A developer needs to implement a custom machine learning (ML) library in an application. The size of the library is 15 GB. The size of the library is increasing. The application uses AWS Lambda functions. All the Lambda functions must have access to the library.
Which solution will meet these requirements?

• A.Save the library in Lambda layers. Attach the layers to all Lambda functions.
• B.Save the library as a Lambda container image. Redeploy the Lambda functions with the new image.
• C.Save the library in an Amazon Elastic File System (Amazon EFS) file system. Mount the EFS file system in all the Lambda functions.
• D.Save the library in Amazon S3. Download the library from Amazon S3 inside the Lambda function.

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A developer wants to store information about movies. Each movie has a title, release year, and genre. The movie information also can include additional properties about the cast and production crew. This additional information is inconsistent across movies. For example, one movie might have an assistant director, and another movie might have an animal trainer.
The developer needs to implement a solution to support the following use cases:
For a given title and release year, get all details about the movie that has that title and release year.
For a given title, get all details about all movies that have that title.
For a given genre, get all details about all movies in that genre.
Which data store configuration will meet these requirements?

• A.Create an Amazon DynamoDB table. Configure the table with a primary key that consists of the title as the partition key and the release year as the sort key. Create a global secondary index that uses the genre as the partition key and the title as the sort key.
• B.Create an Amazon DynamoDB table. Configure the table with a primary key that consists of the genre as the partition key and the release year as the sort key. Create a global secondary index that uses the title as the partition key.
• C.On an Amazon RDS DB instance, create a table that contains columns for title, release year, and genre.
  Configure the title as the primary key.
• D.On an Amazon RDS DB instance, create a table where the primary key is the title and all other data is encoded into JSON format as one additional column.

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A developer is incorporating AWS X-Ray into an application that handles personal identifiable information (PII). The application is hosted on Amazon EC2 instances. The application trace messages include encrypted PII and go to Amazon CloudWatch. The developer needs to ensure that no PII goes outside of the EC2 instances.
Which solution will meet these requirements?

• A.Manually instrument the X-Ray SDK in the application code.
• B.Use the X-Ray auto-instrumentation agent.
• C.Use Amazon Macie to detect and hide PII. Call the X-Ray API from AWS Lambda.
• D.Use AWS Distro for Open Telemetry.

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A developer created several AWS Lambda functions that write data to a single Amazon S3 bucket. The developer configured all the Lambda functions to send logs and metrics to Amazon CloudWatch.
The developer receives reports that one of the Lambda functions writes data to the bucket very slowly. The developer needs to measure the latency between the problematic Lambda function and the S3 bucket.
Which solution will meet this requirement?

• A.Enable AWS X-Ray on the Lambda function. In the generated trace map. select the line between Lambda and Amazon S3.
• B.Enable AWS X-Ray on the Lambda function. Select Amazon S3 in the latency graph to view the latency histogram.
• C.Query the Lambda function's log file in Amazon CloudWatch Logs Insights. Return the average of the auto-discovered duration field.
• D.Enable CloudWatch Lambda Insights on the function. View the latency graph that CloudWatch Lambda Insights provides.

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A company runs an application on AWS The application stores data in an Amazon DynamoDB table Some queries are taking a long time to run These slow queries involve an attribute that is not the table's partition key or sort key The amount of data that the application stores in the DynamoDB table is expected to increase significantly. A developer must increase the performance of the queries.
Which solution will meet these requirements'?

• A.Increase the page size for each request by setting the Limit parameter to be higher than the default value Configure the application to retry any request that exceeds the provisioned throughput.
• B.Create a global secondary index (GSI). Set query attribute to be the partition key of the index
• C.Perform a parallel scan operation by issuing individual scan requests in the parameters specify the segment for the scan requests and the total number of segments for the parallel scan.
• D.Turn on read capacity auto scaling for the DynamoDB table. Increase the maximum read capacity units (RCUs).

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