Amazon SAA-C03 Online Practice Questions and Exam Preparation

Amazon SAA-C03 Online Questions & Answers

• Question 571:

  A company wants to migrate an application that uses a microservice architecture to AWS. The services currently run on Docker containers on-premises. The application has an event-driven architecture that uses Apache Kafka. The company configured Kafka to use multiple queues to send and receive messages. Some messages must be processed by multiple services.

  Which solution will meet these requirements with the LEAST management overhead?

  A. Migrate the services to Amazon Elastic Container Service (Amazon ECS) with the Amazon EC2 launch type. Deploy a Kafka cluster on EC2 instances to handle service-to-service communication.
  B. Migrate the services to Amazon Elastic Container Service (Amazon ECS) with the AWS Fargate launch type. Create multiple Amazon Simple Queue Service (Amazon SQS) queues to handle service-to-service communication.
  C. Migrate the services to Amazon Elastic Container Service (Amazon ECS) with the AWS Fargate launch type. Deploy an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster to handle service-to-service communication.
  D. Migrate the services to Amazon Elastic Container Service (Amazon ECS) with the Amazon EC2 launch type. Use Amazon EventBridge to handle service-to-service communication.
  C. Migrate the services to Amazon Elastic Container Service (Amazon ECS) with the AWS Fargate launch type. Deploy an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster to handle service-to-service communication.

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  Explanation

  Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data. By using Amazon ECS with the AWS Fargate launch type, you can run containers without managing servers or clusters. This combination reduces operational overhead and provides scalability.

  References:

  Power your Kafka Streams application with Amazon MSK and AWS FargateAmazon Web Services, Inc.

• Question 572:

  A company runs an ecommerce application on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group across multiple Availability Zones. The Auto Scaling group scales based on CPU utilization metrics. The ecommerce application stores the transaction data in a MySQL 8.0 database that is hosted on a large EC2 instance. The database's performance degrades quickly as application load increases. The application handles more read requests than write transactions. The company wants a solution that will automatically scale the database to meet the demand of unpredictable read workloads while maintaining high availability.

  Which solution will meet these requirements?

  A. Use Amazon Redshift with a single node for leader and compute functionality.
  B. Use Amazon RDS with a Single-AZ deployment Configure Amazon RDS to add reader instances in a different Availability Zone.
  C. Use Amazon Aurora with a Multi-AZ deployment. Configure Aurora Auto Scaling with Aurora Replicas.
  D. Use Amazon ElastiCache for Memcached with EC2 Spot Instances.
  C. Use Amazon Aurora with a Multi-AZ deployment. Configure Aurora Auto Scaling with Aurora Replicas.

• Question 573:

  A company uses Amazon EC2 instances and stores data on Amazon Elastic Block Store (Amazon EBS) volumes. The company must ensure that all data is encrypted at rest by using AWS Key Management Service (AWS KMS). The company must be able to control rotation of the encryption keys.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Create a customer managed key. Use the key to encrypt the EBS volumes.
  B. Use an AWS managed key to encrypt the EBS volumes. Use the key to configure automatic key rotation.
  C. Create an external KMS key with imported key material. Use the key to encrypt the EBS volumes.
  D. Use an AWS owned key to encrypt the EBS volumes.
  A. Create a customer managed key. Use the key to encrypt the EBS volumes.

• Question 574:

  A company needs to integrate with a third-party data feed. The data feed sends a webhook to notify an external service when new data is ready for consumption. A developer wrote an AWS Lambda function to retrieve data when the company receives a webhook callback. The developer must make the Lambda function available for the third party to call.

  Which solution will meet these requirements with the MOST operational efficiency?

  A. Create a function URL for the Lambda function. Provide the Lambda function URL to the third party for the webhook.
  B. Deploy an Application Load Balancer (ALB) in front of the Lambda function. Provide the ALB URL to the third party for the webhook.
  C. Create an Amazon Simple Notification Service (Amazon SNS) topic. Attach the topic to the Lambda function. Provide the public hostname of the SNS topic to the third party for the webhook.
  D. Create an Amazon Simple Queue Service (Amazon SQS) queue. Attach the queue to the Lambda function. Provide the public hostname of the SQS queue to the third party for the webhook.
  A. Create a function URL for the Lambda function. Provide the Lambda function URL to the third party for the webhook.

• Question 575:

  A company runs HPC workloads requiring high IOPS.

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

  A. Use Amazon EFS as a high-performance file system.
  B. Use Amazon FSx for Lustre as a high-performance file system.
  C. Create an Auto Scaling group of EC2 instances. Use Reserved Instances. Configure a spread placement group. Use AWS Batch for analytics.
  D. Use Mountpoint for Amazon S3 as a high-performance file system.
  E. Create an Auto Scaling group of EC2 instances. Use mixed instance types and a cluster placement group. Use Amazon EMR for analytics.
  B. Use Amazon FSx for Lustre as a high-performance file system.
  E. Create an Auto Scaling group of EC2 instances. Use mixed instance types and a cluster placement group. Use Amazon EMR for analytics.

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  Explanation

  Option B: FSx for Lustre is designed for HPC workloads with high IOPS.

  Option E: A cluster placement group ensures low-latency networking for HPC analytics workloads.

  Option A: Amazon EFS is not optimized for HPC.

  Option D: Mountpoint for S3 does not meet high IOPS needs.

• Question 576:

  A company has deployed a multiplayer game for mobile devices. The game requires live location tracking of players based on latitude and longitude. The data store for the game must support rapid updates and retrieval of locations. The game uses an Amazon RDS for PostgreSQL DB instance with read replicas to store the location data. During peak usage periods, the database is unable to maintain the performance that is needed for reading and writing updates. The game's user base is increasing rapidly.

