Question # 1
A developer has an application that stores data in an Amazon S3 bucket. The application uses an HTTP API to store and retrieve objects. When the PutObject API operation adds objects to the S3 bucket the developer must encrypt these objects at rest by using server-side encryption with Amazon S3 managed keys (SSE-S3).
Which solution will meet this requirement?
| A. Create an AWS Key Management Service (AWS KMS) key. Assign the KMS key to the S3 bucket
| B. Set the x-amz-server-side-encryption header when invoking the PutObject API operation.
| C. Provide the encryption key in the HTTP header of every request.
| D. Apply TLS to encrypt the traffic to the S3 bucket.
|
B. Set the x-amz-server-side-encryption header when invoking the PutObject API operation.
Explanation:
Amazon S3 supports server-side encryption, which encrypts data at rest on the server that stores the data. One of the encryption options is SSE-S3, which uses keys managed by S3. To use SSE-S3, the x-amz-server-side-encryption header must be set to AES256 when invoking the PutObject API operation. This instructs S3 to encrypt the object data with SSE-S3 before saving it on disks in its data centers and decrypt it when it is downloaded.
Reference:
Protecting data using server-side encryption with Amazon S3-managed encryption keys (SSE-S3)
Question # 2
A company is building a scalable data management solution by using AWS services to improve the speed and agility of development. The solution will ingest large volumes of data from various sources and will process this data through multiple business rules and transformations.
The solution requires business rules to run in sequence and to handle reprocessing of data if errors occur when the business rules run. The company needs the solution to be scalable and to require the least possible maintenance.
Which AWS service should the company use to manage and automate the orchestration of the data flows to meet these requirements? | | A. AWS Batch
| | B. AWS Step Functions
| | C. AWS Glue
| | D. AWS Lambda |
B. AWS Step Functions
Question # 3
An application runs on multiple EC2 instances behind an ELB. Where is the session data best written so that it can be served reliably across multiple requests?
| A. Write data to Amazon ElastiCache
| B. Write data to Amazon Elastic Block Store
| C. Write data to Amazon EC2 instance Store
| D. Wide data to the root filesystem
|
A. Write data to Amazon ElastiCache
Explanation:
The solution that will meet the requirements is to write data to Amazon ElastiCache. This way, the application can write session data to a fast, scalable, and reliable in-memory data store that can be served reliably across multiple requests. The other options either involve writing data to persistent storage, which is slower and more expensive than in-memory storage, or writing data to the root filesystem, which is not shared among multiple EC2 instances.
Reference: [Reference: Using ElastiCache for session management, ]
Question # 4
| A developer has an application that makes batch requests directly to Amazon DynamoDB by using the BatchGetItem low-level API operation. The responses frequently return values in the UnprocessedKeys element.
Which actions should the developer take to increase the resiliency of the application when the batch response includes values in UnprocessedKeys? (Choose two.) | | A. Retry the batch operation immediately.
| | B. Retry the batch operation with exponential backoff and randomized delay.
| | C. Update the application to use an AWS software development kit (AWS SDK) to make the requests.
| | D. Increase the provisioned read capacity of the DynamoDB tables that the operation accesses. |
B. Retry the batch operation with exponential backoff and randomized delay.
D. Increase the provisioned read capacity of the DynamoDB tables that the operation accesses.
Question # 5
| For a deployment using AWS Code Deploy, what is the run order of the hooks for in-place deployments?
| | A. BeforeInstall -> ApplicationStop -> ApplicationStart -> AfterInstall
| | B. ApplicationStop -> BeforeInstall -> AfterInstall -> ApplicationStart
| | C. BeforeInstall -> ApplicationStop -> ValidateService -> ApplicationStart
| | D. ApplicationStop -> BeforeInstall -> ValidateService -> ApplicationStart |
B. ApplicationStop -> BeforeInstall -> AfterInstall -> ApplicationStart
Question # 6
| A developer is creating an application that will give users the ability to store photos from their cellphones in the cloud. The application needs to support tens of thousands of users. The application uses an Amazon API Gateway REST API that is integrated with AWS Lambda functions to process the photos. The application stores details about the photos in Amazon DynamoDB.
Users need to create an account to access the application. In the application, users must be able to upload photos and retrieve previously uploaded photos. The photos will range in size from 300 KB to 5 MB.
Which solution will meet these requirements with the LEAST operational overhead? | | A. Use Amazon Cognito user pools to manage user accounts. Create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. Use the Lambda function to store the photos and details in the DynamoDB table. Retrieve previously uploaded photos directly from the DynamoDB table. | | B. Use Amazon Cognito user pools to manage user accounts. Create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as part of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key. | | C. Create an IAM user for each user of the application during the sign-up process. Use IAM authentication to access the API Gateway API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as part of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key. | | D. Create a users table in DynamoDB. Use the table to manage user accounts. Create a Lambda authorizer that validates user credentials against the users table. Integrate the Lambda authorizer with API Gateway to control access to the API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as par of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key. |
B. Use Amazon Cognito user pools to manage user accounts. Create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as part of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key.
Question # 7
A developer is creating a new REST API by using Amazon API Gateway and AWS Lambda. The development team tests the API and validates responses for the known use cases before deploying the API to the production environment.
The developer wants to make the REST API available for testing by using API Gateway locally.
Which AWS Serverless Application Model Command Line Interface (AWS SAM CLI) subcommand will meet these requirements?
| A. Sam local invoke
| B. Sam local generate-event
| C. Sam local start-lambda
| D. Sam local start-api
|
D. Sam local start-api
Explanation:
The AWS Serverless Application Model Command Line Interface (AWS SAM CLI) is a command-line tool for local development and testing of Serverless applications2. The sam local start-api subcommand of AWS SAM CLI is used to simulate a REST API by starting a new local endpoint3. Therefore, option D is correct.
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