Cloud Elasticity: Automatically Scale Resources to Match Demand
A company runs a private cloud infrastructure for its internal applications. During seasonal sales events, demand for computing resources doubles. The IT team wants to automatically expand the private cloud by utilizing a public cloud provider during these peak periods, and then scale back when demand normalizes. Which cloud computing concept does this scenario BEST describe?
Quick Answer
This scenario introduces cloud bursting, a hybrid approach where a private cloud automatically extends into public cloud capacity during periods of high demand, but the underlying cloud characteristic being tested is still elasticity, the same core concept that appears whenever resources scale automatically in both directions to match demand. During seasonal sales events, demand for computing resources doubles, and rather than requiring the IT team to manually provision additional capacity, the private cloud automatically expands by borrowing resources from a public cloud provider, then automatically scales back down to normal levels once demand returns to baseline. That full cycle, automatic expansion in response to increased demand followed by automatic contraction once demand subsides, is the complete definition of elasticity, regardless of whether the expansion happens entirely within one cloud environment or bursts out into a second provider. Cloud bursting is best understood as a specific implementation strategy for achieving elasticity in a hybrid cloud model, not a separate essential characteristic of its own. Whenever a scenario describes a private cloud environment automatically extending into public cloud resources during peak demand and then contracting back afterward, without any manual provisioning steps, recognize that as elasticity being achieved through cloud bursting rather than a distinct concept requiring its own separate label.
⚠ Common exam trap
CompTIA often tests the distinction between elasticity and scalability, where candidates mistakenly choose scalability because they confuse the ability to grow (scalability) with the automated, bidirectional scaling (elasticity) described in the 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
This scenario describes elasticity, which is the ability of a cloud system to dynamically scale resources up or down based on demand. The private cloud automatically expands into a public cloud (cloud bursting) during peak periods and scales back when demand normalizes, matching the definition of elasticity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
High availability
Why it's wrong here
High availability keeps workloads running through component failure using redundancy and health checks, not by adding capacity during demand peaks. It would be the correct choice when the requirement is continuous uptime with no service interruption, rather than temporary cloud bursting.
- ✓
Elasticity
Why this is correct
Elasticity is the ability to automatically provision and de-provision resources to match current demand. Cloud bursting is an implementation of elasticity in a hybrid cloud model, allowing seamless expansion into public cloud during peak loads.
- ✗
Load balancing
Why it's wrong here
Load balancing distributes incoming traffic across multiple servers to optimize resource use and avoid overloading any single server. While useful in cloud environments, it does not directly describe the dynamic expansion of resources into another cloud.
- ✗
Disaster recovery
Why it's wrong here
Disaster recovery restores workloads after an outage, using replication and failover to a secondary site; it does not elastically add capacity during predictable demand peaks. It would be the correct choice when the requirement is recovering from a region or site failure, not seasonal bursting.
Go deeper
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Key term
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Key term
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Same concept, more angles
2 more ways this is tested on 220-1101
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 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?
medium- ✓ A.Rapid elasticity
- B.Resource pooling
- C.Measured service
- D.On-demand self-service
Why A: 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.
Variation 2. A business uses a cloud service that automatically increases the number of virtual servers during peak traffic hours and decreases them during low usage, all without manual intervention. The policy is predefined in the cloud management console. This scenario best exemplifies which characteristic of cloud computing?
hard- A.On-demand self-service
- ✓ B.Rapid elasticity
- C.Resource pooling
- D.Measured service
Why B: Rapid elasticity is the correct characteristic because the cloud service automatically scales virtual server resources up and down based on predefined policies, matching demand without manual intervention. This dynamic scaling—adding instances during peak traffic and removing them during low usage—is the core definition of rapid elasticity in cloud computing, as it allows resources to expand and contract elastically to meet workload changes.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This 220-1101 practice question is part of Courseiva's free CompTIA 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 220-1101 exam.