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A company uses a service to collect metadata from applications that the company hosts on premises. Consumer devices such as TVs and internet radios access the applications. Many older devices do not support certain HTTP headers and exhibit errors when these headers are present in responses. The company has configured an on-premises load balancer to remove the unsupported headers from responses sent to older devices, which the company identified by the User-Agent headers. The company wants to migrate the service to AWS, adopt serverless technologies, and retain the ability to support the older devices. The company has already migrated the applications into a set of AWS Lambda functions. Which solution will meet these requirements?
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A company runs a new application as a static website in Amazon S3. The company has deployed the application to a production AWS account and uses Amazon CloudFront to deliver the website. The website calls an Amazon API Gateway REST API. An AWS Lambda function backs each API method. The company wants to create a CSV report every 2 weeks to show each API Lambda function’s recommended configured memory, recommended cost, and the price difference between current configurations and the recommendations. The company will store the reports in an S3 bucket. Which solution will meet these requirements with the LEAST development time?
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A company is using Amazon OpenSearch Service to analyze data. The company loads data into an OpenSearch Service cluster with 10 data nodes from an Amazon S3 bucket that uses S3 Standard storage. The data resides in the cluster for 1month for read-only analysis. After 1month, the company deletes the index that contains the data from the cluster. For compliance purposes, the company must retain a copy of all input data. The company is concerned about ongoing costs and asks a solutions architect to recommend a new solution. Which solution will meet these requirements MOST cost-effectively?

Question 352 - SAP-C02 discussion

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A company migrated an application to the AWS Cloud. The application runs on two Amazon EC2 instances behind an Application Load Balancer (ALB). Application data is stored in a MySQL database that runs on an additional EC2 instance. The application's use of the database is read-heavy.

The loads static content from Amazon Elastic Block Store (Amazon EBS) volumes that are attached to each EC2 instance. The static content is updated frequently and must be copied to each EBS volume.

The load on the application changes throughout the day. During peak hours, the application cannot handle all the incoming requests. Trace data shows that the database cannot handle the read load during peak hours.

Which solution will improve the reliability of the application?

A.
Migrate the application to a set of AWS Lambda functions. Set the Lambda functions as targets for the ALB. Create a new single EBS volume for the static content. Configure the Lambda functions to read from the new EBS volume. Migrate the database to an Amazon RDS for MySQL Multi-AZ DB cluster.
Answers
A.
Migrate the application to a set of AWS Lambda functions. Set the Lambda functions as targets for the ALB. Create a new single EBS volume for the static content. Configure the Lambda functions to read from the new EBS volume. Migrate the database to an Amazon RDS for MySQL Multi-AZ DB cluster.
B.
Migrate the application to a set of AWS Step Functions state machines. Set the state machines as targets for the ALB. Create an Amazon Elastic File System (Amazon EFS) file system for the static content. Configure the state machines to read from the EFS file system. Migrate the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance.
Answers
B.
Migrate the application to a set of AWS Step Functions state machines. Set the state machines as targets for the ALB. Create an Amazon Elastic File System (Amazon EFS) file system for the static content. Configure the state machines to read from the EFS file system. Migrate the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance.
C.
Containerize the application. Migrate the application to an Amazon Elastic Container Service (Amazon ECS) Cluster. Use the AWS Fargate launch type for the tasks that host the application. Create a new single EBS volume the static content. Mount the new EBS volume on the ECS duster. Configure AWS Application Auto Scaling on ECS cluster. Set the ECS service as a target for the ALB. Migrate the database to an Amazon RDS for MySOL Multi-AZ DB cluster.
Answers
C.
Containerize the application. Migrate the application to an Amazon Elastic Container Service (Amazon ECS) Cluster. Use the AWS Fargate launch type for the tasks that host the application. Create a new single EBS volume the static content. Mount the new EBS volume on the ECS duster. Configure AWS Application Auto Scaling on ECS cluster. Set the ECS service as a target for the ALB. Migrate the database to an Amazon RDS for MySOL Multi-AZ DB cluster.
D.
Containerize the application. Migrate the application to an Amazon Elastic Container Service (Amazon ECS) cluster. Use the AWS Fargate launch type for the tasks that host the application. Create an Amazon Elastic File System (Amazon EFS) file system for the static content. Mount the EFS file system to each container. Configure AWS Application Auto Scaling on the ECS cluster Set the ECS service as a target for the ALB. Migrate the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance.
Answers
D.
Containerize the application. Migrate the application to an Amazon Elastic Container Service (Amazon ECS) cluster. Use the AWS Fargate launch type for the tasks that host the application. Create an Amazon Elastic File System (Amazon EFS) file system for the static content. Mount the EFS file system to each container. Configure AWS Application Auto Scaling on the ECS cluster Set the ECS service as a target for the ALB. Migrate the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance.
Suggested answer: D

Explanation:

This solution will improve the reliability of the application by addressing the issues of scalability, availability, and performance. Containerizing the application will make it easier to deploy and manage on AWS. Migrating the application to an Amazon ECS cluster will allow the application to run on a fully managed container orchestration service. Using the AWS Fargate launch type for the tasks that host the application will enable the application to run on serverless compute engines that are automatically provisioned and scaled by AWS. Creating an Amazon EFS file system for the static content will provide a scalable and shared storage solution that can be accessed by multiple containers. Mounting the EFS file system to each container will eliminate the need to copy the static content to each EBS volume and ensure that the content is always up to date. Configuring AWS Application Auto Scaling on the ECS cluster will enable the application to scale up and down based on demand or a predefined schedule. Setting the ECS service as a target for the ALB will distribute the incoming requests across multiple tasks in the ECS cluster and improve the availability and fault tolerance of the application. Migrating the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance will provide a fully managed, compatible, and scalable relational database service that can handle high throughput and concurrent connections. Using a reader DB instance will offload some of the read load from the primary DB instance and improve the performance of the database.

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asked 16/09/2024
rita whitfield
38 questions
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