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A solutions architect is developing a multiple-subnet VPC architecture. The solution will consist of six subnets in two Availability Zones. The subnets are defined as public, private and dedicated for databases. Only the Amazon EC2 instances running in the private subnets should be able to access a database. Which solution meets these requirements?
A company creates operations data and stores the data in an Amazon S3 bucket for the company's annual audit, an external consultant needs to access an annual report that is stored in the S3 bucket. The external consultant needs to access the report for 7 days. The company must implement a solution to allow the external consultant access to only the report. Which solution will meet these requirements with the MOST operational efficiency?
A company stores customer data in a multitenant Amazon S3 bucket. Each customer's data is stored in a prefix that is unique to the customer. The company needs to migrate data for specific customers to a new. dedicated S3 bucket that is in the same AWS Region as the source bucket. The company must preserve object metadata such as creation date and version IDs. After the migration is finished, the company must delete the source data for the migrated customers from the original multitenant S3 bucket. Which combination of solutions will meet these requirements with the LEAST overhead? (Select THREE.)
A development team uses multiple AWS accounts for its development, staging, and production environments. Team members have been launching large Amazon EC2 instances that are underutilized. A solutions architect must prevent large instances from being launched in all accounts. How can the solutions architect meet this requirement with the LEAST operational overhead?
A company stores data in an on-premises Oracle relational database. The company needs to make the data available in Amazon Aurora PostgreSQL for analysis The company uses an AWS Site-to-Site VPN connection to connect its on-premises network to AWS. The company must capture the changes that occur to the source database during the migration to Aurora PostgreSQL. Which solution will meet these requirements?
A company hosts its multi-tier, public web application in the AWS Cloud. The web application runs on Amazon EC2 instances, and its database runs on Amazon RDS. The company is anticipating a large increase in sales during an upcoming holiday weekend. A solutions architect needs to build a solution to analyze the performance of the web application with a granularity of no more than 2 minutes. What should the solutions architect do to meet this requirement?
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A company recently signed a contract with an AWS Managed Service Provider (MSP) Partner for help with an application migration initiative. A solutions architect needs to share an Amazon Machine Image (AMI) from an existing AWS account with the MSP Partner's AWS account. The AMI is backed by Amazon Elastic Block Store (Amazon EBS) and uses a customer managed customer master key (CMK) to encrypt EBS volume snapshots. What is the MOST secure way for the solutions architect to share the AMI with the MSP Partner's AWS account?
A financial services company plans to launch a new application on AWS to handle sensitive financial transactions. The company will deploy the application on Amazon EC2 instances. The company will use Amazon RDS for MySQL as the database. The company's security policies mandate that data must be encrypted at rest and in transit. Which solution will meet these requirements with the LEAST operational overhead?

Question 579 - SAA-C03 discussion

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A company that uses AWS needs a solution to predict the resources needed for manufacturing processes each month. The solution must use historical values that are currently stored in an Amazon S3 bucket The company has no machine learning (ML) experience and wants to use a managed service for the training and predictions.

Which combination of steps will meet these requirements? (Select TWO.)

A.
Deploy an Amazon SageMaker model. Create a SageMaker endpoint for inference.
Answers
A.
Deploy an Amazon SageMaker model. Create a SageMaker endpoint for inference.
B.
Use Amazon SageMaker to train a model by using the historical data in the S3 bucket.
Answers
B.
Use Amazon SageMaker to train a model by using the historical data in the S3 bucket.
C.
Configure an AWS Lambda function with a function URL that uses Amazon SageMaker endpoints to create predictions based on the inputs.
Answers
C.
Configure an AWS Lambda function with a function URL that uses Amazon SageMaker endpoints to create predictions based on the inputs.
D.
Configure an AWS Lambda function with a function URL that uses an Amazon Forecast predictor to create a prediction based on the inputs.
Answers
D.
Configure an AWS Lambda function with a function URL that uses an Amazon Forecast predictor to create a prediction based on the inputs.
E.
Train an Amazon Forecast predictor by using the historical data in the S3 bucket.
Answers
E.
Train an Amazon Forecast predictor by using the historical data in the S3 bucket.
Suggested answer: B, E

Explanation:

To predict the resources needed for manufacturing processes each month using historical values that are currently stored in an Amazon S3 bucket, a solutions architect should use Amazon SageMaker to train a model by using the historical data in the S3 bucket, and deploy an Amazon SageMaker model and create a SageMaker endpoint for inference. Amazon SageMaker is a fully managed service that provides an easy way to build, train, and deploy machine learning (ML) models. The solutions architect can use the built-in algorithms or frameworks provided by SageMaker, or bring their own custom code, to train a model using the historical data in the S3 bucket as input. The trained model can then be deployed to a SageMaker endpoint, which is a scalable and secure web service that can handle requests for predictions from the application. The solutions architect does not need to have any ML experience or manage any infrastructure to use SageMaker.

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asked 16/09/2024
Mark Green
45 questions
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