Amazon Web Services Updated SAA-C03 Exam Questions and Answers by judah

This solution meets the following requirements:

It is cost-effective, as it only uses serverless components that are charged based on usage and do not require any upfront provisioning or maintenance.

It is scalable, as it can handle any number of recipe records that are uploaded to the S3 bucket without any performance degradation or manual intervention.

It is easy to implement, as it does not require any machine learning knowledge or complex data processing logic. Amazon Comprehend is a natural language processing service that can automatically extract entities such as ingredients from text files. The Lambda function can simply invoke the Comprehend API and store the results in the DynamoDB table.

It is reliable, as it can handle non-food records and errors gracefully. Amazon Comprehend can detect the language and domain of the text files and return an appropriate response. The Lambda function can also implement error handling and logging mechanisms to ensure the data quality and integrity.

References:

Using AWS Lambda with Amazon S3 - AWS Lambda

What Is Amazon Comprehend? - Amazon Comprehend

Working with Tables - Amazon DynamoDB

To migrate the DNS hosting service to a more resilient managed DNS service on AWS, the company should use Amazon Route 53, which is a highly available and scalable cloud DNS web service. Route 53 can host public DNS records for the company’s domain name and provide reliable and secure DNS resolution. To rapidly migrate the DNS hosting service, the company should create a public hosted zone for the domain name in Route 53, which is a container for the domain’s DNS records. Then, the company should import the zone file containing the domain records hosted by the previous provider, which is a text file that defines the DNS records for the domain. This way, the company can quickly transfer the existing DNS records to Route 53 without manually creating them. After importing the zone file, the company should update the domain registrar to use the name servers that Route 53 assigns to the hosted zone. This will ensure that DNS queries for the domain name are routed to Route 53 and resolved by the imported records.

This JSON text is an identity-based policy that grants specific permissions. The IAM principals that the solutions architect can attach this policy to are Role and Group. This is because the policy is written in JSON and is an identity-based policy, which can be attached to IAM principals such as users, groups, and roles. Identity-based policies are permissions policies that you attach to IAM identities (users, groups, or roles) and explicitly state what that identity is allowed (or denied) to do1. Identity-based policies are different from resource-based policies, which define the permissions around the specific resource1. Resource-based policies are attached to a resource, such as an Amazon S3 bucket or an Amazon EC2 instance1. Resource-based policies can also specify a principal, which is the entity that is allowed or denied access to the resource1. Organization is not an IAM principal, but a feature of AWS Organizations that allows you to manage multiple AWS accounts centrally2. Amazon ECS resource and Amazon EC2 resource are not IAM principals, but AWS resources that can have resource-based policies attached to them34.

References:

Identity-based policies and resource-based policies

AWS Organizations

Amazon ECS task role

Amazon EC2 instance profile

The solution that will meet the requirements is to create Amazon Kinesis data streams for data ingestion, create Amazon Kinesis Data Firehose delivery streams to consume the Kinesis data streams, and specify the S3 bucket as the destination of the delivery streams. This solution will allow the company’s application to ingest real-time data from third-party applications and place the ingested raw data in an S3 bucket. Amazon Kinesis data streams are scalable and durable streams that can capture and store data from hundreds of thousands of sources. Amazon Kinesis Data Firehose is a fully managed service that can deliver streaming data to destinations such as S3, Amazon Redshift, Amazon OpenSearch Service, and Splunk. Amazon Kinesis Data Firehose can also transform and compress the data before delivering it to S3.

The other solutions are not as effective as the first one because they either do not support real-time data ingestion, do not work with third-party applications, or do not use S3 as the destination. Creating database migration tasks in AWS Database Migration Service (AWS DMS) will not support real-time data ingestion, as AWS DMS is mainly designed for migrating relational databases, not streaming data. AWS DMS also requires replication instances, source endpoints, and target endpoints to be compatible with specific database engines and versions. Creating and configuring AWS DataSync agents on the EC2 instances will not work with third-party applications, as AWS DataSync is a service that transfers data between on-premises storage systems and AWS storage services, not between applications. AWS DataSync also requires installing agents on the source or destination servers. Creating an AWS Direct Connect connection to the application for data ingestion will not use S3 as the destination, as AWS Direct Connect is a service that establishes a dedicated network connection between on-premises and AWS, not between applications and storage services. AWS Direct Connect also requires a physical connection to an AWS Direct Connect location.

References:

Amazon Kinesis

Amazon Kinesis Data Firehose

AWS Database Migration Service

AWS DataSync

AWS Direct Connect