[May 01, 2024] DVA-C02 PDF Dumps is essential on your DVA-C02 Exam Questions Certain Success! [Q67-Q91]

[May 01, 2024] DVA-C02 PDF Dumps is essential on your DVA-C02 Exam Questions Certain Success!

DVA-C02 PDF Questions - Perfect Prospect To Go With DVA-C02 Practice Exam

NEW QUESTION # 67
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. 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.
• B. 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.
• C. 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.
• D. 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.

Answer: C

Explanation:
Explanation
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. The developer can create a DynamoDB table and configure the table with a primary key that consists of the title as the partition key and the release year as the sort key. This will enable querying for a given title and release year efficiently. The developer can also create a global secondary index that uses the genre as the partition key and the title as the sort key. This will enable querying for a given genre efficiently. The developer can store additional properties about the cast and production crew as attributes in the DynamoDB table. These attributes can have different data types and structures, and they do not need to be consistent across items.
References:
[Amazon DynamoDB]
[Working with Queries - Amazon DynamoDB]
[Working with Global Secondary Indexes - Amazon DynamoDB]

NEW QUESTION # 68
An e-commerce web application that shares session state on-premises is being migrated to AWS.
The application must be fault tolerant, natively highly scalable, and any service interruption should not affect the user experience.
What is the best option to store the session state?

• A. Store the session state in Amazon ElastiCache.
• B. Enable session stickiness using elastic load balancers.
• C. Store the session state in Amazon S3.
• D. Store the session state in Amazon CloudFront.

Answer: A

NEW QUESTION # 69
A developer is creating an AWS Lambda function that searches for items from an Amazon DynamoDB table that contains customer contact information. The DynamoDB table items have the customer's email_address as the partition key and additional properties such as customer_type, name and job_title.
The Lambda function runs whenever a user types a new character into the customer_type text input. The developer wants the search to return partial matches of all the email_address property of a particular customer_type. The developer does not want to recreate the DynamoDB table.
What should the developer do to meet these requirements?

• A. Add a global secondary index (GSI) to the DynamoDB table with email_address as the partition key and customer_type as the sort key. Perform a query operation on the GSI by using the begins_with key condition expression with the email_address property.
• B. Add a local secondary index (LSI) to the DynamoDB table with job_title as the partition key and email_address as the sort key. Perform a query operation on the LSI by using the begins_with key condition expression with the email_address property.
• C. Add a global secondary index (GSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key. Perform a query operation on the GSI by using the begins_with key condition expression with the email_address property.
• D. Add a local secondary index (LSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key. Perform a query operation on the LSI by using the begins_with key condition expression with the email_address property.

Answer: C

Explanation:
By adding a global secondary index (GSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key, the developer can perform a query operation on the GSI using the Begins_with key condition expression with the email_address property. This will return partial matches of all email_address properties of a specific customer_type.

NEW QUESTION # 70
An application is using Amazon Cognito user pools and identity pools for secure access. A developer wants to integrate the user-specific file upload and download features in the application with Amazon S3. The developer must ensure that the files are saved and retrieved in a secure manner and that users can access only their own files. The file sizes range from 3 KB to 300 MB.
Which option will meet these requirements with the HIGHEST level of security?

• A. Use an IAM policy within the Amazon Cognito identity prefix to restrict users to use their own folders in Amazon S3.
• B. Use Amazon API Gateway and an AWS Lambda function to upload and download files. Validate each request in the Lambda function before performing the requested operation.
• C. Save the details of the uploaded files in a separate Amazon DynamoDB table. Filter the list of files in the user interface (UI) by comparing the current user ID with the user ID associated with the file in the table.
• D. Use S3 Event Notifications to validate the file upload and download requests and update the user interface (UI).

Answer: A

Explanation:
Explanation
https://docs.aws.amazon.com/cognito/latest/developerguide/amazon-cognito-integrating-user-pools-with-identity

NEW QUESTION # 71
A developer needs to store configuration variables for an application. The developer needs to set an expiration date and time for me configuration. The developer wants to receive notifications. Before the configuration expires. Which solution will meet these requirements with the LEAST operational overhead?

