A company is building a serverless application on AWS. The application uses an AWS Lambda function to process customer orders 24 hours a day, 7 days a week. The Lambda function calls an external vendor's HTTP API to process payments.
During load tests, a developer discovers that the external vendor payment processing API occasionally times out and returns errors. The company expects that some payment processing API calls will return errors.
The company wants the support team to receive notifications in near real time only when the payment processing external API error rate exceed 5% of the total number of transactions in an hour. Developers need to use an existing Amazon Simple Notification Service (Amazon SNS) topic that is configured to notify the support team.
Which solution will meet these requirements?

• A.Publish custom metrics to CloudWatch that record the failures of the external payment processing API calls. Configure a CloudWatch alarm to notify the existing SNS topic when error rate exceeds the specified rate.
• B.Write the results of payment processing API calls to Amazon CloudWatch. Use Amazon CloudWatch Logs Insights to query the CloudWatch logs. Schedule the Lambda function to check the CloudWatch logs and notify the existing SNS topic.
• C.Publish the results of the external payment processing API calls to a new Amazon SNS topic. Subscribe the support team members to the new SNS topic.
• D.Write the results of the external payment processing API calls to Amazon S3. Schedule an Amazon Athena query to run at regular intervals. Configure Athena to send notifications to the existing SNS topic when the error rate exceeds the specified rate.

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A developer is creating a new batch application that will run on an Amazon EC2 instance. The application requires read access to an Amazon S3 bucket. The developer needs to follow security best practices to grant S3 read access to the application.
Which solution meets these requirements?

• A.Add the permissions to an IAM policy. Use IAM web identity federation to access the S3 bucket with the policy.
• B.Add the permissions inline to an IAM group. Attach the group to the EC2 instance profile.
• C.Add the permissions to an IAM policy. Attach the policy to a role. Attach the role to the EC2 instance profile.
• D.Add the permissions to an IAM policy. Attach the policy to a user. Attach the user to the EC2 instance profile.

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A company has built an AWS Lambda function to convert large image files into output files that can be used in a third-party viewer application. The company recently added a new module to the function to improve the output of the generated files. However, the new module has increased the bundle size and has increased the time that is needed to deploy changes to the function code.
How can a developer increase the speed of the Lambda function deployment?

• A.Use Amazon S3 to host the function dependencies.
• B.Use AWS CodeDeploy to deploy the function code.
• C.Use Lambda layers to package and load dependencies.
• D.Increase the memory size of the function.

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A developer created an AWS Lambda function to process data in an application. The function pulls large objects from an Amazon S3 bucket, processes the data, and loads the processed data into a second S3 bucket. Application users have reported slow response times. The developer checks the logs and finds that Lambda function invocations run much slower than expected. The function itself is simple and has a small deployment package. The function initializes quickly. The developer needs to improve the performance of the application. Which solution will meet this requirement with the LEAST operational overhead?

• A.Store the data in an Amazon EFS file system. Mount the file system to a local directory in the function.
• B.Create an Amazon EventBridge rule to schedule invocations of the function every minute.
• C.Configure the function to use ephemeral storage. Upload the objects and process data in the /tmp directory.
• D.Create a Lambda layer to package the function dependencies. Add the layer to the function.

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A developer builds a serverless application on AWS by using Amazon API Gateway, AWS Lambda functions, and Amazon Route 53. During testing, the developer notices errors but cannot immediately locate the root cause.
To identify the errors, the developer needs to search all the application's logs.
What should the developer do to meet these requirements with the LEAST operational overhead?

• A.Set up API Gateway health checks to monitor the application's availability. Use the Amazon CloudWatch PutMetricData API operation to publish the logs to CloudWatch. Search and query the logs by using Amazon Athena.
• B.Set up Route 53 health checks to monitor the application's availability. Turn on AWS CloudTrail logs for all the AWS services that the application uses. Send the logs to a specified Amazon S3 bucket. Use Amazon Athena to query the log files directly from Amazon S3.
• C.Configure all the application's AWS services to publish a real-time feed of log events to an Amazon Kinesis Data Firehose delivery stream. Configure the delivery stream to publish all the logs to an Amazon S3 bucket. Use Amazon OpenSearch Service to search and analyze the logs.
• D.Set up Route 53 health checks to monitor the application's availability. Turn on Amazon CloudWatch Logs for the API Gateway stages to log API requests with a JSON log format. Use CloudWatch Logs Insights to search and analyze the logs from the AWS services that the application uses.

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