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Difficulty: MediumCost-Optimized Compute Selection and Purchasing Strategies

A media streaming company is designing a cost-optimized architecture on AWS. The application consists of a web portal and API tier running on Amazon EC2 instances 24/7 with a predictable resource baseline, a video transcoding service on EC2 instances that processes user uploads dynamically and is fault-tolerant, and an Amazon RDS for PostgreSQL database. The transcoding service transfers large volumes of video data to and from Amazon S3. Which combination of strategies will provide the most cost-effective compute and data transfer architecture? (Select TWO.)

  1. Purchase a Compute Savings Plan to cover the baseline EC2 instances running the web portal and API tier.Answer
  2. Deploy the video transcoding service on EC2 Spot Instances managed by an Auto Scaling group.Answer
  3. C
    Purchase a Compute Savings Plan to cover both the web portal EC2 instances and the Amazon RDS database instances.
  4. D
    Migrate the video transcoding service to AWS Lambda and configure it to run as a continuous background daemon to process uploads.
  5. E
    Configure the transcoding EC2 instances in a private subnet to access the S3 buckets through a NAT Gateway.

Answer

Deploying the video transcoding service on EC2 Spot Instances and purchasing a Compute Savings Plan to cover the baseline EC2 instances running the web portal and API tier.
The correct strategy combines a Compute Savings Plan for the predictable 24/7 web portal and API tier with EC2 Spot Instances for the stateless, fault-tolerant transcoding service. Compute Savings Plans provide automatic discounts on EC2 instances, while Spot Instances offer the highest discounts for workloads that can handle interruptions.

Step-by-Step Solution

1
Analyze the web portal and API workload characteristics.
Identified as a 24/7 running compute workload with a predictable baseline.
This steady-state compute requirement makes it eligible and optimal for a Compute Savings Plan, which offers a discount in exchange for a continuous usage commitment.
2
Analyze the video transcoding workload characteristics.
Identified as a stateless, fault-tolerant, and dynamically scaling workload.
Because the transcoding service can handle interruptions, it is an ideal candidate for EC2 Spot Instances, which provide the maximum discount rate.
3
Evaluate the database and data transfer components for cost optimization.
Determined that RDS cannot be covered by Compute Savings Plans and that NAT Gateways introduce unnecessary data processing fees for high-volume S3 transfers.
This rules out the incorrect options and confirms that a S3 Gateway Endpoint and RDS Reserved Instances should be used for those specific components.

Key Concept

Selecting cost-optimized compute purchasing models (Savings Plans, Spot Instances) and avoiding expensive data transfer paths for predictable and interruptible workloads.
Estimated Time:2m 0s
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Cost-Optimized Compute Selection and Purchasing Strategies