Amazon SAA-C03 Online Practice Questions and Exam Preparation

Amazon SAA-C03 Online Questions & Answers

• Question 551:

  A company collects data from thousands of remote devices by using a RESTful web services application that runs on an Amazon EC2 instance. The EC2 instance receives the raw data, transforms the raw data, and stores all the data in an Amazon S3 bucket. The number of remote devices will increase into the millions soon. The company needs a highly scalable solution that minimizes operational overhead.

  Which combination of steps should a solutions architect take to meet these requirements? (Choose two.)

  A. Use AWS Glue to process the raw data in Amazon S3.
  B. Use Amazon Route 53 to route traffic to different EC2 instances.
  C. Add more EC2 instances to accommodate the increasing amount of incoming data.
  D. Send the raw data to Amazon Simple Queue Service (Amazon SQS). Use EC2 instances to process the data.
  E. Use Amazon API Gateway to send the raw data to an Amazon Kinesis data stream. Configure Amazon Kinesis Data Firehose to use the data stream as a source to deliver the data to Amazon S3.
  A. Use AWS Glue to process the raw data in Amazon S3.
  E. Use Amazon API Gateway to send the raw data to an Amazon Kinesis data stream. Configure Amazon Kinesis Data Firehose to use the data stream as a source to deliver the data to Amazon S3.

• Question 552:

  A financial service company has a two-tier consumer banking application. The frontend serves static web content. The backend consists of APIs. The company needs to migrate the frontendcomponent to AWS.

  The backend of the application will remain on premises. The company must protect the application from common web vulnerabilities and attacks.

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

  A. Migrate the frontend to Amazon EC2 instances. Deploy an Application Load Balancer (ALB) in front of the instances. Use the instances to invoke the on-premises APIs. Associate AWS WAF rules with the instances.
  B. Deploy the frontend as an Amazon CloudFront distribution that has multiple origins. Configure one origin to be an Amazon S3 bucket that serves the static web content. Configure a second origin to route traffic to the on-premises APIs based on the URL pattern. Associate AWS WAF rules with the distribution.
  C. Migrate the frontend to Amazon EC2 instances. Deploy a Network Load Balancer (NLB) in front of the instances. Use the instances to invoke the on-premises APIs. Create an AWS Network Firewall instance. Route all traffic through the Network Firewall instance.
  D. Deploy the frontend as a static website based on an Amazon S3 bucket. Use an Amazon API Gateway REST API and a set of Amazon EC2 instances to invoke the on-premises APIs. Associate AWS WAF rules with the REST API and the S3 bucket.
  B. Deploy the frontend as an Amazon CloudFront distribution that has multiple origins. Configure one origin to be an Amazon S3 bucket that serves the static web content. Configure a second origin to route traffic to the on-premises APIs based on the URL pattern. Associate AWS WAF rules with the distribution.

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  Explanation

  Comprehensive Explanation:Deploying the frontend as a CloudFront distribution with multiple origins provides an efficient and scalable solution. Using WAF rules with CloudFront protects against web vulnerabilities, while the multi-origin configuration allows traffic routing to the on-premises backend APIs.

  This approach minimizes operational overhead compared to managing EC2 instances.

  References:

  Amazon CloudFront Features

  AWS WAF Integration with CloudFront

• Question 553:

  A company hosts a multiplayer gaming application on AWS. The company wants the application to read data with sub-millisecond latency and run one-time queries on historical data.

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

  A. Use Amazon RDS for data that is frequently accessed. Run a periodic custom script to export the data to an Amazon S3 bucket.
  B. Store the data directly in an Amazon S3 bucket. Implement an S3 Lifecycle policy to move older data to S3 Glacier Deep Archive for long-term storage. Run one-time queries on the data in Amazon S3 by using Amazon Athena.
  C. Use Amazon DynamoDB with DynamoDB Accelerator (DAX) for data that is frequently accessed. Export the data to an Amazon S3 bucket by using DynamoDB table export. Run one-time queries on the data in Amazon S3 by using Amazon Athena.
  D. Use Amazon DynamoDB for data that is frequently accessed. Turn on streaming to Amazon Kinesis Data Streams. Use Amazon Kinesis Data Firehose to read the data from Kinesis Data Streams. Store the records in an Amazon S3 bucket.
  C. Use Amazon DynamoDB with DynamoDB Accelerator (DAX) for data that is frequently accessed. Export the data to an Amazon S3 bucket by using DynamoDB table export. Run one-time queries on the data in Amazon S3 by using Amazon Athena.

