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Zorluk: Çok zorUnderstand concepts of cloud economics

A financial services startup is planning to launch a new algorithmic trading simulation platform. The platform experiences massive, unpredictable traffic spikes during market hours (9:30 AM9:30\text{ AM} to 4:00 PM4:00\text{ PM} EST) but is virtually idle at night. Additionally, the startup must perform a weekly risk analysis batch job every Sunday, which requires high-performance compute resources for exactly 33 hours and can be interrupted without losing progress. The startup wants to optimize its cost structure by shifting capital expenditures (CapEx) to operating expenditures (OpEx) while maximizing the cost benefits of cloud economics.

Which two AWS billing and architectural strategies will best align with the company's financial goals of reducing Total Cost of Ownership (TCO) and leveraging the economic benefits of elasticity? (Select TWO.)

  1. Designing the trading simulation platform to dynamically scale compute instances up and down using Amazon EC2 Auto Scaling based on real-time demand metrics.Cevap
  2. Utilizing Amazon EC2 Spot Instances to run the weekly risk analysis batch jobs.Cevap
  3. C
    Purchasing 3-Year All Upfront Dedicated Host Reserved Instances for the trading simulation platform's compute tier.
  4. D
    Deploying the application on oversized EC2 instances to handle the peak market volume, relying on the scalability of the instances to support future growth.
  5. E
    Configuring the weekly risk analysis batch job to run on On-Demand EC2 instances to guarantee zero interruption, regardless of cost.

Cevap

The correct strategy involves scaling the trading platform dynamically using Amazon EC2 Auto Scaling and running the interruptible weekly risk analysis batch jobs on Amazon EC2 Spot Instances.
Leveraging Amazon EC2 Auto Scaling allows the platform to scale dynamically during unpredictable peak market hours and scale down to minimum capacity at night, optimizing operational costs (OpEx) through elasticity. Utilizing Amazon EC2 Spot Instances for the weekly risk analysis batch job is highly cost-effective because the job can tolerate interruptions, letting the startup take advantage of spare AWS capacity at deep discounts.

Adım Adım Çözüm

1
Analyze the platform's traffic pattern and identify the elasticity requirements.
The platform has highly variable demand (9:30 AM9:30\text{ AM} to 4:00 PM4:00\text{ PM} peak, idle at night), indicating a strong need for elasticity to match resource supply with demand.
Elasticity prevents paying for idle resources during off-peak times.
2
Evaluate the weekly risk analysis workload characteristics.
The batch job is weekly, runs for 33 hours, and is interruptible, making it a perfect fit for EC2 Spot Instances.
Spot Instances offer up to 90%90\% cost reduction for fault-tolerant workloads.
3
Assess the financial goal of shifting CapEx to OpEx.
Avoid options that require upfront payments or long-term capacity lock-in (such as 3-Year All Upfront Dedicated Host Reserved Instances).
Upfront reservations behave like capital expenses, reducing financial flexibility.
4
Identify the combinations of decisions that optimize Total Cost of Ownership (TCO) and support elasticity.
Combining Auto Scaling for variable traffic and Spot Instances for interruptible batch jobs maximizes the economic benefits of the cloud.
This combination minimizes runtime costs and eliminates capital expenditures.

Anahtar Kavram

Shifting CapEx to OpEx, leveraging Spot instances for fault-tolerant batch workloads, and using Auto Scaling to achieve elasticity.
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Understand concepts of cloud economics

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