Learn about the key AWS principle that enables companies to efficiently test new applications by scaling resources as needed without locking into long-term contracts.
Table of Contents
Question
A company wants to test a new application.
Which AWS principle will help the company test the application?
A. Make long-term commitments in exchange for a cost discount.
B. Scale up and down when needed without any long-term commitments.
C. Have total control over the application infrastructure.
D. Manage all of the maintenance tasks associated with the cloud.
Answer
B. Scale up and down when needed without any long-term commitments.
Explanation
This aligns with the core AWS principle of elasticity and scalability. AWS allows you to dynamically adjust your compute, storage, and other cloud resources to match the demands of your application. You can quickly scale up when you need more capacity for testing and scale back down when testing is complete. This on-demand provisioning means you only pay for the resources you use, without any long-term commitments or upfront costs.
The other options are not accurate:
A) While AWS does offer cost discounts for certain long-term commitments like Reserved Instances, this is not the best approach for the short-term needs of application testing. Flexibility is more important than discounts in this use case.
C) Having total control over application infrastructure is more aligned with on-premises hosting rather than the managed services of the cloud. With AWS, you can configure and manage your application but underlying infrastructure is handled by AWS.
D) AWS manages the underlying maintenance of the cloud infrastructure, but some maintenance tasks for your specific application (OS patching, updates, etc.) are still the customer’s responsibility in many cases. However, this is not the most relevant consideration for the application testing scenario.
In summary, the ability to elastically scale up and down on-demand without long-term lock-in is the key AWS principle that makes it ideal for efficiently testing new applications.
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