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Viewing questions 166-180 out of questions

Questions # 166:

A company is building a software-as-a-service (SaaS) solution on AWS. The company has deployed an Amazon API Gateway REST API with AWS Lambda integration in multiple AWS Regions and in the same production account.

The company offers tiered pricing that gives customers the ability to pay for the capacity to make a certain number of API calls per second. The premium tier offers up to 3,000 calls per second, and customers are identified by a unique API key. Several premium tier customers in various Regions report that they receive error responses of 429 Too Many Requests from multiple API methods during peak usage hours. Logs indicate that the Lambda function is never invoked.

What could be the cause of the error messages for these customers?

Options:

The Lambda function reached its concurrency limit.

The Lambda function its Region limit for concurrency.

The company reached its API Gateway account limit for calls per second.

The company reached its API Gateway default per-method limit for calls per second.

Questions # 167:

A company has an application that runs on Amazon EC2 instances in an Amazon EC2 Auto Scaling group. The company uses AWS CodePipeline to deploy the application. The instances that run in the Auto Scaling group are constantly changing because of scaling events.

When the company deploys new application code versions, the company installs the AWS CodeDeploy agent on any new target EC2 instances and associates the instances with the CodeDeploy deployment group. The application is set to go live within the next 24 hours.

What should a solutions architect recommend to automate the application deployment process with the LEAST amount of operational overhead?

Options:

Configure Amazon EventBridge to invoke an AWS Lambda function when a new EC2 instance is launched into the Auto Scaling group. Code the Lambda function to associate the EC2 instances with the CodeDeploy deployment group.

Write a script to suspend Amazon EC2 Auto Scaling operations before the deployment of new code When the deployment is complete, create a new AMI and configure the Auto Scaling group's launch template to use the new AMI for new launches. Resume Amazon EC2 Auto Scaling operations.

Create a new AWS CodeBuild project that creates a new AMI that contains the new code Configure CodeBuild to update the Auto Scaling group's launch template to the new AMI. Run an Amazon EC2 Auto Scaling instance refresh operation.

Create a new AMI that has the CodeDeploy agent installed. Configure the Auto Scaling group's launch template to use the new AMI. Associate the CodeDeploy deployment group with the Auto Scaling group instead of the EC2 instances.

Questions # 168:

A company has purchased appliances from different vendors. The appliances all have loT sensors. The sensors send status information in the vendors' proprietary formats to a legacy application that parses the information into JSON. The parsing is simple, but each vendor has a unique format. Once daily, the application parses all the JSON records and stores the records in a relational database for analysis.

The company needs to design a new data analysis solution that can deliver faster and optimize costs.

Which solution will meet these requirements?

Options:

Connect the loT sensors to AWS loT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon OuickSight for analysis.

Migrate the application server to AWS Fargate, which will receive the information from loT sensors and parse the information into a relational format. Save the parsed information to Amazon Redshift for analysis.

Create an AWS Transfer for SFTP server. Update the loT sensor code to send the information as a .csv file through SFTP to the server. Use AWS Glue to catalog the files. Use Amazon Athena for analysis.

Use AWS Snowball Edge to collect data from the loT sensors directly to perform local analysis. Periodically collect the data into Amazon Redshift to perform global analysis.

Questions # 169:

A company is using Amazon SageMaker A1 Notebook Instances and SageMaker APIs to train machine learning (ML) models. The SageMaker A1 Notebook Instances are deployed in a VPC that does not have access to or from the internet. Datasets for ML model training are stored in an Amazon S3 bucket. Interface VPC endpoints provide access to Amazon S3 and the SageMaker APIs.

Occasionally, data scientists require access to a private Git repository to update application packages that they use as part of their workflow. The company must provide access to the Git repository while ensuring that the SageMaker A1 Notebook Instances remain isolated from the internet.

Which solution meets these requirements with the LEAST operational overhead?

Options:

Add the Git repository as a resource for SageMaker by referencing the remote URL. Configure AWS Secrets Manager to use Git credentials to access the repository.

Add the Git repository as a resource for SageMaker by referencing the remote URL. Add the username to the URL that is required to access the repository.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet. Configure network ACL rules that allow the SageMaker A1 Notebook Instances access to only the Git repository URL.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet with a network ACL that allows access to only the Git repository URL.

