Q99 — AWS DOP-C02 Ch.2

Question 99 of 100 | ← Chapter 2

A DevOps engineer is evaluating the most cost-effective way to implement an image processing cluster on AWS. The application cannot run in Docker containers and must run on Amazon EC2. The image processing workload stores checkpoint data on an NFS volume and can tolerate interruptions. Provisioning the cluster software on an EC2 Linux AMI takes 30 minutes.

• A. Use Amazon EFS for checkpoint data. To run the workload, use an EC2 Auto Scaling group with the On-Demand pricing model to temporarily provision EC2 instances.
• B. Use GlusterFS on EC2 instances for checkpoint data. To run batch jobs, manually configure EC2 instances. After job completion, manually terminate the instances.
• C. Use Amazon EFS for checkpoint data. Use EC2 Fleet to launch EC2 Spot Instances and use user data scripts to configure EC2 Linux instances at launch.
• D. Use Amazon EFS for checkpoint data. Use EC2 Fleet to launch EC2 Spot Instances. Create a custom AMI pre-configured with the cluster software and use the latest AMI when launching instances. ✓

Correct Answer: D. Use Amazon EFS for checkpoint data. Use EC2 Fleet to launch EC2 Spot Instances. Create a custom AMI pre-configured with the cluster software and use the latest AMI when launching instances.

Explanation

Among AWS services, EC2 Spot Instances offer the lowest cost and are suitable for interruptible workloads. Using EC2 Fleet with Spot Instances maximizes savings, but relying on user data scripts for configuration (Option C) incurs a 30-minute delay per launch—inefficient under frequent interruptions. A custom AMI (Option D) pre-installs and configures all required software, eliminating startup delays and enabling rapid scaling. Amazon EFS serves as a fully managed, scalable NFS-compatible storage for checkpoint data. Therefore, Option D optimizes both cost (via Spot Instances and EFS) and efficiency (via pre-configured AMI), making it the most cost-effective solution.