• Question 554:

  A company plans to deploy containerized microservices in the AWS Cloud. The containers must mount a persistent file store that the company can manage by using OS-level permissions. The company requires fully managed services to host the containers and the file store.

  Which solution will meet these requirements?

  A. Use AWS Lambda functions and an Amazon API Gateway REST API to handle the microservices. Use Amazon S3 buckets for storage.
  B. Use Amazon EC2 instances to host the microservices. Use Amazon Elastic Block Store (Amazon EBS) volumes for storage.
  C. Use Amazon Elastic Container Service (Amazon ECS) containers on AWS Fargate to handle the microservices. Use an Amazon Elastic File System (Amazon EFS) file system for storage.
  D. Use Amazon Elastic Container Service (Amazon ECS) containers on AWS Fargate to handle the microservices. Use an Amazon EC2 instance that runs a dedicated file store for storage.
  C. Use Amazon Elastic Container Service (Amazon ECS) containers on AWS Fargate to handle the microservices. Use an Amazon Elastic File System (Amazon EFS) file system for storage.

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  Explanation

  Amazon ECS on AWS Fargate: AWS Fargate is a serverless compute engine for containers that works with Amazon ECS. It allows you to run containers without managing servers or clusters.

  Amazon EFS: Amazon Elastic File System (EFS) provides a simple, scalable, fully managed elastic NFS file system for use with AWS Cloud services and on-premises resources. It can be mounted to ECS tasks running on Fargate, allowing containers to access a shared file system with standard file system semantics, including OS-level permissions.

  References:

  Using Amazon EFS with Amazon ECS Amazon EFS: How it works

• Question 555:

  A company runs a production application on a fleet of Amazon EC2 instances. The application reads messages from an Amazon Simple Queue Service (Amazon SQS) queue and processes the messages in parallel. The message volume is unpredictable and highly variable.

  The company must ensure that the application continually processes messages without any downtime.

  Which solution will meet these requirements MOST cost-effectively?

  A. Use only Spot Instances to handle the maximum capacity required.
  B. Use only Reserved Instances to handle the maximum capacity required.
  C. Use Reserved Instances to handle the baseline capacity. Use Spot Instances to provide additional capacity when required.
  D. Use Reserved Instances in an EC2 Auto Scaling group to handle the minimum capacity. Configure an auto scaling policy that is based on the SQS queue backlog.
  C. Use Reserved Instances to handle the baseline capacity. Use Spot Instances to provide additional capacity when required.

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  Explanation

  AWS guidance is to cover steady baseline with commitments (Reserved Instances or Savings Plans) and use EC2 Spot Instances for burst capacity to minimize cost. Spot provides up to 90% discounts and is well-suited to fault-tolerant, queue-based workloads; interruptions are handled by replacing capacity automatically while messages remain durably in SQS. Using only Spot (A) risks capacity gaps; only RIs sized for peak (B) wastes cost during low demand. Option D scales on backlog but uses On-Demand for bursts, which is more expensive than Spot. With C, baseline capacity (RIs) keeps processing continuously (no downtime), and Spot adds cost-efficient throughput during spikes, aligning with Well-Architected cost and reliability patterns for queue workers.

  References:

  EC2 Spot Best Practices -- burst with Spot for interruptible/queued workloads

  SQS -- durable buffering;

  Well-Architected Cost Optimization -- cover steady state with commitments, scale bursts with discounted capacity.

• Question 556:

  A company is designing a microservice-based architecture tor a new application on AWS. Each microservice will run on its own set of Amazon EC2 instances. Each microservice will need to interact with multiple AWS services such as Amazon S3 and Amazon Simple Queue Service (Amazon SQS).

