220-1101 Virtualization and Cloud Computing Practice Question
A company runs a private cloud for its internal applications. During peak business hours, the IT team notices that some virtual machines (VMs) become slow due to high CPU and memory demand. The team wants the cloud infrastructure to automatically increase resources to the VMs when demand spikes and reduce them when demand drops, without manual intervention. Which cloud computing characteristic BEST describes this capability?
⚠ Common exam trap
Test-takers frequently confuse on-demand self-service (the ability to manually provision resources) with rapid elasticity (the automatic scaling of resources), but the question explicitly states 'automatically increase resources... without manual intervention,' which eliminates on-demand self-service.
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
✓
Rapid elasticity
Rapid elasticity is the cloud characteristic that enables automatic, seamless scaling of resources (such as CPU and memory) up or down in response to demand spikes or drops, without manual intervention. In this scenario, the private cloud infrastructure must dynamically allocate additional compute capacity to VMs during peak hours and reduce it when demand subsides, which is the precise definition of rapid elasticity. This is typically implemented through orchestration tools like VMware vSphere DRS or OpenStack Heat, which monitor utilization metrics and trigger scaling actions via APIs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Rapid elasticity
Why this is correct
Rapid elasticity is the defining cloud characteristic that permits resources to be provisioned and released automatically, both outward and inward, to match current demand almost instantly. This capability makes resources appear unlimited to the consumer and is essential for handling unpredictable or spiky workloads without manual intervention. In a private cloud for internal applications, rapid elasticity ensures that compute and storage scale seamlessly, which precisely satisfies the requirement of automatic resource adjustment in the question.
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Resource pooling
Why it's wrong here
Resource pooling in cloud computing aggregates heterogeneous physical and virtual resources to serve multiple tenants, with resources dynamically assigned and reassigned according to demand. This multi-tenant model improves utilization and cost efficiency, but it does not inherently trigger scale-out or scale-in for a single application. The shared infrastructure supports elasticity, yet pooling itself is a structural characteristic, not the mechanism that automatically adjusts capacity to meet fluctuating workload levels.
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Measured service
Why it's wrong here
Measured service refers to the metering of resource usage, enabling pay-per-use billing and detailed data for monitoring and optimization. Cloud systems track metrics such as compute hours, storage, and bandwidth to charge consumers and provide transparency. However, this telemetry simply records consumption after the fact; it does not proactively modify the allocated resources. Automatic scaling requires an orchestration component that reacts to those metrics, which is outside the scope of metering alone.
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On-demand self-service
Why it's wrong here
On-demand self-service empowers users to provision computing resources themselves through a management console or API, without requiring a service provider's manual approval. This convenience enables immediate access to capacity, but the initiative must come from a user or an external trigger. It does not include the automatic, policy-driven scaling that characterizes rapid elasticity, since the system does not independently modify resources based on real-time load. Thus, while related, self-service is not the answer for automatic scaling.
Go deeper
Related to this question
Learn chapter
Multi-Monitor Configuration
Key term
Software as a Service
Software as a Service (SaaS) is a cloud computing model where users access software applications over the internet on a subscription basis, without installing or maintaining the software locally.
Key term
Anything As A Service
A model where you rent any IT resource or service over the internet instead of owning it.
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