A company hosts a data lake on Amazon S3. The data lake ingests data in Apache Parquet format from various data sources. The company uses multiple transformation steps to prepare the ingested data. The steps include filtering of anomalies, normalizing of data to standard date and time values, and generation of aggregates for analyses.
The company must store the transformed data in S3 buckets that data analysts access. The company needs a prebuilt solution for data transformation that does not require code. The solution must provide data lineage and data profiling. The company needs to share the data transformation steps with employees throughout the company.
Which solution will meet these requirements?
A. Configure an AWS Glue Studio visual canvas to transform the data. Share the transformation steps with employees by using AWS Glue jobs.
B. Configure Amazon EMR Serverless to transform the data. Share the transformation steps with employees by using EMR Serverless jobs.
C. Configure AWS Glue DataBrew to transform the data. Share the transformation steps with employees by using DataBrew recipes.
D. Create Amazon Athena tables for the data. Write Athena SQL queries to transform the data. Share the Athena SQL queries with employees.
Show Answer
Correct Answer: C
Explanation: AWS Glue DataBrew is a prebuilt, no-code visual data preparation service designed for cleaning and transforming data in Amazon S3. It supports Parquet, provides built-in transformations for filtering anomalies, normalizing dates, and generating aggregates, and includes data profiling and lineage. Transformation steps are saved as reusable DataBrew recipes that can be shared across the organization.
Question 214
A company collects and processes data from a vendor. The vendor stores its data in an Amazon RDS for MySQL database in the vendor's own AWS account. The company’s VPC does not have an internet gateway, an AWS Direct Connect connection, or an AWS Site-to-Site VPN connection. The company needs to access the data that is in the vendor database.
Which solution will meet this requirement?
A. Instruct the vendor to sign up for the AWS Hosted Connection Direct Connect Program. Use VPC peering to connect the company's VPC and the vendor's VPC.
B. Configure a client VPN connection between the company's VPC and the vendor's VPC. Use VPC peering to connect the company's VPC and the vendor's VPC.
C. Instruct the vendor to create a Network Load Balancer (NLB). Place the NLB in front of the Amazon RDS for MySQL database. Use AWS PrivateLink to integrate the company's VPC and the vendor's VP
D. Use AWS Transit Gateway to integrate the company's VPC and the vendor's VPC. Use VPC peering to connect the company’s VPC and the vendor's VPC.
Show Answer
Correct Answer: C
Explanation: The company has no internet gateway, Direct Connect, or VPN, so connectivity must stay entirely on the AWS private network. AWS PrivateLink is designed for this exact use case: private, cross-account access to a service in another VPC without VPC peering or internet access. The vendor exposes the RDS for MySQL database through a Network Load Balancer as an endpoint service, and the company consumes it via an interface VPC endpoint. Options A, B, and D rely on VPC peering, VPN, Direct Connect, or Transit Gateway, which are unnecessary or violate the constraints.
Question 215
A social media company has workloads that collect and process data. The workloads store the data in on-premises NFS storage. The data store cannot scale fast enough to meet the company’s expanding business needs. The company wants to migrate the current data store to AWS.
Which solution will meet these requirements MOST cost-effectively?
A. Set up an AWS Storage Gateway Volume Gateway. Use an Amazon S3 Lifecycle policy to transition the data to the appropriate storage class.
B. Set up an AWS Storage Gateway Amazon S3 File Gateway. Use an Amazon S3 Lifecycle policy to transition the data to the appropriate storage class.
C. Use the Amazon Elastic File System (Amazon EFS) Standard-Infrequent Access (Standard-IA) storage class. Activate the infrequent access lifecycle policy.
D. Use the Amazon Elastic File System (Amazon EFS) One Zone-Infrequent Access (One Zone-IA) storage class. Activate the infrequent access lifecycle policy.
Show Answer
Correct Answer: B
Explanation: The workloads use on-premises NFS storage and need a scalable, cost-effective migration to AWS with minimal application changes. AWS Storage Gateway Amazon S3 File Gateway provides an NFS interface backed by Amazon S3, allowing existing NFS-based workloads to continue operating while gaining virtually unlimited scalability. Using Amazon S3 with lifecycle policies enables the lowest-cost storage tiers over time. Volume Gateway is for block storage, not NFS, and Amazon EFS (Standard-IA or One Zone-IA) is more expensive than S3 for large-scale data storage and does not directly address hybrid NFS migration needs.
Question 216
A company runs containers in a Kubernetes environment in the company's local data center. The company wants to use Amazon Elastic Kubernetes Service (Amazon EKS) and other AWS managed services. Data must remain locally in the company's data center and cannot be stored in any remote site or cloud to maintain compliance.
Which solution will meet these requirements?