Answer

Explanation

Comprehensive and Detailed Explanation From Exact Extract:

The key requirement is to provide access to a private Git repository while keeping the SageMaker notebook instances isolated from the internet. The environment is intentionally configured without internet access, and connectivity to AWS services is provided through VPC endpoints. Introducing a NAT gateway and routing to the internet would violate the requirement to keep the notebook instances isolated from the internet, and network ACLs cannot reliably restrict outbound access by URL or domain name because NACLs operate at the IP and port level and do not provide DNS-aware URL filtering.

SageMaker supports integrating Git repositories so that notebooks can pull code directly as part of the workflow. When using a private repository, credentials must be handled securely. Using AWS Secrets Manager to store and reference Git credentials allows authentication without embedding usernames and passwords in code or URLs and without granting broad network access. This approach meets the requirement with low operational overhead because it relies on managed SageMaker Git integration and managed secret storage rather than custom networking controls.

Option A uses SageMaker’s Git repository integration with the remote URL and stores credentials in AWS Secrets Manager. This allows notebooks to access the private repository in a controlled, auditable way while preserving the “no internet access” posture of the VPC design (because it does not require adding a NAT gateway or public routes).

Option B is not appropriate because embedding credentials (even just usernames) in URLs is not a secure or robust credential management practice. It also does not solve private authentication in a secure manner and can lead to credential leakage through logs or configuration.

Options C and D are not correct because they require adding a NAT gateway and routing to the internet. That directly conflicts with the requirement that SageMaker notebook instances remain isolated from the internet. Additionally, the proposed restriction mechanism is invalid: network ACLs cannot restrict traffic to a specific URL. They only allow/deny traffic based on IP addresses, ports, and protocols. A Git repository can resolve to multiple IPs, can change IPs, and can use CDNs, making NACL-based IP allowlisting brittle and operationally heavy.

Therefore, integrating the Git repository with SageMaker and using Secrets Manager for credentials is the best solution with the least operational overhead while maintaining internet isolation.

[References:AWS documentation on SageMaker notebook Git repository integration for pulling code from remote repositories.AWS documentation on AWS Secrets Manager for secure storage and retrieval of credentials used by applications and workflows.AWS networking documentation describing that network ACLs operate on IP/port rules and do not support URL-based filtering, and that adding NAT gateway enables internet egress from private subnets., ]

Questions # 170:

A company is running a data-intensive application on AWS. The application runs on a cluster of hundreds of Amazon EC2 instances. A shared file system also runs on several EC2 instances that store 200 TB of data. The application reads and modifies the data on the shared file system and generates a report. The job runs once monthly, reads a subset of the files from the shared file system, and takes about 72 hours to complete. The compute instances scale in an Auto Scaling group, but the instances that host the shared file system run continuously. The compute and storage instances are all in the same AWS Region.

A solutions architect needs to reduce costs by replacing the shared file system instances. The file system must provide high performance access to the needed data for the duration of the 72-hour run.

Which solution will provide the LARGEST overall cost reduction while meeting these requirements?

Options:

Migrate the data from the existing shared file system to an Amazon S3 bucket that uses the S3 Intelligent-Tiering storage class. Before the job runs each month, use Amazon FSx for Lustre to create a new file system with the data from Amazon S3 by using lazy loading. Use the new file system as the shared storage for the duration of the job. Delete the file system when the job is complete.

Migrate the data from the existing shared file system to a large Amazon Elastic Block Store (Amazon EBS) volume with Multi-Attach enabled. Attach the EBS volume to each of the instances by using a user data script in the Auto Scaling group launch template. Use the EBS volume as the shared storage for the duration of the job. Detach the EBS volume when the job is complete.

Migrate the data from the existing shared file system to an Amazon S3 bucket that uses the S3 Standard storage class. Before the job runs each month, use Amazon FSx for Lustre to create a new file system with the data from Amazon S3 by using batch loading. Use the new file system as the shared storage for the duration of the job. Delete the file system when the job is complete.

