- (Topic 4)
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?

1. 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.
2. B. Use an Amazon EventBridge rule to invoke an AWS Lambda function when PutObject requests occu
3. C. 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.
4. D. Use S3 Event Notifications to invoke an AWS Lambda function when PutObject requests occur Use Amazon Polly to create audio recordings of the recipe record
5. E. 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.
6. F. 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.

Correct Answer: A
This solution meets the following requirements:
✑ It is cost-effective, as it only uses serverless components that are charged based on usage and do not require any upfront provisioning or maintenance.
✑ It is scalable, as it can handle any number of recipe records that are uploaded to the S3 bucket without any performance degradation or manual intervention.
✑ It is easy to implement, as it does not require any machine learning knowledge or complex data processing logic. Amazon Comprehend is a natural language processing service that can automatically extract entities such as ingredients from text files. The Lambda function can simply invoke the Comprehend API and store the results in the DynamoDB table.
✑ It is reliable, as it can handle non-food records and errors gracefully. Amazon Comprehend can detect the language and domain of the text files and return an appropriate response. The Lambda function can also implement error handling and logging mechanisms to ensure the data quality and integrity.
References:
✑ Using AWS Lambda with Amazon S3 - AWS Lambda
✑ What Is Amazon Comprehend? - Amazon Comprehend
✑ Working with Tables - Amazon DynamoDB

- (Topic 3)
A company will deployed a web application on AWS. The company hosts the backend database on Amazon RDS for MySQL with a primary DB instance and five read replicas to support scaling needs. The read replicas must log no more than 1 second bahind the primary DB Instance. The database routinely runs scheduled stored procedures.
As traffic on the website increases, the replicas experinces addtional lag during periods of peak lead. A solutions architect must reduce the replication lag as much as possible. The solutions architect must minimize changes to the applicatin code and must minimize ongoing overhead.
Which solution will meet these requirements?
Migrate the database to Amazon Aurora MySQL. Replace the read replicas with Aurora Replicas, and configure Aurora Auto Scaling. Replace the stored procedures with Aurora
MySQL native functions.
Deploy an Amazon ElasticCache for Redis cluser in front of the database. Modify the application to check the cache before the application queries the database. Repace the stored procedures with AWS Lambda funcions.

1. A. Migrate the database to a MYSQL database that runs on Amazn EC2 instance
2. B. Choose large, compute optimized for all replica node
3. C. Maintain the stored procedures on the EC2 instances.
4. D. Deploy an Amazon ElastiCache for Redis cluster in fornt of the databas
5. E. Modify the application to check the cache before the application queries the databas
6. F. Replace the stored procedures with AWS Lambda functions.
7. G. Migrate the database to a MySQL database that runs on Amazon EC2 instance
8. H. Choose large, compute optimized EC2 instances for all replica nodes, Maintain the stored procedures on the EC2 instances.
9. I. Migrate the database to Amazon DynamoDB, Provision number of read capacity units (RCUs) to support the required throughput, and configure on-demand capacity scalin
10. J. Replace the stored procedures with DynamoDB streams.

Correct Answer: A
Option A is the most appropriate solution for reducing replication lag without significant changes to the application code and minimizing ongoing operational overhead. Migrating the database to Amazon Aurora MySQL allows for improved replication performance and higher scalability compared to Amazon RDS for MySQL. Aurora Replicas provide faster replication, reducing the replication lag, and Aurora Auto Scaling ensures that there are enough Aurora Replicas to handle the incoming traffic. Additionally, Aurora MySQL native functions can replace the stored procedures, reducing the load on the database and improving performance.

- (Topic 4)
A company is planning to use an Amazon DynamoDB table for data storage. The company is concerned about cost optimization. The table will not be used on most mornings. In the evenings, the read and write traffic will often be unpredictable. When traffic spikes occur, they will happen very quickly.
What should a solutions architect recommend?

1. A. Create a DynamoDB table in on-demand capacity mode.
2. B. Create a DynamoDB table with a global secondary index
3. C. Create a DynamoDB table with provisioned capacity and auto scaling.
4. D. Create a DynamoDB table in provisioned capacity mode, and configure it as a global table

Correct Answer: A
Provisioned capacity is best if you have relatively predictable application traffic, run applications whose traffic is consistent, and ramps up or down gradually. On- demand capacity mode is best when you have unknown workloads, unpredictable application traffic and also if you only want to pay exactly for what you use. The on-demand pricing model is ideal for bursty, new, or unpredictable workloads whose traffic can spike in seconds or minutes, and when under-provisioned capacity would impact the user experience. https://docs.aws.amazon.com/wellarchitected/latest/serverless-applications- lens/capacity.html

- (Topic 4)
A company has an AWS Direct Connect connection from its corporate data center to its VPC in the us-east-1 Region. The company recently acquired a corporation that has several VPCs and a Direct Connect connection between its on-premises data center and the eu-west-2 Region. The CIDR blocks for the VPCs of the company and the corporation do not overlap. The company requires connectivity between two Regions and the data centers. The company needs a solution that is scalable while reducing operational overhead.
What should a solutions architect do to meet these requirements?