• A. Create an advanced parameter in AWS Systems Manager Parameter Store Create an Amazon EC2 instance with a corn job to expire the configuration and to send notifications.
• B. Create a standard parameter in AWS Systems Manager Parameter Store Create an AWS Lambda function to expire the configuration and to send Amazon Simple Notification Service (Amazon SNS) notifications.
• C. Create an advanced parameter in AWS Systems Manager Parameter Store Set Expiration and Expiration Notification policy types.
• D. Create a standard parameter in AWS Systems Manager Parameter Store Set Expiation and Expiration Notification policy types.

Answer: C

Explanation:
Explanation
This solution will meet the requirements by creating an advanced parameter in AWS Systems Manager Parameter Store, which is a secure and scalable service for storing and managing configuration data and secrets. The advanced parameter allows setting expiration and expiration notification policy types, which enable specifying an expiration date and time for the configuration and receiving notifications before the configuration expires. The Lambda code will be refactored to load the Root CA Cert from the parameter store and modify the runtime trust store outside the Lambda function handler, which will improve performance and reduce latency by avoiding repeated calls to Parameter Store and trust store modifications for each invocation of the Lambda function. Option A is not optimal because it will create a standard parameter in AWS Systems Manager Parameter Store, which does not support expiration and expiration notification policy types. Option B is not optimal because it will create a secret access key and access key ID with permission to access the S3 bucket, which will introduce additional security risks and complexity for storing and managing credentials.
Option D is not optimal because it will create a Docker container from Node.js base image to invoke Lambda functions, which will incur additional costs and overhead for creating and running Docker containers.
References: AWS Systems Manager Parameter Store, [Using SSL/TLS to Encrypt a Connection to a DB Instance]

NEW QUESTION # 72
A company runs a batch processing application by using AWS Lambda functions and Amazon API Gateway APIs with deployment stages for development, user acceptance testing and production A development team needs to configure the APIs in the deployment stages to connect to third-party service endpoints.
Which solution will meet this requirement?

• A. Store the third-party service endpoint for each environment in AWS AppConfig
• B. Encode the third-party service endpoints as query parameters in the API Gateway request URL.
• C. Store the third-party service endpoints in Lambda layers that correspond to the stage
• D. Store the third-party service endpoints in API Gateway stage variables that correspond to the stage

Answer: D

Explanation:
Explanation
API
Gateway stage variables are name-value pairs that can be defined as configuration attributes associated with a deployment stage of a REST API. They act like environment variables and can be used in the API setup and mapping templates. For example, the development team can define a stage variable named endpoint and assign it different values for each stage, such as dev.example.com for development, uat.example.com for user acceptance testing, and prod.example.com for production. Then, the team can use the stage variable value in the integration request URL, such as http://$ { stageVariables.endpoint}/api. This way, the team can use the same API setup with different endpoints at each stage by resetting the stage variable value. The other solutions are either not feasible or not cost-effective. Lambda layers are used to package and load dependencies for Lambda functions, not for storing endpoints. Encoding the endpoints as query parameters would expose them to the public and make the request URL unnecessarily long. Storing the endpoints in AWS AppConfig would incur additional costs and complexity, and would require additional logic to retrieve the values from the configuration store.
References
* Using Amazon API Gateway stage variables
* Setting up stage variables for a REST API deployment
* Setting stage variables using the Amazon API Gateway console

NEW QUESTION # 73
A developer is designing a serverless application with two AWS Lambda functions to process photos. One Lambda function stores objects in an Amazon S3 bucket and stores the associated metadata in an Amazon DynamoDB table. The other Lambda function fetches the objects from the S3 bucket by using the metadata from the DynamoDB table. Both Lambda functions use the same Python library to perform complex computations and are approaching the quota for the maximum size of zipped deployment packages.
What should the developer do to reduce the size of the Lambda deployment packages with the LEAST operational overhead?

