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MS-900 Describe cloud concepts Practice Question

Which cloud characteristic allows an organization to increase or decrease computing resources quickly based on demand, without requiring manual intervention?

⚠ Common exam trap

Watch out — candidates often confuse 'rapid elasticity' with 'resource pooling' because both involve dynamic allocation, but resource pooling is about sharing resources among multiple tenants, not about automatically scaling a single tenant's resources on demand.

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, on-demand scaling of computing resources (such as virtual machines, storage, or network bandwidth) in response to fluctuating workload demands, without requiring manual provisioning or de-provisioning. This is a core feature of cloud computing defined by NIST SP 800-145, allowing resources to scale out (increase) or scale in (decrease) dynamically, often using orchestration tools like Azure Autoscale or AWS Auto Scaling. The key distinction is that the scaling happens quickly and automatically, based on predefined rules or metrics like CPU utilization or request count.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Measured service

    Why it's wrong here

    Measured service is a cloud characteristic that refers to the metering and monitoring of resource usage, typically for billing, cost allocation, and optimization purposes. It involves tracking metrics like compute hours, storage GB, or network I/O to provide pay-per-use billing and transparency. While it supports capacity planning by showing historical consumption, it does not automatically adjust resource allocation in response to changing demand, so it is not the correct characteristic for scaling, which requires elasticity.

  • ✓

    Rapid elasticity

    Why this is correct

    Rapid elasticity is the cloud characteristic that allows resources—such as virtual machines, storage, or bandwidth—to be provisioned and released quickly, often automatically, to scale in response to fluctuating demand. It gives organizations the ability to scale out (increase resources) and scale in (decrease resources) seamlessly, sometimes without human intervention using orchestration tools or auto-scaling policies. This directly supports dynamic workloads where usage spikes or drops, making it the correct answer for the question.

  • ✗

    Resource pooling

    Why it's wrong here

    Resource pooling is a cloud characteristic where the provider uses a multi-tenant model to serve multiple customers from shared physical and virtual resources, such as compute, storage, and network. Resources are dynamically assigned and reassigned according to customer demand, but the customer has no visibility into or control over the exact underlying infrastructure. This pooling enables economies of scale and cost efficiency, but it does not inherently enable the rapid, automatic scaling of resources for a single organization; that capability is provided by elasticity, not pooling itself.

  • ✗

    Broad network access

    Why it's wrong here

    Broad network access is the cloud characteristic that ensures all cloud resources are accessible over the network using standard protocols (e.g., HTTP, HTTPS) from a wide range of devices, including laptops, smartphones, and tablets. It emphasizes ubiquitous connectivity and the ability to access services from any location with internet access, regardless of the client platform. While network access is necessary for any cloud deployment, it does not describe the ability to dynamically increase or decrease resources based on demand, which is the defining feature of rapid elasticity. Thus, this option is incorrect for the question.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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