AWS Certified Solutions Architect - Professional
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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 production. Which solution will meet these requirements with the LEAST operational overhead?
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 production. Which solution will meet these requirements with the LEAST operational overhead?
Explanation:
Answer C is the correct solution for the problem described in the question. Here's why:
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Modification of Existing Environment: Modifying the existing environment to use a load-balanced environment type ensures that the setup leverages Elastic Beanstalk's load-balancing features without needing to create a completely new environment. This approach reduces operational overhead because it involves working with the current setup rather than starting from scratch.
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Load-Balanced Environment: By changing to a load-balanced environment, the application will distribute incoming requests across multiple instances. This helps in managing CPU utilization more effectively by sharing the load, thereby reducing the performance bottlenecks that occur when CPU utilization exceeds 85%.
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Selection of All Availability Zones: Selecting all Availability Zones ensures high availability and fault tolerance. By distributing the instances across multiple Availability Zones, the application can handle zone-level failures without significant downtime, ensuring better performance and reliability.
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Scaling Policies: Adding a scale-out rule based on average CPU utilization (over 85% for 5 minutes) automatically adds more instances to handle increased load. This ensures that as CPU demand grows, additional resources are provisioned to maintain performance, thus directly addressing the CPU utilization issue.
This approach balances performance enhancements with minimal operational complexity, making it the most efficient fix among the given options.