• A. Combine the two Lambda functions into one Lambda function. Deploy the Lambda function as a single
  .zip file archive.
• B. Download the Python library to an S3 bucket. Program the Lambda functions to reference the object URLs.
• C. Create a Lambda layer with the required Python library. Use the Lambda layer in both Lambda functions.
• D. Package each Python library in its own .zip file archive. Deploy each Lambda function with its own copy of the library.

Answer: C

Explanation:
Explanation
AWS Lambda is a service that lets developers run code without provisioning or managing servers. Lambda layers are a distribution mechanism for libraries, custom runtimes, and other dependencies. The developer can create a Lambda layer with the required Python library and use the layer in both Lambda functions. This will reduce the size of the Lambda deployment packages and avoid reaching the quota for the maximum size of zipped deployment packages. The developer can also benefit from using layers to manage dependencies separately from function code.
References:
[What Is AWS Lambda? - AWS Lambda]
[AWS Lambda Layers - AWS Lambda]

NEW QUESTION # 74
A company has a social media application that receives large amounts of traffic. User posts and interactions are continuously updated in an Amazon RDS database. The data changes frequently, and the data types can be complex. The application must serve read requests with minimal latency.
The application's current architecture struggles to deliver these rapid data updates efficiently. The company needs a solution to improve the application's performance.
Which solution will meet these requirements?

• A. Create an Amazon ElastiCache for Redis cluster. Update the application code to use a write- through caching strategy and read the data from Redis.
• B. Set up Amazon S3 Transfer Acceleration on the RDS database to enhance the speed of data transfer from the databases to the application.
• C. Add an Amazon CloudFront distribution in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.
• D. Use Amazon DynamoDB Accelerator (DAX) in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.

Answer: C

NEW QUESTION # 75
An online food company provides an Amazon API Gateway HTTP API 1o receive orders for partners. The API is integrated with an AWS Lambda function. The Lambda function stores the orders in an Amazon DynamoDB table.
The company expects to onboard additional partners Some to me panthers require additional Lambda function to receive orders. The company has created an Amazon S3 bucket. The company needs 10 store all orders and updates m the S3 bucket for future analysis How can the developer ensure that an orders and updates are stored to Amazon S3 with the LEAST development effort?

• A. Enable DynamoDB Streams on me DynamoOB table. Create a new lambda function. Associate the stream's Amazon Resource Name (ARN) with the Lambda Function Configure the Lambda function to write to the S3 bucket as records appear in the table's stream.
• B. Use Amazon Kinesis Data Streams to create a new data stream. Modify the Lambda function to publish orders to the oats stream Configure in data stream to write to the S3 bucket.
• C. Create a new Lambda function and a new API Gateway API endpoint. Configure the new Lambda function to write to the S3 bucket. Modify the original Lambda function to post updates to the new API endpoint.
• D. Modify the Lambda function to punish to a new Amazon. Simple Lambda function receives orders.
  Subscribe a new Lambda function to the topic. Configure the new Lambda function to write to the S3 bucket as updates come through the topic.

Answer: A

Explanation:
Explanation
This solution will ensure that all orders and updates are stored to Amazon S3 with the least development effort because it uses DynamoDB Streams to capture changes in the DynamoDB table and trigger a Lambda function to write those changes to the S3 bucket. This way, the original Lambda function and API Gateway API endpoint do not need to be modified, and no additional services are required. Option A is not optimal because it will require more development effort to create a new Lambda function and a new API Gateway API endpoint, and to modify the original Lambda function to post updates to the new API endpoint. Option B is not optimal because it will introduce additional costs and complexity to use Amazon Kinesis Data Streams to create a new data stream, and to modify the Lambda function to publish orders to the data stream. Option D is not optimal because it will require more development effort to modify the Lambda function to publish to a new Amazon SNS topic, and to create and subscribe a new Lambda function to the topic.
References: Using DynamoDB Streams, Using AWS Lambda with Amazon S3

NEW QUESTION # 76
A developer is migrating an application to Amazon Elastic Kubernetes Service (Amazon EKS). The developer migrates the application to Amazon Elastic Container Registry (Amazon ECR) with an EKS cluster.
As part of the application migration to a new backend, the developer creates a new AWS account. The developer makes configuration changes to the application to point the application to the new AWS account and to use new backend resources. The developer successfully tests the changes within the application by deploying the pipeline.
The Docker image build and the pipeline deployment are successful, but the application is still connecting to the old backend. The developer finds that the application's configuration is still referencing the original EKS cluster and not referencing the new backend resources.
Which reason can explain why the application is not connecting to the new resources?