Migrate the data from the existing shared file system to an Amazon S3 bucket. Before the job runs each month, use AWS Storage Gateway to create a file gateway with the data from Amazon S3. Use the file gateway as the shared storage for the job. Delete the file gateway when the job is complete.

Questions # 171:

A company has applications in an AWS account that is named Source. The account is in an organization in AWS Organizations. One of the applications uses AWS Lambda functions and store’s inventory data in an Amazon Aurora database. The application deploys the Lambda functions by using a deployment package. The company has configured automated backups for Aurora.

The company wants to migrate the Lambda functions and the Aurora database to a new AWS account that is named Target. The application processes critical data, so the company must minimize downtime.

Which solution will meet these requirements?

Options:

Download the Lambda function deployment package from the Source account. Use the deployment package and create new Lambda functions in the Target account. Share the automated Aurora DB cluster snapshot with the Target account.

Download the Lambda function deployment package from the Source account. Use the deployment package and create new Lambda functions in the Target account Share the Aurora DB cluster with the Target account by using AWS Resource Access Manager {AWS RAM). Grant the Target account permission to clone the Aurora DB cluster.

Use AWS Resource Access Manager (AWS RAM) to share the Lambda functions and the Aurora DB cluster with the Target account. Grant the Target account permission to clone the Aurora DB cluster.

Use AWS Resource Access Manager (AWS RAM) to share the Lambda functions with the Target account. Share the automated Aurora DB cluster snapshot with the Target account.

Questions # 172:

A company wants to migrate to AWS. The company is running thousands of VMs in a VMware ESXi environment. The company has no configuration management database and has little Knowledge about the utilization of the VMware portfolio.

A solutions architect must provide the company with an accurate inventory so that the company can plan for a cost-effective migration.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Use AWS Systems Manager Patch Manager to deploy Migration Evaluator to each VM. Review the collected data in Amazon QuickSight. Identify servers that have high utilization. Remove the servers that have high utilization from the migration list. Import the data to AWS Migration Hub.

Export the VMware portfolio to a csv file. Check the disk utilization for each server. Remove servers that have high utilization. Export the data to AWS Application Migration Service. Use AWS Server Migration Service (AWS SMS) to migrate the remaining servers.

Deploy the Migration Evaluator agentless collector to the ESXi hypervisor. Review the collected data in Migration Evaluator. Identify inactive servers. Remove the inactive servers from the migration list. Import the data to AWS Migration Hub.

Deploy the AWS Application Migration Service Agent to each VM. When the data is collected, use Amazon Redshift to import and analyze the data. Use Amazon QuickSight for data visualization.

Questions # 173:

A company stores a static website on Amazon S3. AWS Lambda functions retrieve content from an S3 bucket and serve the content as a website. An Application Load Balancer (ALB) directs incoming traffic to the Lambda functions. An Amazon CloudFront distribution routes requests to the ALB.

The company has set up an AWS Certificate Manager (ACM) certificate on the HTTPS listener of the ALB. The company needs all users to communicate with the website through HTTPS. HTTP users must not receive an error.

Which combination of steps will meet these requirements? (Select THREE.)

Options:

Configure the ALB with a TCP listener on port 443 for passthrough to backend systems.

Create an S3 bucket policy that denies access to the S3 bucket if the aws:SecureTransport request is false.

Configure HTTP to HTTPS redirection on the S3 bucket.

Set the origin protocol policy to HTTPS Only for CloudFront.

Set the viewer protocol policy to HTTPS Only for CloudFront.

Set the viewer protocol policy to Redirect HTTP to HTTPS for CloudFront.

Questions # 174:

A company is running an application that uses an Amazon ElastiCache for Redis cluster as a caching layer A recent security audit revealed that the company has configured encryption at rest for ElastiCache However the company did not configure ElastiCache to use encryption in transit Additionally, users can access the cache without authentication

A solutions architect must make changes to require user authentication and to ensure that the company is using end-to-end encryption

Which solution will meet these requirements?

Options:

Create an AUTH token Store the token in AWS System Manager Parameter Store, as anencrypted parameter Create a new cluster with AUTH and configure encryption in transit Update the application to retrieve the AUTH token from Parameter Store when necessary and to use the AUTH token for authentication

Create an AUTH token Store the token in AWS Secrets Manager Configure the existing cluster to use the AUTH token and configure encryption in transit Update the application to retrieve the AUTH token from Secrets Manager when necessary and to use the AUTH token for authentication.