1. A. Set up inter-Region VPC peering between the VPC in us-east-1 and the VPCs in eu- west-2.
2. B. Create private virtual interfaces from the Direct Connect connection in us-east-1 to the VPCs in eu-west-2.
3. C. Establish VPN appliances in a fully meshed VPN network hosted by Amazon EC2. Use AWS VPN CloudHub to send and receive data between the data centers and each VPC.
4. D. Connect the existing Direct Connect connection to a Direct Connect gatewa
5. E. Route traffic from the virtual private gateways of the VPCs in each Region to the Direct Connect gateway.

Correct Answer: D
This solution meets the requirements because it allows the company to use a single Direct Connect connection to connect to multiple VPCs in different Regions using a Direct Connect gateway. A Direct Connect gateway is a globally available resource that enables you to connect your on-premises network to VPCs in any AWS Region, except the AWS China Regions. You can associate a Direct Connect gateway with a transit gateway or a virtual private gateway in each Region. By routing traffic from the virtual private gateways of the VPCs to the Direct Connect gateway, you can enable inter-Region and on- premises connectivity for your VPCs. This solution is scalable because you can add more VPCs in different Regions to the Direct Connect gateway without creating additional connections. This solution also reduces operational overhead because you do not need to manage multiple VPN appliances, VPN connections, or VPC peering connections. References:
✑ Direct Connect gateways
✑ Inter-Region VPC peering

- (Topic 4)
A company's application runs on Amazon EC2 instances that are in multiple Availability Zones. The application needs to ingest real-time data from third-party applications.
The company needs a data ingestion solution that places the ingested raw data in an Amazon S3 bucket.
Which solution will meet these requirements?

1. A. Create Amazon Kinesis data streams for data ingestio
2. B. Create Amazon Kinesis Data Firehose delivery streams to consume the Kinesis data stream
3. C. Specify the S3 bucket as the destination of the delivery streams.
4. D. Create database migration tasks in AWS Database Migration Service (AWS DMS). Specify replication instances of the EC2 instances as the source endpoint
5. E. Specify the S3 bucket as the target endpoin
6. F. Set the migration type to migrate existing data and replicate ongoing changes.
7. G. Create and configure AWS DataSync agents on the EC2 instance
8. H. Configure DataSynctasks to transfer data from the EC2 instances to the S3 bucket.
9. I. Create an AWS Direct Connect connection to the application for data ingestio
10. J. Create Amazon Kinesis Data Firehose delivery streams to consume direct PUT operations from the applicatio
11. K. Specify the S3 bucket as the destination of the delivery streams.

Correct Answer: A
The solution that will meet the requirements is to create Amazon Kinesis data streams for data ingestion, create Amazon Kinesis Data Firehose delivery streams to consume the Kinesis data streams, and specify the S3 bucket as the destination of the delivery streams. This solution will allow the company’s application to ingest real-time data from third-party applications and place the ingested raw data in an S3 bucket. Amazon Kinesis data streams are scalable and durable streams that can capture and store data from hundreds of thousands of sources. Amazon Kinesis Data Firehose is a fully managed service that can deliver streaming data to destinations such as S3, Amazon Redshift, Amazon OpenSearch Service, and Splunk. Amazon Kinesis Data Firehose can also transform and compress the data before delivering it to S3.
The other solutions are not as effective as the first one because they either do not support real-time data ingestion, do not work with third-party applications, or do not use S3 as the destination. Creating database migration tasks in AWS Database Migration Service (AWS DMS) will not support real-time data ingestion, as AWS DMS is mainly designed for migrating relational databases, not streaming data. AWS DMS also requires replication instances, source endpoints, and target endpoints to be compatible with specific database engines and versions. Creating and configuring AWS DataSync agents on the EC2 instances will not work with third-party applications, as AWS DataSync is a service that transfers data between on-premises storage systems and AWS storage services, not between applications. AWS DataSync also requires installing agents on the source or destination servers. Creating an AWS Direct Connect connection to the application for data ingestion will not use S3 as the destination, as AWS Direct Connect is a service that establishes a dedicated network connection between on-premises and AWS, not between applications and storage services. AWS Direct Connect also requires a physical connection to an AWS Direct Connect location.
References:
✑ Amazon Kinesis
✑ Amazon Kinesis Data Firehose
✑ AWS Database Migration Service
✑ AWS DataSync
✑ AWS Direct Connect