Question 1
Show Answer
A. Resource metering: This is the process of measuring resource consumption. While it enables the pay-as-you-go model, it is not the cost-saving strategy itself.
B. Reserved resources: This model offers discounts for a long-term commitment (e.g., 1-3 years) and is best suited for stable, predictable workloads, not necessarily for leveraging elasticity to reduce costs.
C. Dedicated host: This provides a physical server for a single tenant. It is the most expensive option and is typically used for compliance or software licensing, directly contradicting the goal of reducing expenses.
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1. National Institute of Standards and Technology (NIST) Special Publication 800-145, "The NIST Definition of Cloud Computing":
Section 2, Page 2: Defines "On-demand self-service" and "Measured service" as essential characteristics of cloud computing. The pay-as-you-go model is a direct implementation of these principles, allowing consumers to provision resources as needed and pay only for what they use. The stateless application in the scenario is perfectly suited to leverage this on-demand nature for cost efficiency.
2. Amazon Web Services (AWS) Documentation, "Amazon EC2 Pricing":
On-Demand Pricing Section: "With On-Demand instances, you pay for compute capacity by the hour or the second with no long-term commitments... This frees you from the costs and complexities of planning, purchasing, and maintaining hardware... [It is recommended for] applications with short-term, spiky, or unpredictable workloads that cannot be interrupted." This directly supports the use of a pay-as-you-go model for an application designed for elasticity to reduce costs.
Reserved Instances & Dedicated Hosts Sections: The documentation contrasts this with Reserved Instances, which are for "applications with steady state or predictable usage," and Dedicated Hosts, which are physical servers that "can help you reduce costs by allowing you to use your existing server-bound software licenses." These use cases do not align with the scenario's primary goal of cost reduction through elasticity.
3. Microsoft Azure Documentation, "Virtual Machines pricing":
Pay as you go Section: Describes this model as ideal for "running applications with short-term or unpredictable workloads where there is no long-term commitment." This aligns with the scenario where an engineer wants to leverage the cloud's elasticity to match cost to actual usage, thus reducing waste.
Reserved Virtual Machine Instances Section: Explains that reservations are for workloads with "predictable, consistent traffic" and require a "one-year or three-year term," which is less flexible than pay-as-you-go.
4. Armbrust, M., et al. (2009). "Above the Clouds: A Berkeley View of Cloud Computing." University of California, Berkeley, Technical Report No. UCB/EECS-2009-28.
Section 3.1, Economic Advantages: The paper states, "Cloud Computing enables a pay-as-you-go model, where you pay only for what you use... An attraction of Cloud Computing is that computing resources can be rapidly provisioned and de-provisioned on a fine-grained basis... allowing clouds to offer an 'infinite' pool of resources in a pay-as-you-go manner." This academic source establishes the fundamental economic benefit of the pay-as-you-go model in leveraging elasticity, which is the core of the question.
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