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Amazon Web Services SAA-C03 Exam Sample Questions

Question # 1

A payment processing company records all voice communication with its customers and stores the audio files in an Amazon S3 bucket. The company needs to capture the text from the audio files. The company must remove from the text any personally identifiable information (Pll) that belongs to customers. What should a solutions architect do to meet these requirements?

A. Process the audio files by using Amazon Kinesis Video Streams. Use an AWS Lambda function to scan for known Pll patterns.

B. When an audio file is uploaded to the S3 bucket, invoke an AWS Lambda function to start an Amazon Textract task to analyze the call recordings.

C. Configure an Amazon Transcribe transcription job with Pll redaction turned on. When an audio file is uploaded to the S3 bucket, invoke an AWS Lambda function to start the transcription job. Store the output in a separate S3 bucket.

D. Create an Amazon Connect contact flow that ingests the audio files with transcription turned on. Embed an AWS Lambda function to scan for known Pll patterns. Use Amazon EventBridge (Amazon CloudWatch Events) to start the contact flow when an audio file is uploaded to the S3 bucket.

Answer

C. Configure an Amazon Transcribe transcription job with Pll redaction turned on. When an audio file is uploaded to the S3 bucket, invoke an AWS Lambda function to start the transcription job. Store the output in a separate S3 bucket.

Explanation: "Sensitive data redaction replaces personally identifiable information (PII) in the text transcript and the audio file. A redacted transcript replaces the original text with [PII]; a redacted audio file replaces spoken personal information with silence. This parameter is useful for protecting customer information."

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Question # 2

A company stores data for multiple business units in a single Amazon S3 bucket that is in the company's payer AWS account. To maintain data isolation, the business units store data in separate prefixes in the S3 bucket by using an S3 bucket policy. The company plans to add a large number of dynamic prefixes. The company does not want to rely on a single S3 bucket policy to manage data access at scale. The company wants to develop a secure access management solution in addition to the bucket policy to enforce prefix-level data isolation.

A. Configure the S3 bucket policy to deny s3:GetObject permissions for all users. Configure the bucket policy to allow s3:* access to individual business units.

B. Enable default encryption on the S3 bucket by using server-side encryption with Amazon S3 managed keys (SSE-S3).

C. Configure resource-based permissions on the S3 bucket by creating an S3 access point for each business unit.

D. Use pre-signed URLs to provide access to the S3 bucket.

Answer

C. Configure resource-based permissions on the S3 bucket by creating an S3 access point for each business unit.

Explanation:
Why Option C is Correct:
S3 Access Points: Provide scalable management of access to large datasets with specific permissions for individual prefixes.
Dynamic Prefixes: Access points simplify managing access to a growing number of prefixes without relying solely on a single bucket policy.
Fine-Grained Control: Resource-based permissions on access points enforce prefix-level isolation effectively.
Why Other Options Are Not Ideal:
Option A: Using deny/allow bucket policies introduces complexity and is less scalable for dynamic prefixes.
Option B: Encryption ensures data security but does not address access management.
Option D: Pre-signed URLs are temporary and not suitable for managing access at scale.

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Question # 3

A solutions architect has created two IAM policies: Policy1 and Policy2. Both policies are attached to an IAM group. https://selfexamtraining.com/uploadimages/SAA-C03-Q-393.png A cloud engineer is added as an IAM user to the IAM group. Which action will the cloud engineer be able to perform?

A. Deleting IAM users

B. Deleting directories

C. Deleting Amazon EC2 instances

D. Deleting logs from Amazon CloudWatch Logs

Answer

C. Deleting Amazon EC2 instances

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Question # 4

A company uses an Amazon Aurora PostgreSQL provisioned cluster with its application. The application's peak traffic occurs several times a day for periods of 30 minutes to several hours. The database capacity is provisioned to handle peak traffic from the application, but the database has wasted capacity during non-peak hours. The company wants to reduce the database costs. Which solution will meet these requirements with the LEAST operational effort?

A. Set up an Amazon CloudWatch alarm to monitor database utilization. Scale up or scale down the database capacity based on the amount of traffic.

B. Migrate the database to Amazon EC2 instances in on Auto Scaling group. Increase or decrease the number of instances based on the amount of traffic.

C. Migrate the database to an Amazon Aurora Serverless DB cluster to scale up or scale down the capacity based on the amount of traffic.

D. Schedule an AWS Lambda function to provision the required database capacity at the start of each day. Schedule another Lambda function to reduce the capacity at the end of each day.

Answer

C. Migrate the database to an Amazon Aurora Serverless DB cluster to scale up or scale down the capacity based on the amount of traffic.

Explanation: Requirement Analysis: The database experiences peak traffic multiple times a day but has wasted capacity during non-peak hours. The goal is to reduce costs with minimal operational effort. Aurora Serverless Overview: Aurora Serverless automatically adjusts database capacity based on current demand, scaling up during peak times and scaling down during non-peak times. Cost Efficiency: Aurora Serverless charges only for the capacity used, which is more cost-effective than provisioning for peak traffic. Operational Efficiency: Aurora Serverless eliminates the need for manual scaling or scheduling Lambda functions for capacity management. Implementation: Migrate the database from the provisioned Aurora PostgreSQL cluster to an Aurora Serverless cluster.

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Question # 5

A weather forecasting company needs to process hundreds of gigabytes of data with submillisecond latency. The company has a high performance computing (HPC) environment in its data center and wants to expand its forecasting capabilities. A solutions architect must identify a highly available cloud storage solution that can handle large amounts of sustained throughput Files that are stored in the solution should be accessible to thousands of compute instances that will simultaneously access and process the entire dataset. What should the solutions architect do to meet these requirements?

A. Use Amazon FSx for Lustre scratch file systems

B. Use Amazon FSx for Lustre persistent file systems.

C. Use Amazon Elastic File System (Amazon EFS) with Bursting Throughput mode.

D. Use Amazon Elastic File System (Amazon EFS) with Provisioned Throughput mode.

Answer

B. Use Amazon FSx for Lustre persistent file systems.

Explanation: Amazon FSx for Lustre: Lustre is a high-performance file system designed for workloads that require fast storage with sustained high throughput and low latency. It integrates with Amazon S3, making it suitable for HPC environments.
Persistent File Systems:
Simultaneous Access: FSx for Lustre allows thousands of compute instances to access and process large datasets concurrently, ensuring that the high volume of data is handled efficiently.
Highly Available: FSx for Lustre is designed to provide high availability and is managed by AWS, reducing the operational burden.

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