Question # 1
| A company uses a legacy application to produce data in CSV format The legacy application stores the output data In Amazon S3 The company is deploying a new commercial off-the- shelf (COTS) application that can perform complex SQL queries to analyze data that is stored Amazon Redshift and Amazon S3 only However the COTS application cannot process the csv files that the legacy application produces The company cannot update the legacy application to produce data in another format The company needs to implement a solution so that the COTS application can use the data that the legacy applicator produces.
Which solution will meet these requirements with the LEAST operational overhead? | | A. Create a AWS Glue extract, transform, and load (ETL) job that runs on a schedule. Configure the ETL job to process the .csv files and store the processed data in Amazon Redshit. | | B. Develop a Python script that runs on Amazon EC2 instances to convert the. csv files to sql files invoke the Python script on cron schedule to store the output files in Amazon S3. | | C. Create an AWS Lambda function and an Amazon DynamoDB table. Use an S3 event to invoke the Lambda function. Configure the Lambda function to perform an extract transform, and load (ETL) job to process the .csv files and store the processed data in the DynamoDB table. | | D. Use Amazon EventBridge (Amazon CloudWatch Events) to launch an Amazon EMR cluster on a weekly schedule. Configure the EMR cluster to perform an extract, tractform, and load (ETL) job to process the .csv files and store the processed data in an Amazon Redshift table. |
A. Create a AWS Glue extract, transform, and load (ETL) job that runs on a schedule. Configure the ETL job to process the .csv files and store the processed data in Amazon Redshit.
Explanation:
This solution meets the requirements of implementing a solution so that the COTS application can use the data that the legacy application produces with the least operational overhead. AWS Glue is a fully managed service that provides a serverless ETL platform to prepare and load data for analytics. AWS Glue can process data in various formats, including .csv files, and store the processed data in Amazon Redshift, which is a fully managed data warehouse service that supports complex SQL queries. AWS Glue can run ETL jobs on a schedule, which can automate the data processing and loading process.
Option B is incorrect because developing a Python script that runs on Amazon EC2 instances to convert the .csv files to sql files can increase the operational overhead and complexity, and it may not provide consistent data processing and loading for the COTS application. Option C is incorrect because creating an AWS Lambda function and an Amazon DynamoDB table to process the .csv files and store the processed data in the DynamoDB table does not meet the requirement of using Amazon Redshift as the data source for the COTS application. Option D is incorrect because using Amazon EventBridge (Amazon CloudWatch Events) to launch an Amazon EMR cluster on a weekly schedule to process the .csv files and store the processed data in an Amazon Redshift table can increase the operational overhead and complexity, and it may not provide timely data processing and loading for the COTS application.
Question # 2
| A company has a web application in the AWS Cloud and wants to collect transaction data
in real time. The company wants to prevent data duplication and does not want to manage
infrastructure. The company wants to perform additional processing on the data after the
data is collected.
Which solution will meet these requirements? | | A. Configure an Amazon Simple Queue Service (Amazon SOS) FIFO queue. Configure an
AWS Lambda function with an event source mapping for the FIFO queue to process the
data. | | B. Configure an Amazon Simple Queue Service (Amazon SQS) FIFO queue Use an AWS
Batch job to remove duplicate data from the queue Configure an AWS
Lambda function to process the data. | | C. Use Amazon Kinesis Data Streams to send the Incoming transaction data to an AWS
Batch job that removes duplicate data. Launch an Amazon EC2 instance that runs a
custom script lo process the data. | | D. Set up an AWS Step Functions state machine to send incoming transaction data to an
AWS Lambda function to remove duplicate data. Launch an Amazon EC2 instance that
runs a custom script to process the data. |
A. Configure an Amazon Simple Queue Service (Amazon SOS) FIFO queue. Configure an
AWS Lambda function with an event source mapping for the FIFO queue to process the
data.
Explanation:
Understanding the Requirement: The company needs to collect transaction data in
real time, avoid data duplication, and perform additional processing without
managing infrastructure.
Question # 3
| A company is migrating a document management application to AWS. The application runs
on Linux servers. The company will migrate the application to Amazon EC2 instances in an
Auto Scaling group. The company stores 7 TiB of documents in a shared storage file
system. An external relational database tracks the documents.
Documents are stored once and can be retrieved multiple times for reference at any time.
The company cannot modify the application during the migration. The storage solution must be highly available and must support scaling over time.
Which solution will meet these requirements MOST cost-effectively? | | A. Deploy an EC2 instance with enhanced networking as a shared NFS storage system.
Export the NFS share. Mount the NFS share on the EC2 instances in the
Auto Scaling group. | | B. Create an Amazon S3 bucket that uses the S3 Standard-Infrequent Access (S3
Standard-IA) storage class Mount the S3 bucket on the EC2 instances in the
Auto Scaling group | | C. Deploy an SFTP server endpoint by using AWS Transfer for SFTP and an Amazon S3
bucket. Configure the EC2 instances in the Auto Scaling group to
connect to the SFTP server. | | D. Create an Amazon.. System (Amazon fcFS) file system with mount points in multiple
Availability Zones. Use the bFS Stondard-intrcqucnt Access (Standard-IA) storage class.
Mount the NFS share on the EC2 instances in the Auto Scaling group. |
D. Create an Amazon.. System (Amazon fcFS) file system with mount points in multiple
Availability Zones. Use the bFS Stondard-intrcqucnt Access (Standard-IA) storage class.
Mount the NFS share on the EC2 instances in the Auto Scaling group.
Explanation:
Requirement Analysis: The company needs highly available, scalable storage for a
document management application without modifying the application during
migration.
