Q36 — AWS SAP-C02 Ch.2

Question 36 of 75 | ← Chapter 2

Q186. A company developed a pilot application by using AWS Elastic Beanstalk and Java. To save costs during development, the company's development team deployed the application into a single-instance environment Recent tests indicate that the application consumes more CPU than expected. CPU utilization is regularly greater than 85%, which causes some performance bottlenecks. A solutions architect must mitigate the performance issues before the company launches the application to productionWhich solution will meet these requirements with the LEAST operational overhead?

• A. Create a new Elastic Beanstalk application. Select a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the maximum CPU utilization is over 85% for 5 minutes
• B. Create a second Elastic Beanstalk environment. Apply the traffic-splitting deployment policy. Specify a percentage of incoming traffic to direct to the new environment if the average CPU utilization is over 85%for 5 minutes
• C. Modify the existing environment's capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes ✓
• D. Select the Rebuild environment action with the load balancing option. Select all Availability Zones. Add a scale-out rule that will run if the sum CPU utilization is over 85% for 5 minutes

Correct Answer: C. Modify the existing environment's capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes

Explanation

The solution that will meet the requirements with the least operational overhead is: C. Modify the existing environment's capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes. Here's why this option is the most suitable: 1. Operational Overhead: Modifying the existing environment's capacity configuration is a straightforward process that minimizes operational overhead. It involves making changes to the configuration of the existing environment rather than creating new environments or rebuilding existing ones. 2. Load-Balanced Environment: By switching to a load-balanced environment type, the application can distribute the incoming traffic across multiple instances. This helps in mitigating the performance bottlenecks caused by high CPU utilization. 3. Availability Zones: Selecting all Availability Zones ensures that the application can leverage resources across different physical locations, improving fault tolerance and scalability. 4. Scale-Out Rule: Adding a scale-out rule that triggers when the average CPU utilization is over 85% for 5 minutes allows the environment to automatically scale out by adding more instances. This helps in handling increased workload and reduces the chances of performance issues. Option A (Creating a new Elastic Beanstalk application with a load-balanced environment type) would involve creating a new application and environment, which incurs additional overhead and complexity compared to modifying the existing environment. Option B (Creating a second Elastic Beanstalk environment with traffic-splitting deployment) introduces additional complexity by splitting the traffic between two environments. It requires configuring traffic splitting and monitoring average CPU utilization. Option D (Rebuilding the environment with load balancing and scale-out rule) involves rebuilding the environment, which may result in downtime and additional operational effort compared to modifying the existing environment. Therefore, based on the given requirements, option C is the most appropriate choice as it offers a simple and effective solution for mitigating the performance issues by modifying the existing environment's capacity configuration to use a load-balanced environment type and adding a scale-out rule for high CPU utilization.