Get SAA-C03 Dumps : Verified AWS Certified Solutions Architect - Associate (SAA-C03)

Deletion protection is a feature of DynamoDB that prevents accidental deletion of tables. When deletion protection is enabled, you cannot delete a table unless you explicitly disable it first. This adds an extra layer of security and reduces the risk of data loss and operational disruption. Deletion protection is easy to enable and disable using the AWS Management Console, the AWS CLI, or the DynamoDB API. This solution has the least operational overhead, as you do not need to create, manage, or invoke any additional resources or services. References:

• Using deletion protection to protect your table
• Preventing Accidental Table Deletion in DynamoDB
• Amazon DynamoDB now supports table deletion protection

The solution that meets the requirements with the most operational efficiency is to configure public subnets in the existing VPC and deploy an MSK cluster in the public subnets. This solution allows the data ingestion solution to be publicly available over the internet without creating a new VPC or deploying a load balancer. The solution also ensures that the data in transit is encrypted by enabling mutual TLS authentication, which requires both the client and the server to present certificates for verification. This solution leverages the public access feature of Amazon MSK, which is available for clusters running Apache Kafka 2.6.0 or later versions1.

The other solutions are not as efficient as the first one because they either create unnecessary resources or do not encrypt the data in transit. Creating a new VPC with public subnets would incur additional costs and complexity for managing network resources and routing. Deploying an ALB or an NLB would also add more costs and latency for the data ingestion solution. Moreover, an ALB or an NLB would not encrypt the data in transit by itself, unless they are configured with HTTPS listeners and certificates, which would require additional steps and maintenance. Therefore, these solutions are not optimal for the given requirements.

References:

• Public access - Amazon Managed Streaming for Apache Kafka

Amazon Cognito user pools provide a secure and scalable user directory for user authentication and management. User pools support various authentication methods, such as username and password, email and password, phone number and password, and social identity providers. User pools also support multi-factor authentication (MFA), which adds an extra layer of security by requiring users to provide a verification code or a biometric factor in addition to their credentials. User pools can also enable risk-based adaptive authentication, which dynamically adjusts the authentication challenge based on the risk level of the sign-in attempt. For example, if a user tries to sign in from an unfamiliar device or location, the user pool can require a stronger authentication factor, such as SMS or email verification code. This feature helps to protect user accounts from unauthorized access and reduce the friction for legitimate users. User pools can scale up to millions of users and integrate with other AWS services, such as Amazon SNS, Amazon SES, AWS Lambda, and AWS KMS.

Amazon Cognito identity pools provide a way to federate identities from multiple identity providers, such as user pools, social identity providers, and corporate identity providers. Identity pools allow users to access AWS resources with temporary, limited-privilege credentials. Identity pools do not provide user authentication or management features, such as MFA or adaptive authentication. Therefore, option B is not correct.

AWS Identity and Access Management (IAM) is a service that helps to manage access to AWS resources. IAM users are entities that represent people or applications that need to interact with AWS. IAM users can be authenticated with a password or an access key. IAM users can also enable MFA for their own accounts, by using the AllowManageOwnUserMFA action in an IAM policy. However, IAM users are not suitable for user authentication for web or mobile applications, as they are intended for administrative purposes. IAM users also do not support adaptive authentication based on risk factors. Therefore, option C is not correct.

AWS IAM Identity Center (AWS Single Sign-On) is a service that enables users to sign in to multiple AWS accounts and applications with a single set of credentials. AWS SSO supports various identity sources, such as AWS SSO directory, AWS Managed Microsoft AD, and external identity providers. AWS SSO also supports MFA for user authentication, which can be configured in the permission sets that define the level of access for each user. However, AWS SSO does not support adaptive authentication based on risk factors. Therefore, option D is not correct.

References:

• Amazon Cognito User Pools
• Adding Multi-Factor Authentication (MFA) to a User Pool
• Risk-Based Adaptive Authentication
• Amazon Cognito Identity Pools
• IAM Users
• Enabling MFA Devices
• AWS Single Sign-On
• How AWS SSO Works

This answer is correct because it meets the requirements of running the ML models as independent microservices that can handle irregular and unpredictable usage patterns. By directing the requests from the API into an Amazon SQS queue, the company can decouple the request processing from the model execution, and ensure that no requests are lost due to spikes in demand. By deploying the models as Amazon ECS services that read from the queue, the company can leverage containers to isolate and package each model as a microservice, and fetch the model data from S3 at startup. By enabling AWS Auto Scaling on Amazon ECS for both the cluster and copies of the service based on the queue size, the company can automatically scale up or down the number of EC2 instances in the cluster and the number of tasks in each service to match the demand and optimize performance.

References:

• https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/welcome.html
• https://docs.aws.amazon.com/AmazonECS/latest/developerguide/Welcome.html
• https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-ecs.html

it allows the company to implement a disaster recovery (DR) solution for the application that has a recovery time objective (RTO) of less than 4 hours and uses the fewest possible AWS resources during normal operations. By creating Amazon Machine Images (AMIs) to back up the EC2 instances and copying the AMIs to a secondary AWS Region, the company can create point-in-time snapshots of the application and store them in a different geographical location. By automating infrastructure deployment in the secondary Region by using AWS CloudFormation, the company can quickly launch a stack of resources from a template in case of a disaster. This is a cost-effective and operationally efficient way to implement a DR solution for EC2 instances. References:

• Amazon Machine Images (AMI)
• Copying an AMI
• AWS CloudFormation
• Working with Stacks