  What should a solutions architect do to improve the performance of the data tier?

  A. Take a snapshot of the existing DB instance. Restore the snapshot with Multi-AZ enabled.
  B. Migrate from Amazon RDS to Amazon OpenSearch Service with OpenSearch Dashboards.
  C. Deploy Amazon DynamoDB Accelerator (DAX) in front of the existing DB instance. Modify the game to use DAX.
  D. Deploy an Amazon ElastiCache for Redis cluster in front of the existing DB instance. Modify the game to use Redis.
  D. Deploy an Amazon ElastiCache for Redis cluster in front of the existing DB instance. Modify the game to use Redis.

• Question 577:

  A solutions architect creates an Auto Scaling group for a memory-intensive application. The solutions architect wants to scale up and scale down based on memory usage.

  Which solution will meet this requirement?

  A. Install and configure the AWS Systems Manager Agent (SSM Agent). Create a step scaling policy that has step adjustments based on the memory usage trend.
  B. Install and configure the Amazon CloudWatch agent. Create a target tracking policy to scale based on the mem_used_percent CloudWatch metric.
  C. Install and configure the AWS Systems Manager Agent (SSM Agent). Create a target tracking policy to scale based on the mem_used_percent Amazon CloudWatch metric.
  D. Install and configure the Amazon CloudWatch agent. Create a scheduled scaling policy to scale based on the memory usage trend.
  B. Install and configure the Amazon CloudWatch agent. Create a target tracking policy to scale based on the mem_used_percent CloudWatch metric.

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  Explanation

  The Amazon CloudWatch agent is required to collect memory utilization metrics (as memory metrics are not reported by default). A target tracking policy is the simplest and most effective way to scale based on a custom metric such as mem_used_percent.

  References:

  " Install the CloudWatch agent to collect memory metrics, and create a target tracking scaling policy using these custom metrics. "

  Source: AWS Certified Solutions Architect?Official Study Guide, Monitoring and Scaling section.

• Question 578:

  A data analytics company has 80 offices that are distributed globally. Each office hosts 1 PB of data and has between 1 and 2 Gbps of internet bandwidth.

  The company needs to perform a one-time migration of a large amount of data from its offices to Amazon

  S3. The company must complete the migration within 4 weeks.

  Which solution will meet these requirements MOST cost-effectively?

  A. Establish a new 10 Gbps AWS Direct Connect connection to each office. Transfer the data to Amazon S3.
  B. Use multiple AWS Snowball Edge storage-optimized devices to store and transfer the data to Amazon S3.
  C. Use an AWS Snowmobile to store and transfer the data to Amazon S3.
  D. Set up an AWS Storage Gateway Volume Gateway to transfer the data to Amazon S3.
  B. Use multiple AWS Snowball Edge storage-optimized devices to store and transfer the data to Amazon S3.

• Question 579:

  An advertising company stores terabytes of data in an Amazon S3 data lake. The company wants to build its own foundation model (FM) and has deployed a training cluster on AWS. The company loads file-based data from Amazon S3 to the training cluster to train the FM. The company wants to reduce data loading time to optimize the overall deployment cycle.

  The company needs a storage solution that is natively integrated with Amazon S3. The solution must be scalable and provide high throughput.

  Which storage solution will meet these requirements?

  A. Mount an Amazon Elastic File System (Amazon EFS) file system to the training cluster. Use AWS DataSync to migrate data from Amazon S3 to the EFS file system to train the FM.
  B. Use an Amazon FSx for Lustre file system and Amazon S3 with Data Repository Association (DRA). Preload the data from Amazon S3 to the Lustre file system to train the FM.
  C. Attach Amazon Block Store (Amazon EBS) volumes to the training cluster. Load the data from Amazon S3 to the EBS volumes to train the FM.
  D. Use AWS DataSync to migrate the data from Amazon S3 to the training cluster as files. Train the FM on the local file-based data.
  B. Use an Amazon FSx for Lustre file system and Amazon S3 with Data Repository Association (DRA). Preload the data from Amazon S3 to the Lustre file system to train the FM.

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  Explanation

  Amazon FSx for Lustre is a high-performance parallel file system designed for machine learning and HPC that can be linked to Amazon S3 via Data Repository Associations (DRA). With DRA, you can import S3 objects as files (lazy or preloaded) and export results back to S3, providing very high throughput and low-latency POSIX access on the training cluster. This S3-native integration minimizes data loading overhead and accelerates training cycles at scale. EFS (A) is general-purpose and lower throughput per TB than Lustre. EBS (C) requires manual copy and does not scale as a shared parallel filesystem. DataSync alone (D) is a transfer tool, not a high-throughput training filesystem. FSx for Lustre with S3 DRA best satisfies scalability, throughput, and native S3 integration for rapid ML training.

• Question 580:

  A company hosts an application on Amazon EC2 On-Demand Instances in an Auto Scaling group.

  Application peak hours occur at the same time each day. Application users report slow application performance at the start of peak hours. The application performs normally 2-3 hours after peak hours begin. The company wants to ensure that the application works properly at the start of peak hours.

  Which solution will meet these requirements?

  A. Configure an Application Load Balancer to distribute traffic properly to the instances.
  B. Configure a dynamic scaling policy for the Auto Scaling group to launch new instances based on memory utilization.
  C. Configure a dynamic scaling policy for the Auto Scaling group to launch new instances based on CPU utilization.
  D. Configure a scheduled scaling policy for the Auto Scaling group to launch new instances before peak hours.
  D. Configure a scheduled scaling policy for the Auto Scaling group to launch new instances before peak hours.