  The company wants to manage permissions for each EC2 instance based on the principle of least privilege.

  Which solution will meet this requirement?

  A. Assign an IAM user to each micro-service. Use access keys stored within the application code to authenticate AWS service requests.
  B. Create a single IAM role that has permission to access all AWS services. Associate the IAM role with all EC2 instances that run the microservices
  C. Use AWS Organizations to create a separate account for each microservice. Manage permissions at the account level.
  D. Create individual IAM roles based on the specific needs of each microservice. Associate the IAM roles with the appropriate EC2 instances.
  D. Create individual IAM roles based on the specific needs of each microservice. Associate the IAM roles with the appropriate EC2 instances.

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  Explanation

  When designing a microservice architecture where each microservice interacts with different AWS services, it's essential to follow the principle of least privilege. This means granting each microservice only the permissions it needs to perform its tasks, reducing the risk of unauthorized access or accidental actions.

  The recommended approach is to create individualIAM roleswith policies that grant each microservice the specific permissions it requires. Then, these roles should be associated with the EC2 instances that run the corresponding microservice. By doing so, each EC2 instance will assume its specific IAM role, and permissions will be automatically managed by AWS.

  IAM roles provide temporary credentials via the instance metadata service, eliminating the need to hard-code credentials in your application code, which enhances security.

  AWS References: IAM Roles for Amazon EC2explains how EC2 instances can use IAM roles to securely access AWS services without managing long-term credentials.

  Best Practices for IAMincludes recommendations for implementing the least privilege principle and using

  IAM roles effectively.

  Why the other options are incorrect:

  Option A: Assign an IAM user to each microservice: This requires managing long-term credentials (access keys), which should be avoided. Storing keys in application code is insecure and creates a maintenance burden.

  Option B: Create a single IAM role: This violates the principle of least privilege, as a single role with broad permissions across all services is less secure.

  Option C:Use

  AWS Organizations: This approach adds unnecessary complexity. Managing permissions at the account level for each microservice is excessive for this use case and doesn ' t adhere to the principle of least privilege.

• Question 557:

  A company is building an application on Amazon EC2 instances. The application needs to handle a large number of transactions. The application requires an Amazon EBS data volume that has configurable and consistent input/output operations per second (IOPS).

  Which solution will meet these requirements?

  A. Provision EC2 instances with a Throughput Optimized HDD (st1) EBS root volume and a Cold HDD (sc1) EBS data volume.
  B. Provision EC2 instances with a Throughput Optimized HDD (st1) EBS volume that will serve as both a root volume and a data volume.
  C. Provision EC2 instances with a General Purpose SSD (gp3) EBS root volume and a Provisioned IOPS SSD (io2) EBS data volume.
  D. Provision EC2 instances with a General Purpose SSD (gp3) EBS root volume. Configure the application to store data in an Amazon S3 bucket.
  C. Provision EC2 instances with a General Purpose SSD (gp3) EBS root volume and a Provisioned IOPS SSD (io2) EBS data volume.

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  Explanation

  The correct answer is C because the requirement specifically calls for an Amazon EBS data volume that provides configurable and consistent IOPS for a transaction-heavy application. Provisioned IOPS SSD (io2) volumes are designed for workloads that need high performance, low latency, and predictable I/O performance. These volumes are the best fit for applications that process a large number of transactions and require storage performance to remain stable under load.

  Using a gp3 volume for the root device is appropriate because the operating system volume usually does not require the same high and sustained performance characteristics as the application data volume. The io2 data volume provides the ability to provision IOPS independently to match the application's transactional demands. This separation of root and data storage is a common AWS design pattern for performance-sensitive workloads.

  Option A is incorrect because st1 and sc1 are HDD-based volumes intended for large, sequential workloads, not high-transaction workloads that require consistent low-latency I/O.

  Option B is also incorrect because st1 does not provide the required configurable and consistent IOPS characteristics.

  Option D is incorrect because the requirement explicitly states that the application needs an Amazon EBS data volume, and Amazon S3 is object storage rather than block storage attached as an EBS volume.