• A. The developer did not successfully create the new AWS account.
• B. The developer did not update the Docker image tag to a new version.
• C. The developer added a new tag to the Docker image.
• D. The developer pushed the changes to a new Docker image tag.

Answer: B

Explanation:
Explanation
The correct answer is C. The developer did not update the Docker image tag to a new version.
C: The developer did not update the Docker image tag to a new version. This is correct. When deploying an application to Amazon EKS, the developer needs to specify the Docker image tag that contains the application code and configuration. If the developer does not update the Docker image tag to a new version after making changes to the application, the EKS cluster will continue to use the old Docker image tag that references the original backend resources. To fix this issue, the developer should update the Docker image tag to a new version and redeploy the application to the EKS cluster.
A: The developer did not successfully create the new AWS account. This is incorrect. The creation of a new AWS account is not related to the application's connection to the backend resources. The developer can use any AWS account to host the EKS cluster and the backend resources, as long as they have the proper permissions and configurations.
B: The developer added a new tag to the Docker image. This is incorrect. Adding a new tag to the Docker image is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.
D: The developer pushed the changes to a new Docker image tag. This is incorrect. Pushing the changes to a new Docker image tag is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.
References:
1: Amazon EKS User Guide, "Deploying applications to your Amazon EKS cluster",
https://docs.aws.amazon.com/eks/latest/userguide/deploying-applications.html
2: Amazon ECR User Guide, "Pushing an image",
https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html
3: Amazon EKS User Guide, "Updating an Amazon EKS cluster",
https://docs.aws.amazon.com/eks/latest/userguide/update-cluster.html

NEW QUESTION # 77
A developer is designing a serverless application for a game in which users register and log in through a web browser. The application makes requests on behalf of users to a set of AWS Lambda functions that run behind an Amazon API Gateway HTTP API.
The developer needs to implement a solution to register and log in users on the application's sign-in page. The solution must minimize operational overhead and must minimize ongoing management of user identities.
Which solution will meet these requirements?

• A. Create an Amazon RDS for SQL Server DB instance to store the users and manage the permissions to the backend resources in AWS.
• B. Program the sign-in page to create users' IAM groups with the IAM roles attached to the groups.
• C. Configure the sign-in page to register and store the users and their passwords in an Amazon DynamoDB table with an attached IAM policy.
• D. Create Amazon Cognito user pools for external social identity providers. Configure IAM roles for the identity pools.

Answer: A

NEW QUESTION # 78
A company has an application that runs as a series of AWS Lambda functions. Each Lambda function receives data from an Amazon Simple Notification Service (Amazon SNS) topic and writes the data to an Amazon Aurora DB instance.
To comply with an information security policy, the company must ensure that the Lambda functions all use a single securely encrypted database connection string to access Aurora.
Which solution will meet these requirements'?

• A. Use Lambda environment variables with a shared AWS Key Management Service (AWS KMS) key for encryption.
• B. Store the credentials in AWS Systems Manager Parameter Store as a secure string parameter.
• C. Use IAM database authentication for Aurora to enable secure database connections for ail the Lambda functions.
• D. Store the credentials and read the credentials from an encrypted Amazon RDS DB instance.

