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Difficulty: HardUnderstand concepts of cloud economics

A municipal public transit authority plans to modernize its fare collection and passenger tracking system, which currently runs on legacy, on-premises mainframe hardware. The transit system experiences extreme peak passenger volumes during morning and evening rush hours, but very low usage overnight. The authority wants to understand how migrating this infrastructure to AWS will impact its financial model and total cost of ownership (TCO). Which two outcomes represent the primary cloud economics benefits of migrating this system to AWS? (Select TWO).

  1. Transitioning from upfront hardware investments to a variable operational expense model that aligns costs with passenger demand.Answer
  2. Reducing the total cost of ownership by dynamically matching infrastructure capacity with peak transit hours, eliminating the need to pay for idle resources during overnight periods.Answer
  3. C
    Increasing fixed capital expenditures to build dedicated physical environments in multiple AWS Regions.
  4. D
    Ensuring consistent scalability by allocating a static amount of cloud resources that remains constant regardless of daily passenger volume fluctuations.
  5. E
    Adopting a monolithic architecture to consolidate all fare collection components onto a single large server to simplify billing tracking.

Answer

Transitioning from upfront hardware investments to a variable operational expense model that aligns costs with passenger demand, and reducing the total cost of ownership by dynamically matching capacity with peak transit hours.
The correct outcomes are transitioning to a variable operational expense model and reducing TCO via dynamic capacity matching. Transitioning to a variable operational expense model replaces large upfront capital expenditures (CapEx) on hardware with pay-as-you-go operating expenses (OpEx). Dynamically matching capacity with peak demand leverages elasticity, meaning resources scale up during peak passenger volumes and scale down during overnight hours, preventing costs from running on idle resources.

Step-by-Step Solution

1
Analyze the financial transition described in the scenario, identifying the shift from buying physical mainframes to renting AWS resources.
Identify that the upfront hardware cost constitutes Capital Expenditure (CapEx), while paying for active resources constitutes Operating Expenditure (OpEx). Thus, transitioning to a variable operational expense model is correct.
Understanding the shift from CapEx to OpEx is fundamental to cloud economics.
2
Analyze the workload characteristics (extreme peak hours vs. low overnight usage) to evaluate capacity requirements.
Identify that the system has highly variable demand, meaning elasticity (scaling resources dynamically) will prevent pay-for-idle scenarios and reduce the total cost of ownership (TCO).
Elasticity is the core mechanism that optimizes costs for fluctuating workloads.

Key Concept

Concepts of cloud economics including CapEx to OpEx shift and elasticity
Estimated Time:2m 0s
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Understand concepts of cloud economics

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