ensuring the company never pays for idle capacity. This is distinct from high availability, fault tolerance, or disaster recovery, which focus on uptime, redundancy, and data protection rather than dynamic scaling.

Variation 4. A company runs an e-commerce web application on a set of Azure virtual machines behind a load balancer. The application experiences unpredictable traffic surges during flash sales. The company configures an autoscale setting that automatically adds virtual machines when the average CPU usage across the existing VMs exceeds 75% for five minutes, and removes virtual machines when CPU usage drops below 30% for ten minutes. Which essential characteristic of cloud computing does this configuration primarily demonstrate?

medium
  • A.Measured service
  • B.Rapid elasticity
  • C.Resource pooling
  • D.Broad network access

Why B: B is correct because the autoscale configuration dynamically adds and removes virtual machines in response to real-time CPU usage thresholds, which is the defining characteristic of rapid elasticity. This allows the e-commerce application to scale computing resources up and down automatically and seamlessly to match unpredictable traffic surges, ensuring performance during flash sales without manual intervention.

Last reviewed: Jun 11, 2026

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