  AWS storage best practices recommend Provisioned IOPS SSD volumes for mission-critical applications, transactional systems, and workloads that need sustained, predictable performance. Therefore, a gp3 root volume combined with an io2 data volume is the most appropriate solution for this use case.

• Question 558:

  A solutions architect is designing a security solution for a company that wants to provide developers with individual AWS accounts through AWS Organizations, while also maintaining standard security controls.

  Because the individual developers will have AWS account root user-level access to their own accounts, the solutions architect wants to ensure that the mandatory AWS CloudTrail configuration that is applied to new developer accounts is not modified.

  Which action meets these requirements?

  A. Create an IAM policy that prohibits changes to CloudTrail. and attach it to the root user.
  B. Create a new trail in CloudTrail from within the developer accounts with the organization trails option enabled.
  C. Create a service control policy (SCP) that prohibits changes to CloudTrail, and attach it the developer accounts.
  D. Create a service-linked role for CloudTrail with a policy condition that allows changes only from an Amazon Resource Name (ARN) in the management account.
  C. Create a service control policy (SCP) that prohibits changes to CloudTrail, and attach it the developer accounts.

• Question 559:

  A company runs multiple workloads in its on-premises data center. The company's data center cannot scale fast enough to meet the company's expanding business needs. The company wants to collect usage and configuration data about the on-premises servers and workloads to plan a migration to AWS.

  Which solution will meet these requirements?

  A. Set the home AWS Region in AWS Migration Hub. Use AWS Systems Manager to collect data about the on-premises servers.
  B. Set the home AWS Region in AWS Migration Hub. Use AWS Application Discovery Service to collect data about the on-premises servers.
  C. Use the AWS Schema Conversion Tool (AWS SCT) to create the relevant templates. Use AWS Trusted Advisor to collect data about the on-premises servers.
  D. Use the AWS Schema Conversion Tool (AWS SCT) to create the relevant templates. Use AWS Database Migration Service (AWS DMS) to collect data about the on-premises servers.
  B. Set the home AWS Region in AWS Migration Hub. Use AWS Application Discovery Service to collect data about the on-premises servers.

• Question 560:

  A reporting team receives files each day in an Amazon S3 bucket. The reporting team manually reviews and copies the files from this initial S3 bucket to an analysis S3 bucket each day at the same time to use with Amazon QuickSight. Additional teams are starting to send more files in larger sizes to the initial S3 bucket. The reporting team wants to move the files automatically analysis S3 bucket as the files enter the initial S3 bucket. The reporting team also wants to use AWS Lambda functions to run pattern-matching code on the copied data. In addition, the reporting team wants to send the data files to a pipeline in Amazon SageMaker Pipelines.

  What should a solutions architect do to meet these requirements with the LEAST operational overhead?

  A. Create a Lambda function to copy the files to the analysis S3 bucket. Create an S3 event notification for the analysis S3 bucket. Configure Lambda and SageMaker Pipelines as destinations of the event notification. Configure s3:ObjectCreated:Put as the event type.
  B. Create a Lambda function to copy the files to the analysis S3 bucket. Configure the analysis S3 bucket to send event notifications to Amazon EventBridge (Amazon CloudWatch Events). Configure an ObjectCreated rule in EventBridge (CloudWatch Events). Configure Lambda and SageMaker Pipelines as targets for the rule.
  C. Configure S3 replication between the S3 buckets. Create an S3 event notification for the analysis S3 bucket. Configure Lambda and SageMaker Pipelines as destinations of the event notification. Configure s3:ObjectCreated:Put as the event type.
  D. Configure S3 replication between the S3 buckets. Configure the analysis S3 bucket to send event notifications to Amazon EventBridge (Amazon CloudWatch Events). Configure an ObjectCreated rule in EventBridge (CloudWatch Events). Configure Lambda and SageMaker Pipelines as targets for the rule.
  D. Configure S3 replication between the S3 buckets. Configure the analysis S3 bucket to send event notifications to Amazon EventBridge (Amazon CloudWatch Events). Configure an ObjectCreated rule in EventBridge (CloudWatch Events). Configure Lambda and SageMaker Pipelines as targets for the rule.