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Amazon AWS Certified Developer - Associate Sample Questions (Q63-Q68):

NEW QUESTION # 63
A company has developed a new serverless application using AWS Lambda functions that will be deployed using the AWS Serverless Application Model (AWS SAM) CLI.
Which step should the developer complete prior to deploying the application?

A. Create the application environment using the eb create my-env command.
B. Bundle the serverless application using a SAM package.
C. Compress the application to a zip file and upload it into AWS Lambda.
D. Test the new AWS Lambda function by first tracing it m AWS X-Ray.

Answer: B

Explanation:
Explanation
This step should be completed prior to deploying the application because it prepares the application artifacts for deployment. The AWS Serverless Application Model (AWS SAM) is a framework that simplifies building and deploying serverless applications on AWS. The AWS SAM CLI is a command-line tool that helps you create, test, and deploy serverless applications using AWS SAM templates. The sam package command bundles the application artifacts, such as Lambda function code and API definitions, and uploads them to an Amazon S3 bucket. The command also returns a CloudFormation template that is ready to be deployed with the sam deploy command. Compressing the application to a zip file and uploading it to AWS Lambda will not work because it does not use AWS SAM templates or CloudFormation. Testing the new Lambda function by first tracing it in AWS X-Ray will not prepare the application for deployment, but only monitor its performance and errors. Creating the application environment using the eb create my-env command will not work because it is a command for AWS Elastic Beanstalk, not AWS SAM.

NEW QUESTION # 64
A company is building a new application that runs on AWS and uses Amazon API Gateway to expose APIs Teams of developers are working on separate components of the application in parallel The company wants to publish an API without an integrated backend so that teams that depend on the application backend can continue the development work before the API backend development is complete.
Which solution will meet these requirements?

A. Create API Gateway resources and set the integration type value set to HTTP_PROXY. Add mapping templates and deploy the API. Create an AWS Lambda layer that returns various HTTP status codes Associate the Lambda layer with the API deployment
B. Create an EC2 application that returns mocked HTTP responses Create API Gateway resources and set the integration type value to AWS Create an API Gateway stage and deploy the API.
C. Create API Gateway resources and set the integration type value to MOCK Configure the method integration request and integration response to associate a response with an HTTP status code Create an API Gateway stage and deploy the API.
D. Create an AWS Lambda function that returns mocked responses and various HTTP status codes. Create API Gateway resources and set the integration type value to AWS_PROXY Deploy the API.

Answer: C

Explanation:
* API Gateway Mocking: This feature is built for decoupling development dependencies. Here's the process:
* Create resources and methods in your API Gateway.
* Set the integration type to 'MOCK'.
* Define Integration Responses, mapping HTTP status codes to desired mocked responses (JSON, etc.).
* Deployment and Use:
* Create a deployment stage for the API.
* Frontend teams can call this API and get the mocked responses without a real backend.

NEW QUESTION # 65
A company runs an application on AWS The application uses an AWS Lambda function that is configured with an Amazon Simple Queue Service (Amazon SQS) queue called high priority queue as the event source A developer is updating the Lambda function with another SQS queue called low priority queue as the event source The Lambda function must always read up to 10 simultaneous messages from thehigh priority queue before processing messages from low priority queue. The Lambda function must be limited to 100 simultaneous invocations.
Which solution will meet these requirements'?

A. Set the event source mapping batch window to 10 for the high priority queue and to 90 for the low priority queue
B. Set the event source mapping maximum concurrency to 10 for the high priority queue and to 90 for the low priority queue
C. Set the event source mapping batch size to 10 for the high priority queue and to 90 for the low priority queue
D. Set the delivery delay to 0 seconds for the high priority queue and to 10 seconds for the low priority queue

Answer: B

Explanation:
* Lambda Concurrency: The 'maximum concurrency' setting in event source mappings controls the maximum number of simultaneous invocations Lambda allows for that specific source.
* Prioritizing Queues: Setting a lower maximum concurrency for the 'high priority queue' ensures it's processed first while allowing more concurrent invocations from the 'low priority queue'.
* Batching: Batch size settings affect the number of messages Lambda retrieves from a queue per invocation, which is less relevant to the prioritization requirement.

NEW QUESTION # 66
A developer is working on a Python application that runs on Amazon EC2 instances. The developer wants to enable tracing of application requests to debug performance issues in the code.
Which combination of actions should the developer take to achieve this goal? (Select TWO)

A. Install the AWS X-Ray daemon on the EC2 instances.
B. Configure the application to write JSON-formatted togs to /var/log/cloudwatch.
C. Install and configure the AWS X-Ray SDK for Python in the application.
D. Configure the application to write trace data to /Var/log-/xray.
E. Install the Amazon CloudWatch agent on the EC2 instances.

Answer: A,C

Explanation:
Explanation
This solution will meet the requirements by using AWS X-Ray to enable tracing of application requests to debug performance issues in the code. AWS X-Ray is a service that collects data about requests that the applications serve, and provides tools to view, filter, and gain insights into that data. The developer can install the AWS X-Ray daemon on the EC2 instances, which is a software that listens for traffic on UDP port 2000, gathers raw segment data, and relays it to the X-Ray API. The developer can also install and configure the AWS X-Ray SDK for Python in the application, which is a library that enables instrumenting Python code to generate and send trace data to the X-Ray daemon. Option A is not optimal because it will install the Amazon CloudWatch agent on the EC2 instances, which is a software that collects metrics and logs from EC2 instances and on-premises servers, not application performance data. Option C is not optimal because it will configure the application to write JSON-formatted logs to /var/log/cloudwatch, which is not a valid path or destination for CloudWatch logs. Option D is not optimal because it will configure the application to write trace data to
/var/log/xray, which is also not a valid path or destination for X-Ray trace data.
References: [AWS X-Ray], [Running the X-Ray Daemon on Amazon EC2]

NEW QUESTION # 67
A company is building a compute-intensive application that will run on a fleet of Amazon EC2 instances. The application uses attached Amazon Elastic Block Store (Amazon EBS) volumes for storing data. The Amazon EBS volumes will be created at time of initial deployment. The application will process sensitive information. All of the data must be encrypted. The solution should not impact the application's performance.
Which solution will meet these requirements?

A. Configure the application to write all data to an encrypted Amazon S3 bucket.
B. Configure the fleet of EC2 instances to use encrypted EBS volumes to store data.
C. Configure a custom encryption algorithm for the application that will encrypt and decrypt all data.
D. Configure an Amazon Machine Image (AMI) that has an encrypted root volume and store the data to ephemeral disks.

Answer: B

NEW QUESTION # 68
......

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