A company receives food orders from multiple partners. The company has a microservices application that uses Amazon API Gateway APIs with AWS Lambda integration. Each partner sends orders by calling a customized API that is exposed through API Gateway. The API call invokes a shared Lambda function to process the orders.
Partners need to be notified after the Lambda function processes the orders. Each partner must receive updates for only the partner's own orders. The company wants to add new partners in the future with the fewest code changes possible.
Which solution will meet these requirements in the MOST scalable way?

• A.Create a different Amazon Simple Notification Service (Amazon SNS) topic for each partner. Configure the Lambda function to publish messages for each partner to the partner's SNS topic.
• B.Create a different Lambda function for each partner. Configure the Lambda function to notify each partner's service endpoint directly.
• C.Create an Amazon Simple Notification Service (Amazon SNS) topic. Configure the Lambda function to publish messages with specific attributes to the SNS topic. Subscribe each partner to the SNS topic.
  Apply the appropriate filter policy to the topic subscriptions.
• D.Create one Amazon Simple Notification Service (Amazon SNS) topic. Subscribe all partners to the SNS topic.

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A developer at a company needs to create a small application mat makes the same API call once each flay at a designated time. The company does not have infrastructure in the AWS Cloud yet, but the company wants to implement this functionality on AWS.
Which solution meets these requirements in the MOST operationally efficient manner?

• A.Use a Kubermetes cron job that runs on Amazon Elastic Kubemetes Sen/ice (Amazon EKS)
• B.Use an Amazon Linux crontab scheduled job that runs on Amazon EC2
• C.Use an AWS Lambda function that is invoked by an Amazon EventBridge scheduled event.
• D.Use an AWS Batch job that is submitted to an AWS Batch job queue.

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A company has an application that stores data in Amazon RDS instances. The application periodically experiences surges of high traffic that cause performance problems.
During periods of peak traffic, a developer notices a reduction in query speed in all database queries.
The team's technical lead determines that a multi-threaded and scalable caching solution should be used to offload the heavy read traffic. The solution needs to improve performance.
Which solution will meet these requirements with the LEAST complexity?

• A.Use Amazon ElastiCache for Memcached to offload read requests from the main database.
• B.Replicate the data to Amazon DynamoDB. Set up a DynamoDB Accelerator (DAX) cluster.
• C.Configure the Amazon RDS instances to use Multi-AZ deployment with one standby instance. Offload read requests from the main database to the standby instance.
• D.Use Amazon ElastiCache for Redis to offload read requests from the main database.

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An Amazon Kinesis Data Firehose delivery stream is receiving customer data that contains personally identifiable information. A developer needs to remove pattern-based customer identifiers from the data and store the modified data in an Amazon S3 bucket.
What should the developer do to meet these requirements?

• A.Implement Kinesis Data Firehose data transformation as an AWS Lambda function. Configure the function to remove the customer identifiers. Set an Amazon S3 bucket as the destination of the delivery stream.
• B.Launch an Amazon EC2 instance. Set the EC2 instance as the destination of the delivery stream. Run an application on the EC2 instance to remove the customer identifiers. Store the transformed data in an Amazon S3 bucket.
• C.Create an Amazon OpenSearch Service instance. Set the OpenSearch Service instance as the destination of the delivery stream. Use search and replace to remove the customer identifiers. Export the data to an Amazon S3 bucket.
• D.Create an AWS Step Functions workflow to remove the customer identifiers. As the last step in the workflow, store the transformed data in an Amazon S3 bucket. Set the workflow as the destination of the delivery stream.

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A company is building a web application on AWS. When a customer sends a request, the application will generate reports and then make the reports available to the customer within one hour. Reports should be accessible to the customer for 8 hours. Some reports are larger than 1 MB. Each report is unique to the customer. The application should delete all reports that are older than 2 days.
Which solution will meet these requirements with the LEAST operational overhead?

• A.Generate the reports and then store the reports as Amazon DynamoDB items that have a specified TTL.
  Generate a URL that retrieves the reports from DynamoDB. Provide the URL to customers through the web application.
• B.Generate the reports and then store the reports in an Amazon S3 bucket that uses server-side encryption. Attach the reports to an Amazon Simple Notification Service (Amazon SNS) message.
  Subscribe the customer to email notifications from Amazon SNS.
• C.Generate the reports and then store the reports in an Amazon S3 bucket that uses server-side encryption. Generate a presigned URL that contains an expiration date Provide the URL to customers through the web application. Add S3 Lifecycle configuration rules to the S3 bucket to delete old reports.
• D.Generate the reports and then store the reports in an Amazon RDS database with a date stamp.Generate an URL that retrieves the reports from the RDS database. Provide the URL to customers through the web application. Schedule an hourly AWS Lambda function to delete database records that have expired date stamps.

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