- (Topic 1)
A company collects temperature, humidity, and atmospheric pressure data in cities across multiple continents. The average volume of data collected per site each day is 500 GB. Each site has a high-speed internet connection. The company's weather forecasting applications are based in a single Region and analyze the data daily.
What is the FASTEST way to aggregate data from all of these global sites?

1. A. Enable Amazon S3 Transfer Acceleration on the destination bucke
2. B. Use multipart uploads to directly upload site data to the destination bucket.
3. C. Upload site data to an Amazon S3 bucket in the closest AWS Regio
4. D. Use S3 cross- Region replication to copy objects to the destination bucket.
5. E. Schedule AWS Snowball jobs daily to transfer data to the closest AWS Regio
6. F. Use S3 cross-Region replication to copy objects to the destination bucket.
7. G. Upload the data to an Amazon EC2 instance in the closest Regio
8. H. Store the data in an Amazon Elastic Block Store (Amazon EBS) volum
9. I. Once a day take an EBS snapshot and copy it to the centralized Regio
10. J. Restore the EBS volume in the centralized Region and run an analysis on the data daily.

Correct Answer: A
You might want to use Transfer Acceleration on a bucket for various reasons, including the following:
You have customers that upload to a centralized bucket from all over the world. You transfer gigabytes to terabytes of data on a regular basis across continents.
You are unable to utilize all of your available bandwidth over the Internet when uploading to Amazon S3.
https://docs.aws.amazon.com/AmazonS3/latest/dev/transfer-acceleration.html
https://aws.amazon.com/s3/transfer-acceleration/#:~:text=S3%20Transfer%20Acceleration%20(S3TA)%20reduces,to%20S3% 20for%20remote%20applications:
"Amazon S3 Transfer Acceleration can speed up content transfers to and from Amazon S3 by as much as 50-500% for long-distance transfer of larger objects. Customers who have either web or mobile applications with widespread users or applications hosted far away from their S3 bucket can experience long and variable upload and download speeds over the Internet"
https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html
"Improved throughput - You can upload parts in parallel to improve throughput."

- (Topic 4)
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?

1. A. Configure an AWS Glue Studio visual canvas to transform the dat
2. B. Share the transformation steps with employees by using AWS Glue jobs.
3. C. Configure Amazon EMR Serverless to transform the dat
4. D. Share the transformation steps with employees by using EMR Serveriess jobs.
5. E. Configure AWS Glue DataBrew to transform the dat
6. F. Share the transformation steps with employees by using DataBrew recipes.
7. G. Create Amazon Athena tables for the dat
8. H. Write Athena SQL queries to transform the dat
9. I. Share the Athena SQL queries with employees.

Correct Answer: C
The most suitable solution for the company’s requirements is to configure AWS Glue DataBrew to transform the data and share the transformation steps with employees by using DataBrew recipes. This solution will provide a prebuilt solution for data transformation that does not require code, and will also provide data lineage and data profiling. The company can easily share the data transformation steps with employees throughout the company by using DataBrew recipes.
AWS Glue DataBrew is a visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data for analytics or machine learning by up to 80% faster. Users can upload their data from various sources, such as Amazon S3, Amazon RDS, Amazon Redshift, Amazon Aurora, or Glue Data Catalog, and use a point- and-click interface to apply over 250 built-in transformations. Users can also preview the results of each transformation step and see how it affects the quality and distribution of the data1.
A DataBrew recipe is a reusable set of transformation steps that can be applied to one or more datasets. Users can create recipes from scratch or use existing ones from the DataBrew recipe library. Users can also export, import, or share recipes with other users or groups within their AWS account or organization2.
DataBrew also provides data lineage and data profiling features that help users understand and improve their data quality. Data lineage shows the source and destination of each dataset and how it is transformed by each recipe step. Data profiling shows various statistics and metrics about each dataset, such as column

- (Topic 3)
A company is migrating its on-premises workload to the AWS Cloud. The company already uses several Amazon EC2 instances and Amazon RDS DB instances. The company wants a solution that automatically starts and stops the EC2 instances and D6 instances outside of business hours. The solution must minimize cost and infrastructure maintenance.
Which solution will meet these requirement?

1. A. Scale the EC2 instances by using elastic resize Scale the DB instances to zero outside of business hours
2. B. Explore AWS Marketplace for partner solutions that will automatically start and stop theEC2 Instances and OB instances on a schedule
3. C. Launch another EC2 instanc
4. D. Configure a crontab schedule to run shell scripts that will start and stop the existing EC2 instances and DB instances on a schedule.
5. E. Create an AWS Lambda function that will start and stop the EC2 instances and DB instances Configure Amazon EventBridge to invoke the Lambda function on a schedule

Correct Answer: D
The most efficient solution for automatically starting and stopping EC2 instances and DB instances on a schedule while minimizing cost and infrastructure maintenance is to create an AWS Lambda function and configure Amazon EventBridge to invoke the function on a schedule.
Option A, scaling EC2 instances by using elastic resize and scaling DB instances to zero outside of business hours, is not feasible as DB instances cannot be scaled to zero.
Option B, exploring AWS Marketplace for partner solutions, may be an option, but it may not be the most efficient solution and could potentially add additional costs.
Option C, launching another EC2 instance and configuring a crontab schedule to run shell scripts that will start and stop the existing EC2 instances and DB instances on a schedule, adds unnecessary infrastructure and maintenance.

- (Topic 1)
A company is preparing to deploy a new serverless workload. A solutions architect must use the principle of least privilege to configure permissions that will be used to run an AWS Lambda function. An Amazon EventBridge (Amazon CloudWatch Events) rule will invoke the function.
Which solution meets these requirements?

1. A. Add an execution role to the function with lambda: InvokeFunction as the action and * asthe principal.
2. B. Add an execution role to the function with lambda: InvokeFunction as the action and Service:amazonaws.com as the principal.
3. C. Add a resource-based policy to the function with lambda:'* as the action and Service:events.amazonaws.com as the principal.
4. D. Add a resource-based policy to the function with lambda: InvokeFunction as the action and Service:events.amazonaws.com as the principal.

Correct Answer: D
https://docs.aws.amazon.com/eventbridge/latest/userguide/resource-based- policies-eventbridge.html#lambda-permissions

- (Topic 3)
A company is designing a shared storage solution for a gaming application that is hosted in the AWS Cloud The company needs the ability to use SMB clients to access data solution must be fully managed.
Which AWS solution meets these requirements?

1. A. Create an AWS DataSync task that shares the data as a mountable file system Mount the file system to the application server
2. B. Create an Amazon EC2 Windows instance Install and configure a Windows file share role on the instance Connect the application server to the file share
3. C. Create an Amazon FSx for Windows File Server file system Attach the file system to the origin server Connect the application server to the file system
4. D. Create an Amazon S3 bucket Assign an IAM role to the application to grant access to the S3 bucket Mount the S3 bucket to the application server

Correct Answer: C
Amazon FSx for Windows File Server (Amazon FSx) is a fully managed, highly available, and scalable file storage solution built on Windows Server that uses the Server Message Block (SMB) protocol. It allows for Microsoft Active Directory integration, data deduplication, and fully managed backups, among other critical enterprise features. https://aws.amazon.com/blogs/storage/accessing-smb-file-shares-remotely-with-amazon- fsx-for-windows-file-server/