Answer: C

Explanation:
Explanation
This solution will meet the requirements by using IAM database authentication for Aurora, which enables using IAM roles or users to authenticate with Aurora databases instead of using passwords or other secrets.
The developer can use IAM database authentication for Aurora to enable secure database connections for all the Lambda functions that access Aurora DB instance. The developer can create an IAM role with permission to connect to Aurora DB instance and attach it to each Lambda function. The developer can also configure Aurora DB instance to use IAM database authentication and enable encryption in transit using SSL certificates. This way, the Lambda functions can use a single securely encrypted database connection string to access Aurora without needing any secrets or passwords. Option B is not optimal because it will store the credentials and read them from an encrypted Amazon RDS DB instance, which may introduce additional costs and complexity for managing and accessing another RDS DB instance. Option C is not optimal because it will store the credentials in AWS Systems Manager Parameter Store as a secure string parameter, which may require additional steps or permissions to retrieve and decrypt the credentials from Parameter Store.
Option D is not optimal because it will use Lambda environment variables with a shared AWS Key Management Service (AWS KMS) key for encryption, which may not be secure or scalable as environment variables are stored as plain text unless encrypted with AWS KMS.
References: [IAM Database Authentication for MySQL and PostgreSQL], [Using SSL/TLS to Encrypt a Connection to a DB Instance]

NEW QUESTION # 79
A company hosts its application on AWS. The application runs on an Amazon Elastic Container Service (Amazon ECS) cluster that uses AWS Fargate. The cluster runs behind an Application Load Balancer The application stores data in an Amazon Aurora database A developer encrypts and manages database credentials inside the application The company wants to use a more secure credential storage method and implement periodic credential rotation.
Which solution will meet these requirements with the LEAST operational overhead?

• A. Migrate the credentials to AWS Secrets Manager. Encrypt the credentials by using an AWS Key Management Service (AWS KMS) key Turn on secret rotation Use 1AM policies and roles to grant Amazon ECS Fargate permissions to access to AWS Secrets Manager by using keys.
• B. Migrate the secret credentials to Amazon RDS parameter groups. Encrypt the parameter by using an AWS Key Management Service (AWS KMS) key Turn on secret rotation. Use 1AM policies and roles to grant AWS KMS permissions to access Amazon RDS.
• C. Migrate the credentials to AWS Systems Manager Parameter Store. Encrypt the parameter by using an AWS Key Management Service (AWS KMS) key. Turn on secret rotation. Use 1AM policies and roles to grant Amazon ECS Fargate permissions to access to AWS Secrets Manager
• D. Migrate the credentials to ECS Fargate environment variables. Encrypt the credentials by using an AWS Key Management Service (AWS KMS) key Turn on secret rotation. Use 1AM policies and roles to grant Amazon ECS Fargate permissions to access to AWS Secrets Manager.

Answer: A

Explanation:
Explanation
AWS Secrets Manager is a service that helps you store, distribute, and rotate secrets securely. You can use Secrets Manager to migrate your credentials from your application code to a secure and encrypted storage.
You can also enable automatic rotation of your secrets by using AWS Lambda functions or custom logic. You can use IAM policies and roles to grant your Amazon ECS Fargate tasks permissions to access your secrets from Secrets Manager. This solution minimizes the operational overhead of managing your credentials and enhances the security of your application. References
* AWS Secrets Manager: Store, Distribute, and Rotate Credentials Securely | AWS News Blog
* Why You Should Audit and Rotate Your AWS Credentials Periodically - Cloud Academy
* Top 5 AWS root account best practices - TheServerSide

NEW QUESTION # 80
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 Lambda
• B. AWS Glue
• C. AWS Batch
• D. AWS Step Functions

Answer: D

Explanation:
Explanation
https://docs.aws.amazon.com/step-functions/latest/dg/welcome.html

NEW QUESTION # 81
A developer is testing a new file storage application that uses an Amazon CloudFront distribution to serve content from an Amazon S3 bucket. The distribution accesses the S3 bucket by using an origin access identity (OAI). The S3 bucket's permissions explicitly deny access to all other users.
The application prompts users to authenticate on a login page and then uses signed cookies to allow users to access their personal storage directories. The developer has configured the distribution to use its default cache behavior with restricted viewer access and has set the origin to point to the S3 bucket. However, when the developer tries to navigate to the login page, the developer receives a 403 Forbidden error.
The developer needs to implement a solution to allow unauthenticated access to the login page. The solution also must keep all private content secure.
Which solution will meet these requirements?

