SAP-C02 · Question #873
A company runs an event ticketing application on AWS. The company deployed the application on an Amazon EKS cluster with the Amazon EC2 launch type. The application uses an Amazon RDS for MySQL DB…
The correct answer is D. Purchase Compute Savings Plans for the predicted base load of the EKS cluster. Use Spot. Fargate usage is best discounted with Compute Savings Plans (they apply to Fargate, unlike EC2 Instance SPs or EC2 RIs). Because the app tolerates interruptions, scaling surges with Fargate Spot minimizes cost. For the persistent RDS MySQL database, a 1-year All Upfront…
Question
A company runs an event ticketing application on AWS. The company deployed the application on an Amazon EKS cluster with the Amazon EC2 launch type. The application uses an Amazon RDS for MySQL DB instance. The application experiences infrequent surges in demand. The surges in demand correspond to event dates. The application stores job states in the RDS for MySQL DB instance and can withstand interruptions. The company is developing new features for the application and wants to migrate the application and the EKS cluster to use the AWS Fargate launch type. Which solution will meet these requirements MOST cost-effectively?
Options
- APurchase EC2 Standard Reserved Instances to handle the baseline load of the EKS cluster. Use
- BPurchase Compute Savings Plans for the predicted medium load of the EKS cluster. Use On-
- CPurchase EC2 Instance Savings Plans for the predicted base load of the EKS cluster. Use Spot
- DPurchase Compute Savings Plans for the predicted base load of the EKS cluster. Use Spot
How the community answered
(32 responses)- A3% (1)
- B9% (3)
- C19% (6)
- D69% (22)
Explanation
Fargate usage is best discounted with Compute Savings Plans (they apply to Fargate, unlike EC2 Instance SPs or EC2 RIs). Because the app tolerates interruptions, scaling surges with Fargate Spot minimizes cost. For the persistent RDS MySQL database, a 1-year All Upfront Reserved DB Instance covering baseline demand is the most economical.
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