SAP-C02 Exam Dumps - AWS Certified Solutions Architect - Professional

 The company should create a resource-based IAM policy that includes conditions for specific DynamoDB attributes (fine-grained access control). The company should attach the policy to the DynamoDB table. In the marketing team’s account, the company should create an IAM role that has permissions to access the DynamoDB table in the finance team’s account. This solution will meet the requirements because a resource-based IAM policy is a policy that you attach to an AWS resource (such as a DynamoDB table) to control who can access that resource and what actions they can perform on it. You can use IAM policyconditions to specify fine-grained access control for DynamoDB items and attributes. For example, you can allow or deny access to specific attributes of all items in a table by matching on attribute names1. By creating a resource-based policy that allows access to only specific attributes of the DynamoDB table and attaching it to the table, the company can restrict access to confidential data. By creating an IAM role in the marketing team’s account that has permissions to access the DynamoDB table in the finance team’s account, the company can enable cross-account access.

The other options are not correct because:

Creating an SCP to grant the marketing team’s AWS account access to the specific attributes of the DynamoDB table would not work because SCPs are policies that you can use with AWS Organizations to manage permissions in your organization’s accounts. SCPs do not grant permissions; instead, they specify the maximum permissions that identities in an account can have2. SCPs cannot be used to specify fine-grained access control for DynamoDB items and attributes.

Creating an IAM role in the finance team’s account by using IAM policy conditions for specific DynamoDB attributes and establishing trust with the marketing team’s account would not work because IAM roles are identities that you can create in your account that have specific permissions. You can use an IAM role to delegate access to users, applications, or services that don’t normally have access to your AWS resources3. However, creating an IAM role in the finance team’s account would not restrict access to specific attributes of the DynamoDB table; it would only allow cross-account access. The company would still need a resource-based policy attached to the table to enforce fine-grained access control.

Creating an IAM role in the finance team’s account to access the DynamoDB table and using an IAM permissions boundary to limit the access to the specific attributes would not work because IAM permissions boundaries are policies that you use to delegate permissions management to other users. You can use permissions boundaries to limit the maximum permissions that an identity-based policy can grant to an IAM entity (user or role)4. Permissions boundaries cannot be used to specify fine-grained access control for DynamoDB items and attributes.

The best option is to use Amazon SQS and AWS Lambda to create a serverless order processing application. Amazon SQS is a fully managed message queue service that can decouple the order receiving and processing components, making the application more scalable and fault-tolerant. AWS Lambda is a serverless compute service that can automatically scale to handle the incoming messages from the SQS queue and process them according to the business logic. AWS Lambda can also integrate with Amazon DynamoDB to store the processed orders in a fast and flexible NoSQL database. This approach eliminates the need to provision, manage, or scale any servers or containers, and reduces the operational overhead and cost.

Option A is not reliable because using an EC2-hosted database to receive the orders introduces a single point of failure and a scalability bottleneck. EC2 instances also require more management and configuration than serverless services.

Option C is not reliable because using AWS Step Functions to receive the orders adds unnecessary complexity and cost to the application. AWS Step Functions is a service that coordinates multiple AWS services into a serverless workflow, but it is not designed to handle high-volume, sporadic, or unpredictable traffic patterns. AWS Step Functions also charges per state transition, which can be expensive for a large number of orders. Launching an ECS container to process each order also requires more resources and management than invoking a Lambda function.

Option D is not reliable because using Amazon Kinesis Data Streams to receive the orders is not suitable for this use case. Amazon Kinesis Data Streams is a service that enables real-time processing of streaming data at scale, but it is not meant for asynchronous message queuing. Amazon Kinesis Data Streams requires consumers to poll the data from the stream, which can introduce latency and complexity. Amazon Kinesis Data Streams also charges per shard hour, which can be expensive for a sporadic traffic pattern.

Amazon SQS

AWS Lambda

Amazon DynamoDB

AWS Step Functions

Amazon ECS

https://docs.aws.amazon.com/AmazonECR/latest/userguide/ecr-eventbridge.html "Activating an AWS Step Functions state machine"https://docs.aws.amazon.com/step-functions/latest/dg/tutorial-creating-lambda-state-machine.html

A. Modify the application deployment by building a Docker image that contains the application code. Publish the image to Amazon Elastic Container Registry (Amazon ECR). - This step is necessary to package the application code in a container and make it available for running on ECS. B. Create a new Amazon Elastic Container Service (Amazon ECS) task definition with a compatibility type of AWS Fargate. Configure the task definition to use the new image in Amazon Elastic Container Registry (Amazon ECR). Adjust the Lambda function to invoke an ECS task by using the ECS taskdefinition when a new file arrives in Amazon S3.

AWS Global Accelerator is a networking service that helps you improve the availability and performance of the applications that you offer to your global users1. It provides static IP addresses that act as a fixed entry point to your applications and route user traffic to the optimal endpoint based on performance, health, and policies that you configure1. By creating a standard accelerator endpoint for the NLB in each additional Region, you can ensure that customers are automatically directed to the Region that is geographically closest to them2. You can also provide customers with the Global Accelerator IP address, which is anycast from AWS edge locations and does not change when you add or remove endpoints3.

What is AWS Global Accelerator?

Standard accelerator endpoints

AWS Global Accelerator IP addresses

https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/AWSHowTo.cloudwatch.html Elastic Beanstalk automatically uses Amazon CloudWatch to help you monitor your application and environment status. You can navigate to the Amazon CloudWatch console to see your dashboard and get an overview of all of your resources as well as your alarms. You can also choose to view more metrics or add custom metrics.

AWS DMS can migrate data from a source database to a target database in AWS, using change data capture (CDC) to replicate ongoing changes and keep the databases in sync. Setting Amazon S3 as a target allows storing the migrated data in a durable and cost-effective storage service. When the source and destination are fully synchronized, the data can be loaded from Amazon S3 into an Amazon RDS for Microsoft SQL Server DB instance, which is a managed database service that simplifies database administration tasks. References:

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.SQLServer.html

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Target.S3.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_SQLServer.html

Automating the process of increasing service quotas for Amazon EC2 instances in new AWS accounts with minimal operational overhead can be effectively achieved by using Amazon EventBridge, Amazon SNS, and AWS Lambda. An EventBridge rule can detect the creation of a new account and trigger an SNS topic, which in turn invokes a Lambda function. This function can then programmatically request a service quota increase for EC2 instances using the AWS Service Quotas API. This approach streamlines the process, reduces manual intervention, and ensures that new accounts are automatically configured with the desired service quotas.

Amazon EventBridge Documentation: Provides guidance on setting up event rules for detecting AWS account creation.

AWS Lambda Documentation: Details how to create and configure Lambda functions to perform automated tasks, such as requesting service quota increases.

AWS Service Quotas Documentation: Offers information on managing and requesting increases for AWS service quotas programmatically.