QUESTION: 77

A company recently completed the migration from an on-premises data center to the AWS Cloud by using a replatforming strategy. One of the migrated servers is running a legacy Simple Mail Transfer Protocol (SMTP) service that a critical application relies upon. The application sends outbound email messages to the company’s customers. The legacy SMTP server does not support TLS encryption and uses TCP port 25. The application can use SMTP only.

The company decides to use Amazon Simple Email Service (Amazon SES) and to decommission the legacy SMTP server. The company has created and validated the SES domain. The company has lifted the SES limits.

What should the company do to modify the application to send email messages from Amazon SES?

Configure the application to connect to Amazon SES by using TLS Wrapper. Create an IAM role that has ses:SendEmail and ses:SendRawEmail permissions. Attach the IAM role to an Amazon EC2 instance.
Configure the application to connect to Amazon SES by using STARTTLS. Obtain Amazon SES SMTP credentials. Use the credentials to authenticate with Amazon SES.
Configure the application to use the SES API to send email messages. Create an IAM role that has ses:SendEmail and ses:SendRawEmail permissions. Use the IAM role as a service role for Amazon SES.
Configure the application to use AWS SDKs to send email messages. Create an IAM user for Amazon SES. Generate API access keys. Use the access keys to authenticate with Amazon SES.

Answer(s): B

Explanation:

B) Configure the application to connect to Amazon SES by using STARTTLS. Obtain Amazon SES SMTP credentials. Use the credentials to authenticate with Amazon SES.

Amazon Simple Email Service (SES) requires the use of STARTTLS for encryption when sending emails via SMTP. Since the application can only use SMTP, this solution is the most appropriate and secure. The company needs to obtain SMTP credentials for Amazon SES, which are used for authentication. This method ensures that the application can continue to send emails securely using Amazon SES, with minimal changes required.

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QUESTION: 78

A company recently acquired several other companies. Each company has a separate AWS account with a different billing and reporting method. The acquiring company has consolidated all the accounts into one organization in AWS Organizations. However, the acquiring company has found it difficult to generate a cost report that contains meaningful groups for all the teams.

The acquiring company’s finance team needs a solution to report on costs for all the companies through a self-managed application.

Which solution will meet these requirements?

Create an AWS Cost and Usage Report for the organization. Define tags and cost categories in the report. Create a table in Amazon Athena. Create an Amazon QuickSight dataset based on the Athena table. Share the dataset with the finance team.
Create an AWS Cost and Usage Report for the organization. Define tags and cost categories in the report. Create a specialized template in AWS Cost Explorer that the finance department will use to build reports.
Create an Amazon QuickSight dataset that receives spending information from the AWS Price List Query API. Share the dataset with the finance team.
Use the AWS Price List Query API to collect account spending information. Create a specialized template in AWS Cost Explorer that the finance department will use to build reports.

Answer(s): A

Explanation:

A) Create an AWS Cost and Usage Report for the organization. Define tags and cost categories in the report. Create a table in Amazon Athena. Create an Amazon QuickSight dataset based on the Athena table. Share the dataset with the finance team.

This solution allows the finance team to generate meaningful cost reports across all accounts within the organization. By creating an AWS Cost and Usage Report (CUR) and defining tags and cost categories, the company can segment costs by teams or companies. The Athena table allows querying the detailed cost and usage data, and Amazon QuickSight provides visualization and reporting capabilities, which can be shared with the finance team. This solution meets the requirements for self-management and detailed reporting.

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QUESTION: 79

A company runs an IoT platform on AWS. IoT sensors in various locations send data to the company’s Node.js API servers on Amazon EC2 instances running behind an Application Load Balancer. The data is stored in an Amazon RDS MySQL DB instance that uses a 4 TB General Purpose SSD volume.

The number of sensors the company has deployed in the field has increased over time, and is expected to grow significantly. The API servers are consistently overloaded and RDS metrics show high write latency.

Which of the following steps together will resolve the issues permanently and enable growth as new sensors are provisioned, while keeping this platform cost-efficient? (Choose two.)

Resize the MySQL General Purpose SSD storage to 6 TB to improve the volume’s IOPS.
Re-architect the database tier to use Amazon Aurora instead of an RDS MySQL DB instance and add read replicas.
Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data.
Use AWS X-Ray to analyze and debug application issues and add more API servers to match the load.
Re-architect the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance.

Answer(s): C,E

Explanation:

C) Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data.
This step offloads the data ingestion from the API servers, allowing Kinesis Data Streams to handle the large influx of data from the IoT sensors. This will significantly reduce the load on the API servers and make the system more scalable as new sensors are deployed.

E) Re-architect the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance.
Switching to Amazon DynamoDB provides a scalable and high-performance database solution for handling large amounts of IoT data, especially for write-heavy workloads. DynamoDB is a better fit for handling IoT sensor data with minimal latency and automatic scaling.

These two steps together will resolve the performance bottlenecks and allow the system to grow efficiently as new sensors are added.

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QUESTION: 80

A company is building an electronic document management system in which users upload their documents. The application stack is entirely serverless and runs on AWS in the eu-central-1 Region. The system includes a web application that uses an Amazon CloudFront distribution for delivery with Amazon S3 as the origin. The web application communicates with Amazon API Gateway Regional endpoints. The API Gateway APIs call AWS Lambda functions that store metadata in an Amazon Aurora Serverless database and put the documents into an S3 bucket.
The company is growing steadily and has completed a proof of concept with its largest customer. The company must improve latency outside of Europe.

Which combination of actions will meet these requirements? (Choose two.)

Enable S3 Transfer Acceleration on the S3 bucket. Ensure that the web application uses the Transfer Acceleration signed URLs.
Create an accelerator in AWS Global Accelerator. Attach the accelerator to the CloudFront distribution.
Change the API Gateway Regional endpoints to edge-optimized endpoints.
Provision the entire stack in two other locations that are spread across the world. Use global databases on the Aurora Serverless cluster.
Add an Amazon RDS proxy between the Lambda functions and the Aurora Serverless database.

Answer(s): A,C

Explanation:

A) Enable S3 Transfer Acceleration on the S3 bucket. Ensure that the web application uses the Transfer Acceleration signed URLs.
Enabling S3 Transfer Acceleration will improve upload and download speeds by using Amazon CloudFront’s globally distributed edge locations, reducing latency for users outside of Europe.

C) Change the API Gateway Regional endpoints to edge-optimized endpoints.
Edge-optimized API Gateway endpoints use the Amazon CloudFront network to reduce latency for global users by routing requests to the nearest edge location, improving the API response times outside of Europe.

These solutions help address the latency issues for users outside Europe by improving data transfer speeds and API response times.

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QUESTION: 77

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QUESTION: 78

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QUESTION: 79

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QUESTION: 80

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