• A. Add a bucket policy to the S3 bucket to allow read access. Set the resource on the policy to the Amazon Resource Name (ARN) of the login page object in the S3 bucket. Add a CloudFront function to the default cache behavior to redirect unauthorized requests to the login page's S3 URL.
• B. Add a second cache behavior to the distribution with the same origin as the default cache behavior. Set the path pattern for the second cache behavior to the path of the login page, and make viewer access unrestricted. Keep the default cache behavior's settings unchanged.
• C. Add a second origin as a failover origin to the default cache behavior. Point the failover origin to the S3 bucket. Set the path pattern for the primary origin to *, and make viewer access restricted. Set the path pattern for the failover origin to the path of the login page, and make viewer access unrestricted.
• D. Add a second cache behavior to the distribution with the same origin as the default cache behavior. Set the path pattern for the second cache behavior to *, and make viewer access restricted. Change the default cache behavior's path pattern to the path of the login page, and make viewer access unrestricted.

Answer: B

Explanation:
Explanation
The solution that will meet the requirements is to add a second cache behavior to the distribution with the same origin as the default cache behavior. Set the path pattern for the second cache behavior to the path of the login page, and make viewer access unrestricted. Keep the default cache behavior's settings unchanged.
This way, the login page can be accessed without authentication, while all other content remains secure and requires signed cookies. The other options either do not allow unauthenticated access to the login page, or expose private content to unauthorized users.

NEW QUESTION # 82
An application is using Amazon Cognito user pools and identity pools for secure access. A developer wants to integrate the user-specific file upload and download features in the application with Amazon S3. The developer must ensure that the files are saved and retrieved in a secure manner and that users can access only their own files. The file sizes range from 3 KB to 300 MB.
Which option will meet these requirements with the HIGHEST level of security?

• A. Use an IAM policy within the Amazon Cognito identity prefix to restrict users to use their own folders in Amazon S3.
• B. Use Amazon API Gateway and an AWS Lambda function to upload and download files. Validate each request in the Lambda function before performing the requested operation.
• C. Save the details of the uploaded files in a separate Amazon DynamoDB table. Filter the list of files in the user interface (UI) by comparing the current user ID with the user ID associated with the file in the table.
• D. Use S3 Event Notifications to validate the file upload and download requests and update the user interface (UI).

Answer: A

Explanation:
Explanation
https://docs.aws.amazon.com/cognito/latest/developerguide/amazon-cognito-integrating-user-pools-with-identit

NEW QUESTION # 83
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. 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.
• B. 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.
• C. 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.
• 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.

Answer: C

NEW QUESTION # 84
A developer is setting up infrastructure by using AWS CloudFormation. If an error occurs when the resources described in the Cloud Formation template are provisioned, successfully provisioned resources must be preserved. The developer must provision and update the CloudFormation stack by using the AWS CLI.
Which solution will meet these requirements?

• A. Add a --parameters ParameterKey=PreserveResources,ParameterValue=True command line option to the create-stack command and the update-stack command.
• B. Add an --enable-termination-protection command line option to the create-stack command and the update-stack command.
• C. Add a --disable-rollback command line option to the create-stack command and the update-stack command.
• D. Add a --tags Key=PreserveResources,Value=True command line option to the create-stack command and the update-stack command.

Answer: C

Explanation:
The --disable-rollback command-line option will prevent CloudFormation from rolling back the stack to the previous state if an error occurs. This will ensure that successfully provisioned resources are preserved.

NEW QUESTION # 85
A developer is creating an application for a company. The application needs to read the file doc.txt that is placed in the root folder of an Amazon S3 bucket that is named DOC-EXAMPLE- BUCKET. The company's security team requires the principle of least privilege to be applied to the application's IAM policy.
Which IAM policy statement will meet these security requirements?

• A.
• B.
• C.
• D.

Answer: A

NEW QUESTION # 86
A company is using an AWS Lambda function to process records from an Amazon Kinesis data stream. The company recently observed slow processing of the records. A developer notices that the iterator age metric for the function is increasing and that the Lambda run duration is constantly above normal.
Which actions should the developer take to increase the processing speed? (Choose two.)