EFS Overview: Amazon EFS provides scalable file storage that can be mounted
concurrently on multiple EC2 instances across different Availability Zones.
EFS Standard-IA: Using the Standard-IA storage class helps reduce costs for
infrequently accessed data while maintaining high availability and scalability.
Implementation:
Conclusion: This solution meets the high availability, scalability, and costeffectiveness
requirements without needing application modifications.
Question # 4
| A company runs a website that uses a content management system (CMS) on Amazon EC2. The CMS runs on a single EC2 instance and uses an Amazon Aurora MySQL Multi- AZ DB instance for the data tier. Website images are stored on an Amazon Elastic Block Store (Amazon EBS) volume that is mounted inside the EC2 instance.
Which combination of actions should a solutions architect take to improve the performance and resilience of the website? (Select TWO.) | | A. Move the website images into an Amazon S3 bucket that is mounted on every EC2 instance. | | B. Share the website images by using an NFS share from the primary EC2 instance. Mount this share on the other EC2 instances. | | C. Move the website images onto an Amazon Elastic File System (Amazon EFS) file system that is mounted on every EC2 instance. | | D. Create an Amazon Machine Image (AMI) from the existing EC2 instance Use the AMI to provision new instances behind an Application Load Balancer as part of an Auto Scaling group. Configure the Auto Scaling group to maintain a minimum of two instances. Configure an accelerator in AWS Global Accelerator for the website. | | E. Create an Amazon Machine Image (AMI) from the existing EC2 instance. Use the AMI to provision new instances behind an Application Load Balancer as part of an Auto Scaling group. Configure the Auto Scaling group to maintain a minimum of two instances. Configure an Amazon CloudFront distribution for the website. |
C. Move the website images onto an Amazon Elastic File System (Amazon EFS) file system that is mounted on every EC2 instance.
E. Create an Amazon Machine Image (AMI) from the existing EC2 instance. Use the AMI to provision new instances behind an Application Load Balancer as part of an Auto Scaling group. Configure the Auto Scaling group to maintain a minimum of two instances. Configure an Amazon CloudFront distribution for the website.
Explanation: Option C provides moving the website images onto an Amazon EFS file system that is mounted on every EC2 instance. Amazon EFS provides a scalable and fully managed file storage solution that can be accessed concurrently from multiple EC2 instances. This ensures that the website images can be accessed efficiently and consistently by all instances, improving performance In Option E The Auto Scaling group maintains a minimum of two instances, ensuring resilience by automatically replacing any unhealthy instances. Additionally, configuring an Amazon CloudFront distribution for the website further improves performance by caching content at edge locations closer to the end-users, reducing latency and improving content delivery. Hence combining these actions, the website's performance is improved through efficient image storage and content delivery.
Question # 5
| An ecommerce company is building a distributed application that involves several serverless functions and AWS services to complete order-processing tasks. These tasks require manual approvals as part of the workflow A solutions architect needs to design an architecture for the order-processing application The solution must be able to combine multiple AWS Lambda functions into responsive serverless applications The solution also must orchestrate data and services that run on Amazon EC2 instances, containers, or on- premises servers
Which solution will meet these requirements with the LEAST operational overhead?
| | A. Use AWS Step Functions to build the application. | | B. Integrate all the application components in an AWS Glue job | | C. Use Amazon Simple Queue Service (Amazon SQS) to build the application | | D. Use AWS Lambda functions and Amazon EventBridge (Amazon CloudWatch Events) events to build the application |
A. Use AWS Step Functions to build the application.
Explanation:
AWS Step Functions is a fully managed service that makes it easy to build applications by coordinating the components of distributed applications and microservices using visual workflows. With Step Functions, you can combine multiple AWS Lambda functions into responsive serverless applications and orchestrate data and services that run on Amazon EC2 instances, containers, or on-premises servers. Step Functions also allows for manual approvals as part of the workflow. This solution meets all the requirements with the least operational overhead.
Question # 6
| A company has an application that is running on Amazon EC2 instances A solutions
architect has standardized the company on a particular instance family and various
instance sizes based on the current needs of the company.
The company wants to maximize cost savings for the application over the next 3 years. The
company needs to be able to change the instance family and sizes in the next 6 months
based on application popularity and usage
Which solution will meet these requirements MOST cost-effectively? | | A. Compute Savings Plan | | B. EC2 Instance Savings Plan | | C. Zonal Reserved Instances | | D. Standard Reserved Instances |
A. Compute Savings Plan
Understanding the Requirement: The company wants to maximize cost savings for
their application over the next three years, with the flexibility to change the
instance family and sizes within the next six months based on application
popularity and usage.
Question # 7
| A company runs workloads in the AWS Cloud The company wants to centrally collect security data to assess security across the entire company and to improve workload
protection.
Which solution will meet these requirements with the LEAST development effort? | | A. Configure a data lake in AWS Lake Formation Use AWS Glue crawlers to ingest the
security data into the data lake. | | B. Configure an AWS Lambda function to collect the security data in csv format. Upload the
data to an Amazon S3 bucket | | C. Configure a data lake in Amazon Security Lake to collect the security data Upload the
data to an Amazon S3 bucket. | | D. Configure an AWS Database Migration Service (AWS DMS) replication instance to load
the security data into an Amazon RDS cluster |
C. Configure a data lake in Amazon Security Lake to collect the security data Upload the
data to an Amazon S3 bucket.
Explanation:
Understanding the Requirement: The company wants to centrally collect security
data with minimal development effort to assess and improve security across all
workloads.
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