Create an SSL certificate Store the certificate in AWS Secrets Manager Create a new cluster and configure encryption in transit Update the application to retrieve the SSL certificate from Secrets Manager when necessary and to use the certificate for authentication.

Create an SSL certificate Store the certificate in AWS Systems Manager Parameter Store, as an encrypted advanced parameter Update the existing cluster to configure encryption in transit Update the application to retrieve the SSL certificate from Parameter Store when necessary and to use the certificate for authentication

Questions # 175:

A software as a service (SaaS) based company provides a case management solution to customers A3 part of the solution. The company uses a standalone Simple Mail Transfer Protocol (SMTP) server to send email messages from an application. The application also stores an email template for acknowledgement email messages that populate customer data before the application sends the email message to the customer.

The company plans to migrate this messaging functionality to the AWS Cloud and needs to minimize operational overhead.

Which solution will meet these requirements MOST cost-effectively?

Options:

Set up an SMTP server on Amazon EC2 instances by using an AMI from the AWS Marketplace. Store the email template in an Amazon S3 bucket. Create an AWS Lambda function to retrieve the template from the S3 bucket and to merge the customer data from the application with the template. Use an SDK in the Lambda function to send the email message.

Set up Amazon Simple Email Service (Amazon SES) to send email messages. Store the email template in an Amazon S3 bucket. Create an AWS Lambda function to retrieve the template from the S3 bucket and to merge the customer data from the application with the template. Use an SDK in the Lambda function to send the email message.

Set up an SMTP server on Amazon EC2 instances by using an AMI from the AWS Marketplace. Store the email template in Amazon Simple Email Service (Amazon SES) with parameters for the customer data.Create an AWS Lambda function to call the SES template and to pass customer data to replace the parameters. Use the AWS Marketplace SMTP server to send the email message.

Set up Amazon Simple Email Service (Amazon SES) to send email messages. Store the email template on Amazon SES with parameters for the customer data. Create an AWS Lambda function to call the SendTemplatedEmail API operation and to pass customer data to replace the parameters and the email destination.

Questions # 176:

A video processing company has an application that downloads images from an Amazon S3 bucket, processes the images, stores a transformed image in a second S3 bucket, and updates metadata about the image in an Amazon DynamoDB table. The application is written in Node.js and runs by using an AWS Lambda function. The Lambda function is invoked when a new image is uploaded to Amazon S3.

The application ran without incident for a while. However, the size of the images has grown significantly. The Lambda function is now failing frequently with timeout errors. The function timeout is set to its maximum value. A solutions architect needs to refactor the application’s architecture to prevent invocation failures. The company does not want to manage the underlying infrastructure.

Which combination of steps should the solutions architect take to meet these requirements? (Choose two.)

Options:

Modify the application deployment by building a Docker image that contains the application code. Publish the image to Amazon Elastic Container Registry (Amazon ECR).

Create a new Amazon Elastic Container Service (Amazon ECS) task definition with a compatibility type of AWS Fargate. Configure the task definition to use the new image in Amazon Elastic Container Registry (Amazon ECR). Adjust the Lambda function to invoke an ECS task by using the ECS task definition when a new file arrives in Amazon S3.

Create an AWS Step Functions state machine with a Parallel state to invoke the Lambda function. Increase the provisioned concurrency of the Lambda function.

Create a new Amazon Elastic Container Service (Amazon ECS) task definition with a compatibility type of Amazon EC2. Configure the task definition to use the new image in Amazon Elastic Container Registry (Amazon ECR). Adjust the Lambda function to invoke an ECS task by using the ECS task definition when a new file arrives in Amazon S3.

Modify the application to store images on Amazon Elastic File System (Amazon EFS) and to store metadata on an Amazon RDS DB instance. Adjust the Lambda function to mount the EFS file share.

Questions # 177:

A company is developing and hosting several projects in the AWS Cloud. The projects are developed across multiple AWS accounts under the same organization in AWS Organizations. The company requires the cost lor cloud infrastructure to be allocated to the owning project. The team responsible for all of the AWS accounts has discovered that several Amazon EC2 instances are lacking the Project tag used for cost allocation.