A. Deploy AWS Local Zones in the company's data center.
B. Use an AWS Snowmobile in the company's data center.
C. Install an AWS Outposts rack in the company's data center.
D. Install an AWS Snowball Edge Storage Optimized node in the data center.
Show Answer
Correct Answer: C
Explanation: AWS Outposts installs AWS-managed infrastructure directly in the company’s data center, allowing use of Amazon EKS and other AWS managed services while ensuring that data remains on premises. Local Zones are still AWS locations, Snowmobile is for data transfer, and Snowball Edge is not intended for running full AWS managed services like EKS.
Question 217
A company has an Amazon S3 data lake. The company needs a solution that transforms the data from the data lake and loads the data into a data warehouse every day. The data warehouse must have massively parallel processing (MPP) capabilities.
Data analysts then need to create and train machine learning (ML) models by using SQL commands on the data. The solution must use serverless AWS services wherever possible.
Which solution will meet these requirements?
A. Run a daily Amazon EMR job to transform the data and load the data into Amazon Redshift. Use Amazon Redshift ML to create and train the ML models.
B. Run a daily Amazon EMR job to transform the data and load the data into Amazon Aurora Serverless. Use Amazon Aurora ML to create and train the ML models.
C. Run a daily AWS Glue job to transform the data and load the data into Amazon Redshift Serverless. Use Amazon Redshift ML to create and train the ML models.
D. Run a daily AWS Glue job to transform the data and load the data into Amazon Athena tables. Use Amazon Athena ML to create and train the ML models.
Show Answer
Correct Answer: C
Explanation: The requirements call for a serverless solution that transforms S3 data daily, loads it into a data warehouse with MPP capabilities, and allows ML model creation using SQL. Amazon Redshift is the AWS data warehouse with MPP, and Redshift ML supports creating and training ML models using SQL. AWS Glue is a fully serverless ETL service, and Amazon Redshift Serverless satisfies the serverless preference. EMR-based options are not fully serverless by default, Aurora is not an MPP data warehouse, and Athena is not a data warehouse nor does it support ML training in this way. Therefore, option C best meets all requirements.
Question 218
A company wants to run its payment application on AWS. The application receives payment notifications from mobile devices. Payment notifications require a basic validation before they are sent for further processing.
The backend processing application is long running and requires compute and memory to be adjusted. The company does not want to manage the infrastructure.
Which solution will meet these requirements with the LEAST operational overhead?
A. Create an Amazon Simple Queue Service (Amazon SQS) queue. Integrate the queue with an Amazon EventBridge rule to receive payment notifications from mobile devices. Configure the rule to validate payment notifications and send the notifications to the backend application. Deploy the backend application on Amazon Elastic Kubernetes Service (Amazon EKS) Anywhere. Create a standalone cluster.
B. Create an Amazon API Gateway API. Integrate the API with an AWS Step Functions state machine to receive payment notifications from mobile devices. Invoke the state machine to validate payment notifications and send the notifications to the backend application. Deploy the backend application on Amazon Elastic Kubernetes Service (Amazon EKS). Configure an EKS cluster with self-managed nodes.
C. Create an Amazon Simple Queue Service (Amazon SQS) queue. Integrate the queue with an Amazon EventBridge rule to receive payment notifications from mobile devices. Configure the rule to validate payment notifications and send the notifications to the backend application. Deploy the backend application on Amazon EC2 Spot Instances. Configure a Spot Fleet with a default allocation strategy.
D. Create an Amazon API Gateway API. Integrate the API with AWS Lambda to receive payment notifications from mobile devices. Invoke a Lambda function to validate payment notifications and send the notifications to the backend application. Deploy the backend application on Amazon Elastic Container Service (Amazon ECS). Configure Amazon ECS with an AWS Fargate launch type.
Show Answer
Correct Answer: D
Explanation: The company wants the least operational overhead and does not want to manage infrastructure. Amazon API Gateway and AWS Lambda provide a fully serverless way to receive and perform basic validation of payment notifications. The backend application is long running and needs adjustable compute and memory, which is well suited for Amazon ECS with the AWS Fargate launch type, as Fargate removes the need to manage servers or clusters. Other options involve managing EKS clusters, EC2 instances, or EKS Anywhere, all of which increase operational overhead. Therefore, option D best meets the requirements.
Question 219
A financial company needs to handle highly sensitive data. The company will store the data in an Amazon S3 bucket. The company needs to ensure that the data is encrypted in transit and at rest. The company must manage the encryption keys outside the AWS Cloud.
Which solution will meet these requirements?
A. Encrypt the data in the S3 bucket with server-side encryption (SSE) that uses an AWS Key Management Service (AWS KMS) customer managed key.
B. Encrypt the data in the S3 bucket with server-side encryption (SSE) that uses an AWS Key Management Service (AWS KMS) AWS managed key.
