Full Access Amazon Web Services SAA-C03 Tutorials

{

"Version": "2012-10-17",

"Statement": [

{

"Action": [

"s3:ListBucket",

"s3:DeleteObject"

],

"Resource": [

"arn:aws:s3:::"

],

"Effect": "Allow",

},

{

"Action": "s3:*DeleteObject",

"Resource": [

"arn:aws:s3:::/*" # <- The policy clause kludge "added" to match the solution (Q248.1) example

],

"Effect": "Allow"

}

]

}

An Auto Scaling group is a collection of EC2 instances that share similar characteristics and can be scaled in or out automatically based on demand. An Auto Scaling group can be placed behind an Application Load Balancer, which is a type of Elastic Load Balancing load balancer that distributes incoming traffic across multiple targets in multiple Availability Zones. This solution will improve the resiliency of the web tier by providing high availability, scalability, and fault tolerance. An Amazon RDS Multi-AZ deployment is a configuration that automatically creates a primary database instance and synchronously replicates the data to a standby instance in a different Availability Zone. When a failure occurs, Amazon RDS automatically fails over to the standby instance without manual intervention. This solution will improve the resiliency of the database tier by providing data redundancy, backup support, and availability. This combination of steps will meet the requirements with minimal changes to the application during the migration.

References:

1 describes the concept and benefits of an Auto Scaling group.

2 provides an overview of Application Load Balancers and their benefits.

3 explains how Amazon RDS Multi-AZ deployments work and their benefits.

it allows the solutions architect to create a separate organization for the research and development (R&D) business and move its AWS account to the new organization. By inviting the R&D AWS account to be part of the new organization after it has left the prior organization, the solutions architect can ensure that there is no overlap or conflict between the two organizations. The R&D AWS account can accept or decline the invitation to join the new organization. Once accepted, it will be subject to any policies and controls applied by the new organization. References:

Inviting an AWS Account to Join Your Organization

Leaving an Organization as a Member Account

Amazon Athena is a service that allows you to run SQL queries on data stored in Amazon S3. It is serverless, meaning you do not need to provision or manage any infrastructure. You only pay for the queries you run and the amount of data scanned1.

By using Amazon Athena to query your data in Amazon S3, you can achieve the following benefits:

You can run queries for your report without affecting the performance of your Amazon RDS for MySQL DB instance. You can export your data from your DB instance to an S3 bucket and use Athena to query the data in the bucket. This way, you can avoid the overhead and contention of running queries on your DB instance.

You can reduce the cost and complexity of running queries for your report. You do not need to create a read replica or a backup of your DB instance, which would incur additional charges and require maintenance. You also do not need to resize your DB instance to accommodate the additional workload, which would increase your operational overhead.

You can leverage the scalability and flexibility of Amazon S3 and Athena. You can store large amounts of data in S3 and query them with Athena without worrying about capacity or performance limitations. You can also use different formats, compression methods, and partitioning schemes to optimize your data storage and query performance1.