Which actions should a solutions architect take to resolve the problem and prevent it from happening in the future? (Select THREE.)

Options:

Create an AWS Config rule in each account to find resources with missing tags.

Create an SCP in the organization with a deny action for ec2:Runlnstances if the Project tag is missing.

Use Amazon Inspector in the organization to find resources with missing tags.

Create an IAM policy in each account with a deny action for ec2:RunInstances if the Project tag is missing.

Create an AWS Config aggregator for the organization to collect a list of EC2 instances with the missing Project tag.

Use AWS Security Hub to aggregate a list of EC2 instances with the missing Project tag.

Questions # 178:

A company needs to monitor a growing number of Amazon S3 buckets across two AWS Regions. The company also needs to track the percentage of objects that are

encrypted in Amazon S3. The company needs a dashboard to display this information for internal compliance teams.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Create a new S3 Storage Lens dashboard in each Region to track bucket and encryption metrics. Aggregate data from both Region dashboards into a singledashboard in Amazon QuickSight for the compliance teams.

Deploy an AWS Lambda function in each Region to list the number of buckets and the encryption status of objects. Store this data in Amazon S3. Use AmazonAthena queries to display the data on a custom dashboard in Amazon QuickSight for the compliance teams.

Use the S3 Storage Lens default dashboard to track bucket and encryption metrics. Give the compliance teams access to the dashboard directly in the S3console.

Create an Amazon EventBridge rule to detect AWS Cloud Trail events for S3 object creation. Configure the rule to invoke an AWS Lambda function to recordencryption metrics in Amazon DynamoDB. Use Amazon QuickSight to display the metrics in a dashboard for the compliance teams.

Questions # 179:

A company plans to deploy a new private intranet service on Amazon EC2 instances inside a VPC. An AWS Site-to-Site VPN connects the VPC to the company's on-premises network. The new service must communicate with existing on-premises services The on-premises services are accessible through the use of hostnames that reside in the company example DNS zone This DNS zone is wholly hosted on premises and is available only on the company's private network.

A solutions architect must ensure that the new service can resolve hostnames on the company example domain to integrate with existing services.

Which solution meets these requirements?

Options:

Create an empty private zone in Amazon Route 53 for company example Add an additional NS record to the company's on-premises company example zone that points to the authoritative name servers for the new private zone in Route 53

Turn on DNS hostnames for the VPC Configure a new outbound endpoint with Amazon Route 53 Resolver. Create a Resolver rule to forward requests for company example to the on-premises name servers

Turn on DNS hostnames for the VPC Configure a new inbound resolver endpointwith Amazon Route 53 Resolver. Configure the on-premises DNS server to forward requests for company example to the new resolver.

Use AWS Systems Manager to configure a run document that will install a hosts file that contains any required hostnames. Use an Amazon EventBndge rule to run the document when an instance is entering the running state.

Questions # 180:

An application is using an Amazon RDS for MySQL Multi-AZ DB instance in the us-east-1 Region. After a failover test, the application lost the connections to the database and could not re-establish the connections. After a restart of the application, the application re-established the connections.

A solutions architect must implement a solution so that the application can re-establish connections to the database without requiring a restart.

Which solution will meet these requirements?

Options:

Create an Amazon Aurora MySQL Serverless v1 DB instance. Migrate the RDS DB instance to the Aurora Serverless v1 DB instance. Update the connection settings in the application to point to the Aurora reader endpoint.

Create an RDS proxy. Configure the existing RDS endpoint as a target. Update the connection settings in the application to point to the RDS proxy endpoint.

Create a two-node Amazon Aurora MySQL DB cluster. Migrate the RDS DB instance to the Aurora DB cluster. Create an RDS proxy. Configure the existing RDS endpoint as a target. Update the connection settings in the application to point to the RDS proxy endpoint.

Create an Amazon S3 bucket. Export the database to Amazon S3 by using AWS Database Migration Service (AWS DMS). Configure Amazon Athena to use the S3 bucket as a data store. Install the latest Open Database Connectivity (ODBC) driver for the application. Update the connection settings in the application to point to the Athena endpoint

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