• A. Increase the timeout of the Lambda function.
• B. Increase the memory that is allocated to the Lambda function.
• C. Decrease the number of shards of the Kinesis data stream.
• D. Increase the number of shards of the Kinesis data stream.
• E. Decrease the timeout of the Lambda function.

Answer: B,D

Explanation:
Explanation
Increasing the number of shards of the Kinesis data stream will increase the throughput and parallelism of the data processing. Increasing the memory that is allocated to the Lambda function will also increase the CPU and network performance of the function, which will reduce the run duration and improve the processing speed. Option B is not correct because decreasing the timeout of the Lambda function will not affect the processing speed, but may cause some records to fail if they exceed the timeout limit. Option D is not correct because decreasing the number of shards of the Kinesis data stream will decrease the throughput and parallelism of the data processing, which will slow down the processing speed. Option E is not correct because increasing the timeout of the Lambda function will not affect the processing speed, but may increase the cost of running the function.
References: [Amazon Kinesis Data Streams Scaling], [AWS Lambda Performance Tuning]

NEW QUESTION # 87
A company is using an AWS Lambda function to process records from an Amazon Kinesis data stream. The company recently observed slow processing of the records. A developer notices that the iterator age metric for the function is increasing and that the Lambda run duration is constantly above normal.
Which actions should the developer take to increase the processing speed? (Choose two.)

• A. Increase the timeout of the Lambda function.
• B. Increase the memory that is allocated to the Lambda function.
• C. Decrease the number of shards of the Kinesis data stream.
• D. Increase the number of shards of the Kinesis data stream.
• E. Decrease the timeout of the Lambda function.

Answer: B,D

Explanation:
https://aws.amazon.com/premiumsupport/knowledge-center/lambda-iterator-age/

NEW QUESTION # 88
A developer is building a serverless application that is based on AWS Lambda. The developer initializes the AWS software development kit (SDK) outside of the Lambda handcar function.
What is the PRIMARY benefit of this action?

• A. Provides better error handling
• B. Improves legibility and systolic convention
• C. Takes advantage of runtime environment reuse
• D. Creates a new SDK instance for each invocation

Answer: C

Explanation:
Explanation
This benefit occurs when initializing the AWS SDK outside of the Lambda handler function because it allows the SDK instance to be reused across multiple invocations of the same function. This can improve performance and reduce latency by avoiding unnecessary initialization overhead. If the SDK is initialized inside the handler function, it will create a new SDK instance for each invocation, which can increase memory usage and execution time.

NEW QUESTION # 89
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 the high 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 size 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 window 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: A

NEW QUESTION # 90
A developer is creating an application that will be deployed on IoT devices. The application will send data to a RESTful API that is deployed as an AWS Lambda function. The application will assign each API request a unique identifier. The volume of API requests from the application can randomly increase at any given time of day.
During periods of request throttling, the application might need to retry requests. The API must be able to handle duplicate requests without inconsistencies or data loss.
Which solution will meet these requirements?

• A. Create an Amazon RDS for MySQL DB instance. Store the unique identifier for each request in a database table. Modify the Lambda function to check the table for the identifier before processing the request.
• B. Create an Amazon DynamoDB table. Store the unique identifier for each request in the table. Modify the Lambda function to return a client error response when the function receives a duplicate request.
• C. Create an Amazon DynamoDB table. Store the unique identifier for each request in the table. Modify the Lambda function to check the table for the identifier before processing the request.
• D. Create an Amazon ElastiCache for Memcached instance. Store the unique identifier for each request in the cache. Modify the Lambda function to check the cache for the identifier before processing the request.

Answer: C

Explanation:
Explanation
Amazon DynamoDB is a fully managed NoSQL database service that can store and retrieve any amount of data with high availability and performance. DynamoDB can handle concurrent requests from multiple IoT devices without throttling or data loss. To prevent duplicate requests from causing inconsistencies or data loss, the Lambda function can use DynamoDB conditional writes to check if the unique identifier for each request already exists in the table before processing the request. If the identifier exists, the function can skip or abort the request; otherwise, it can process the request and store the identifier in the table. Reference: Using conditional writes

NEW QUESTION # 91
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