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Difficulty: HardUnderstand concepts of cloud economics

A manufacturing company is analyzing the financial impact of migrating its supply chain optimization application to AWS. Currently, the on-premises system runs on physical servers that are depreciated over a five-year lifecycle. The application experiences a predictable, steady baseline workload throughout the year, but requires double the capacity for a three-day period at the end of every month to run inventory reconciliations. Which of the following describes the most cost-effective strategy that aligns with AWS cloud economics principles for this workload?

  1. Commit to a Savings Plan for the baseline workload to reduce operating expenses, and dynamically provision additional resources only during the three-day monthly spikes to benefit from elasticity.Answer
  2. B
    Size the cloud infrastructure to permanently match the peak capacity of the monthly reconciliation using On-Demand Instances, thereby shifting all variable operational expenses into a fixed capital expense.
  3. C
    Purchase upfront Reserved Instances for the entire peak capacity to convert the monthly reconciliation spikes into capital expenses, ensuring that hardware remains dedicated and depreciates over time.
  4. D
    Utilize Spot Instances for the baseline workload to guarantee constant availability, and purchase On-Demand Instances for the three-day monthly spikes to convert capital expenses into operational expenses.

Answer

Commit to a Savings Plan for the baseline workload to reduce operating expenses, and dynamically provision additional resources only during the three-day monthly spikes to benefit from elasticity.
The correct strategy combines a commitment-based payment model (Savings Plan) to lower the operating expenses of the constant baseline workload with dynamic scaling (elasticity) to handle the short-term monthly spikes. This avoids paying for idle capacity and fully transitions the company from a capital expense model (depreciating physical servers) to an optimized operating expense model.

Step-by-Step Solution

1
Analyze the workload characteristics: a constant, predictable baseline throughout the year and a short, recurring spike at the end of each month.
Identified two distinct demand profiles: steady-state (baseline) and transient/elastic (monthly spike).
Different workload profiles require different pricing and provisioning models to optimize costs.
2
Identify the appropriate pricing model for the predictable baseline workload.
A commitment-based model like Savings Plans or Reserved Instances is ideal for steady-state baseline workloads, providing significant discounts over On-Demand rates.
Commitment reduces operating expenses for predictable workloads.
3
Identify the appropriate provisioning strategy for the transient monthly spike.
Using elasticity to provision resources dynamically for the three days and terminate them afterward is the most cost-effective approach.
This avoids paying for idle resources during the rest of the month, demonstrating the economic benefits of cloud elasticity.
4
Evaluate the financial transition model from on-premises to AWS.
Migrating to AWS shifts capital expenses (depreciating physical servers) to operating expenses (pay-as-you-go and operational cost optimization).
This aligns with the cloud economics principle of trading capital expense for variable operating expense.

Key Concept

Cloud Economics: CapEx vs OpEx and Elasticity
Estimated Time:2m 0s
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Understand concepts of cloud economics

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