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Answer: Opt in to AWS Compute Optimizer. Create a Lambda function that calls the Export Lambda Function Recommendations operation. Export the .csv file to an S3 bucket. Create an Amazon Event Bridge rule to schedule the Lambda function to run every 2 weeks.
Answer B is the most efficient solution for the given requirements as it leverages AWS Compute Optimizer, a service designed to provide recommendations for optimal resource allocation and cost savings. Here's why it's the best choice: 1. **AWS Compute Optimizer Integration**: By opting into AWS Compute Optimizer, the company can automatically receive recommendations for optimal Lambda function configurations, including memory settings and cost estimates. This service is specifically designed to analyze the usage patterns of AWS resources and provide actionable recommendations. 2. **Lambda Function for Recommendation Retrieval**: A Lambda function can be created to call the `ExportLambdaFunctionRecommendations` operation provided by AWS Compute Optimizer. This operation will fetch the recommended configurations and costs for the Lambda functions backing the API methods. 3. **CSV Export and S3 Storage**: The Lambda function can then be set up to export the recommendations into a CSV format and store the file in an S3 bucket. This meets the requirement of generating a report and storing it in S3. 4. **Scheduling with Amazon EventBridge**: An Amazon EventBridge rule can be created to schedule the Lambda function to run every two weeks, ensuring that the company receives regular updates on the recommended configurations and cost savings. 5. **Least Development Time**: This solution requires minimal development time as it utilizes existing AWS services and operations. The company does not need to manually extract metrics from CloudWatch Logs or set up complex infrastructure metrics, as suggested in other options. The integration with AWS Compute Optimizer simplifies the process and reduces the amount of custom code required. In summary, option B is the most efficient and time-saving solution as it makes use of AWS Compute Optimizer's capabilities to automate the process of generating cost optimization recommendations for Lambda functions, with minimal custom development required.
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A company runs a new application as a static website in Amazon S3. The company has deployed the application to a production AWS account and uses Amazon CloudFront to deliver the website. The website calls an Amazon API Gateway REST API. An AWS Lambda function backs each API method. The company wants to create a CSV report every 2 weeks to show each API Lambda function’s recommended configured memory, recommended cost, and the price difference between current configurations and the recommendations. The company will store the reports in an S3 bucket. Which solution will meet these requirements with the LEAST development time?
A
Create a Lambda function that extracts metrics data for each API Lambda function from Amazon Cloud Watch Logs for the 2-week period. Collate the data into tabular format. Store the data as a .csv file in an S3 bucket. Create an Amazon Event Bridge rule to schedule the Lambda function to run every 2 weeks.
B
Opt in to AWS Compute Optimizer. Create a Lambda function that calls the Export Lambda Function Recommendations operation. Export the .csv file to an S3 bucket. Create an Amazon Event Bridge rule to schedule the Lambda function to run every 2 weeks.
C
Opt in to AWS Compute Optimizer. Set up enhanced infrastructure metrics. Within the Compute Optimizer console, schedule a job to export the Lambda recommendations to a .csv file. Store the file in an S3 bucket every 2 weeks.
D
Purchase the AWS Business Support plan for the production account. Opt in to AWS Compute Optimizer for AWS Trusted Advisor checks. In the Trusted Advisor console, schedule a job to export the cost optimization checks to a .csv file. Store the file in an S3 bucket every 2 weeks.