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Difficulty: MediumCost-Optimized Compute Selection and Purchasing Strategies

A software company is deploying a corporate training platform on AWS. The platform requires a backend service to process employee learning telemetry, which must run continuously 2424 hours a day, 77 days a week (24/724/7). Additionally, the platform stores user progress and quiz results in a database. This database experiences highly unpredictable, sharp spikes in traffic when training modules are assigned to large teams. The company wants to design a highly cost-optimized solution for both compute and database resources. Which combination of services and purchasing strategies will meet these requirements at the lowest cost?

  1. Run the backend service on AWS Fargate covered by a 11-year Compute Savings Plan, and use Amazon DynamoDB in on-demand capacity mode for the database.Answer
  2. B
    Run the backend service on AWS Fargate covered by a 11-year Compute Savings Plan, and use Amazon DynamoDB in provisioned capacity mode for the database.
  3. C
    Run the backend service on AWS Lambda, and use Amazon DynamoDB in on-demand capacity mode for the database.
  4. D
    Run the backend service on AWS Fargate, and use Amazon RDS for PostgreSQL for the database, covering both the Fargate tasks and the RDS instance under a single 11-year Compute Savings Plan.

Answer

Run the backend service on AWS Fargate covered by a 11-year Compute Savings Plan, and use Amazon DynamoDB in on-demand capacity mode for the database.
Running the backend service on AWS Fargate with a Compute Savings Plan provides significant cost savings for steady-state, continuous compute workloads. Utilizing Amazon DynamoDB in on-demand capacity mode is the most cost-effective database choice because it automatically handles sudden, unpredictable traffic spikes without manual intervention or the need to pay for idle provisioned capacity.

Step-by-Step Solution

1
Analyze the operational requirements of the backend compute layer.
Identify that a containerized backend running 24/724/7 is best suited for AWS Fargate, and a 11-year Compute Savings Plan will offer the maximum discount for this steady-state workload.
Compute Savings Plans cover AWS Fargate and provide significant savings over On-Demand rates for continuous use.
2
Analyze the traffic pattern of the database layer.
Determine that Amazon DynamoDB with on-demand capacity mode is the best fit.
The database experiences sharp, unpredictable spikes. On-demand capacity mode automatically scales to handle these spikes instantly and avoids the costs of idle, provisioned capacity.
3
Evaluate the scope of the Compute Savings Plan across the selected services.
Confirm that the Compute Savings Plan applies to AWS Fargate but excludes Amazon RDS database instances.
Compute Savings Plans are restricted to EC2, Fargate, and Lambda, meaning they cannot be used to offset RDS costs.

Key Concept

Matching compute hosting models and purchasing strategies with workload patterns, and understanding the billing scopes of AWS Savings Plans and DynamoDB capacity modes.
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Topics

Cost-Optimized Compute Selection and Purchasing Strategies