C. Encrypt the data in the S3 bucket with the default server-side encryption (SSE).
D. Encrypt the data at the company's data center before storing the data in the S3 bucket.
Show Answer
Correct Answer: D
Explanation: The requirement states that encryption keys must be managed outside the AWS Cloud. Server-side encryption options (default SSE, SSE-KMS with AWS managed keys, or SSE-KMS with customer managed keys) all rely on AWS-managed infrastructure for key storage and control. By encrypting the data at the company’s data center before uploading it to Amazon S3 (client-side encryption), the company controls and manages the encryption keys entirely outside AWS, while S3 still provides encryption in transit via HTTPS. This satisfies both encryption in transit and at rest with external key management.
Question 220
A company needs to create an AWS Lambda function that will run in a VPC in the company's primary AWS account. The Lambda function needs to access files that the company stores in an Amazon Elastic File System (Amazon EFS) file system. The EFS file system is located in a secondary AWS account. As the company adds files to the file system, the solution must scale to meet the demand.
Which solution will meet these requirements MOST cost-effectively?
A. Create a new EFS file system in the primary account. Use AWS DataSync to copy the contents of the original EFS file system to the new EFS file system.
B. Create a VPC peering connection between the VPCs that are in the primary account and the secondary account.
C. Create a second Lambda function in the secondary account that has a mount that is configured for the file system. Use the primary account's Lambda function to invoke the secondary account's Lambda function.
D. Move the contents of the file system to a Lambda layer. Configure the Lambda layer's permissions to allow the company's secondary account to use the Lambda layer.
Show Answer
Correct Answer: B
Explanation: AWS Lambda can mount an Amazon EFS file system that resides in a different AWS account as long as there is network connectivity between the VPCs and proper permissions. Creating a VPC peering connection between the primary and secondary account VPCs enables direct, scalable, and low-latency access to the existing EFS file system without duplicating data or adding extra services. This avoids additional storage, data transfer, and operational costs, making it the most cost-effective solution.
Question 221
A company needs to extract the names of ingredients from recipe records that are stored as text files in an Amazon S3 bucket. A web application will use the ingredient names to query an Amazon DynamoDB table and determine a nutrition score.
The application can handle non-food records and errors. The company does not have any employees who have machine learning knowledge to develop this solution.
Which solution will meet these requirements MOST cost-effectively?
A. Use S3 Event Notifications to invoke an AWS Lambda function when PutObject requests occur. Program the Lambda function to analyze the object and extract the ingredient names by using Amazon Comprehend. Store the Amazon Comprehend output in the DynamoDB table.
B. Use an Amazon EventBridge rule to invoke an AWS Lambda function when PutObject requests occur. Program the Lambda function to analyze the object by using Amazon Forecast to extract the ingredient names. Store the Forecast output in the DynamoDB table.
C. Use S3 Event Notifications to invoke an AWS Lambda function when PutObject requests occur. Use Amazon Polly to create audio recordings of the recipe records. Save the audio files in the S3 bucket. Use Amazon Simple Notification Service (Amazon SNS) to send a URL as a message to employees. Instruct the employees to listen to the audio files and calculate the nutrition score. Store the ingredient names in the DynamoDB table.
D. Use an Amazon EventBridge rule to invoke an AWS Lambda function when a PutObject request occurs. Program the Lambda function to analyze the object and extract the ingredient names by using Amazon SageMaker. Store the inference output from the SageMaker endpoint in the DynamoDB table.
Show Answer
Correct Answer: A
Explanation: The requirement is to extract ingredient names from text files without in-house ML expertise and at the lowest cost. Amazon Comprehend is a fully managed NLP service that can extract entities and key phrases from text with no model development, making it cost-effective and simple to integrate with Lambda triggered by S3 events. Amazon Forecast is for time-series prediction (not text extraction), Polly adds unnecessary cost and manual work, and SageMaker requires ML expertise and higher operational cost.
Question 222
A company’s website hosted on Amazon EC2 instances processes classified data stored in Amazon S3. Due to security concerns, the company requires a private and secure connection between its EC2 resources and Amazon S3.
Which solution meets these requirements?
A. Set up S3 bucket policies to allow access from a VPC endpoint.
B. Set up an IAM policy to grant read-write access to the S3 bucket.
C. Set up a NAT gateway to access resources outside the private subnet.
D. Set up an access key ID and a secret access key to access the S3 bucket.
Show Answer
Correct Answer: A
Explanation: A private and secure connection from EC2 to Amazon S3 is achieved using an S3 VPC endpoint. By configuring the S3 bucket policy to allow access from that VPC endpoint, traffic stays on the AWS network without traversing the public internet. The other options address authorization or internet access but do not provide a private network path to S3.
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