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Difficulty: HardUnderstand concepts of cloud economics

A genomic research institution is evaluating the migration of its DNA sequencing pipeline to the AWS Cloud. The pipeline runs highly resource-intensive, batch-processing jobs that vary wildly in demand, operating heavily for a few days a month and remaining idle otherwise. On-premises, the institution maintains a cluster of high-performance servers that are underutilized 80%80\% of the time. Which of the following represent the primary economic advantages of moving this workload to AWS? (Select TWO.)

  1. The transition from a capital expense (CapEx) model of purchasing physical hardware to an operating expense (OpEx) model where costs align with actual analysis runtimes.Answer
  2. The capability to leverage elasticity by dynamically provisioning compute resources during active sequencing runs and terminating them when processing is complete, avoiding idle capacity costs.Answer
  3. C
    The reduction of operational costs by utilizing On-Demand Instances for baseline infrastructure that requires uninterrupted, 24/724/7 availability.
  4. D
    The elimination of capital expenses by transferring ownership and depreciation of the existing physical data center assets to AWS.
  5. E
    The ability to scale capacity upward to support long-term organizational growth, which eliminates the need to monitor or adjust active cloud resource utilization.

Answer

The primary economic advantages are the transition from a capital expense model to an operating expense model, and the capability to leverage elasticity by dynamically provisioning and terminating compute resources based on active workloads.
Migrating the genomic sequencing workload to AWS allows the institution to transition from a capital expense model (purchasing physical servers) to an operating expense model (paying only for active runs). By leveraging cloud elasticity, they can dynamically provision compute instances for the short duration of active sequencing and terminate them immediately afterward, completely avoiding costs during the period when resources would otherwise sit idle on-premises.

Step-by-Step Solution

1
Analyze the workload demand pattern in the scenario.
The genomic pipeline has highly variable, batch-processing demand, running for only a few days a month and remaining idle the rest of the time.
Identifying the workload profile is necessary to determine which cloud economics concepts, such as elasticity, are applicable.
2
Evaluate the economic impact of shifting infrastructure acquisition models.
Eliminating the need to purchase physical hardware shifts costs from capital expenses (CapEx) to variable operating expenses (OpEx) that occur only during active analysis.
This maps directly to the cloud economic concept of trading capital expense for variable operating expense.
3
Evaluate how dynamic resource provisioning affects idle hardware costs.
By using elastic scaling, compute instances can be provisioned when sequencing begins and terminated when it ends, avoiding costs during the idle period.
This demonstrates the direct cost benefit of elasticity compared to provisioning fixed on-premises capacity.

Key Concept

Cloud economics benefits including CapEx to OpEx shift and elasticity.
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Understand concepts of cloud economics

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