Tags: SAA-C03자격증공부자료, SAA-C03시험응시료, SAA-C03최신버전 덤프공부자료, SAA-C03완벽한 시험덤프, SAA-C03최고덤프공부
예를 들어Amazon SAA-C03 덤프를 보면 어떤 덤프제공사이트에서는 문항수가 아주 많은 자료를 제공해드리지만 저희Amazon SAA-C03덤프는 문항수가 적은 편입니다.왜냐하면 저희는 더 이상 출제되지 않는 오래된 문제들을 삭제해버리기 때문입니다. 문제가 많으면 고객들의 시간을 허비하게 됩니다. Itexamdump는 응시자에게 있어서 시간이 정말 소중하다는 것을 잘 알고 있습니다.
Amazon SAA-C03 인증 시험은 AWS 플랫폼에서 안전하고 확장 가능한 신뢰할 수있는 애플리케이션을 설계하고 배치하는 데있어 전문 기술과 전문 지식을 검증하는 인증 시험입니다. 이 시험은 클라우드 컴퓨팅 및 AWS에서 경력을 발전시키려는 전문가를 위해 설계되었으며 AWS 서비스, 보안, 네트워킹, 데이터베이스 및 스토리지를 포함한 광범위한 주제를 다룹니다. 응시자는 AWS 교육 과정, 화이트 패퍼 및 실습 시험을 포함한 다양한 자원을 활용하여 시험을 준비 할 수 있습니다.
아마존 SAA-C03 자격증은 AWS 솔루션 아키텍처에 대한 전문성을 증명하고자 하는 개인에게 가치 있는 자산입니다. 세계적으로 인정되며 AWS 관련 직종에서 요구 사항 중 하나입니다. AWS 솔루션 아키텍처 자격증을 취득하면 직업 기회가 증가하고 더 높은 급여를 받을 수 있습니다. 또한 이를 통해 개인들은 직장 시장에서 경쟁 우위를 얻을 수 있으며 복잡한 AWS 솔루션을 설계하고 구현하는 데 필요한 기술과 지식을 제공받을 수 있습니다.
Amazon SAA-C03 인증 시험은 AWS 핵심 서비스, 보안, 네트워킹, 데이터베이스, 스토리지, 배포 및 관리를 포함한 광범위한 주제를 다룹니다. 이 시험에 합격하면 AWS에서 확장 가능하고 고도로 사용 가능한 고도로 사용 가능한 고도로 제공되는 개인의 능력을 보여줍니다. 이 인증은 많은 조직에 의해 인정되며 클라우드 컴퓨팅에서 경력을 발전시키고 자하는 IT 전문가에게는 귀중한 자산입니다.
SAA-C03시험응시료 - SAA-C03최신버전 덤프공부자료
Amazon SAA-C03 인증시험 최신버전덤프만 마련하시면Amazon SAA-C03시험패스는 바로 눈앞에 있습니다. 주문하시면 바로 사이트에서 pdf파일을 다운받을수 있습니다. Amazon SAA-C03 덤프의 pdf버전은 인쇄 가능한 버전이라 공부하기도 편합니다. Amazon SAA-C03 덤프샘플문제를 다운받은후 굳게 믿고 주문해보세요. 궁금한 점이 있으시면 온라인서비스나 메일로 상담받으시면 됩니다.
최신 AWS Certified Solutions Architect SAA-C03 무료샘플문제 (Q376-Q381):
질문 # 376
A company has an application that provides marketing services to stores. The services are based on previous purchases by store customers. The stores upload transaction data to the company through SFTP, and the data is processed and analyzed to generate new marketing offers. Some of the files can exceed 200 GB in size.
Recently, the company discovered that some of the stores have uploaded files that contain personally identifiable information (PII) that should not have been included. The company wants administrators to be alerted if PII is shared again. The company also wants to automate remediation.
What should a solutions architect do to meet these requirements with the LEAST development effort?
- A. Implement custom scanning algorithms in an AWS Lambda function. Trigger the function when objects are loaded into the bucket. It objects contain Rll. use Amazon Simple Notification Service (Amazon SNS) to trigger a notification to the administrators to remove the objects that contain Pll.
- B. Use an Amazon S3 bucket as a secure transfer point. Use Amazon Macie to scan the objects in the bucket. If objects contain Pll. Use Amazon Simple Notification Service (Amazon SNS) to trigger a notification to the administrators to remove the objects mat contain Pll.
- C. Implement custom scanning algorithms in an AWS Lambda function. Trigger the function when objects are loaded into the bucket. If objects contain Pll. use Amazon Simple Email Service (Amazon STS) to trigger a notification to the administrators and trigger on S3 Lifecycle policy to remove the objects mot contain PII.
- D. Use an Amazon S3 bucket as a secure transfer point. Use Amazon Inspector to scan me objects in the bucket. If objects contain Pll. trigger an S3 Lifecycle policy to remove the objects that contain Pll.
정답:B
설명:
To meet the requirements of detecting and alerting the administrators when PII is shared and automating remediation with the least development effort, the best approach would be to use Amazon S3 bucket as a secure transfer point and scan the objects in the bucket with Amazon Macie. Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect sensitive data stored in Amazon S3. It can be used to classify sensitive data, monitor access to sensitive data, and automate remediation actions.
In this scenario, after uploading the files to the Amazon S3 bucket, the objects can be scanned for PII by Amazon Macie, and if it detects any PII, it can trigger an Amazon Simple Notification Service (SNS) notification to alert the administrators to remove the objects containing PII. This approach requires the least development effort, as Amazon Macie already has pre-built data classification rules that can detect PII in various formats.
Hence, option B is the correct answer.
References:
* Amazon Macie User Guide: https://docs.aws.amazon.com/macie/latest/userguide/what-is-macie.html
* AWS Well-Architected Framework - Security Pillar: https://docs.aws.amazon.com/wellarchitected/latest
/security-pillar/welcome.html
질문 # 377
A transaction processing company has weekly scripted batch jobs that run on Amazon EC2 instances. The EC2 instances are in an Auto Scaling group. The number of transactions can vary but the beseline CPU utilization that is noted on each run is at least 60%. The company needs to provision the capacity 30 minutes before the jobs run.
Currently engineering complete this task by manually modifying the Auto Scaling group parameters. The company does not have the resources to analyze the required capacity trends for the Auto Scaling group counts. The company needs an automated way to modify the Auto Scaling group's capacity.
Which solution will meet these requiements with the LEAST operational overhead?
- A. Create a scheduled scaling polcy for the Auto Scaling group. Set the appropriate desired capacity, minimum capacity, and maximum capacity. Set the recurrence to weekly. Set the start time to 30 minutes. Before the batch jobs run.
- B. Ceate a dynamic scalling policy for the Auto Scaling group. Configure the policy to scale based on the CPU utilization metric to 60%.
- C. Create an Amazon EventBridge event to invoke an AWS Lamda function when the CPU utilization metric value for the Auto Scaling group reaches 60%. Configure the Lambda function to increase the Auto Scaling group's desired capacity and maximum capacity by 20%.
- D. Create a predictive scaling policy for the Auto Scaling group. Configure the policy to scale based on forecast. Set the scaling metric to CPU utilization. Set the target value for the metric to 60%. In the Policy, set the instances to pre-launch 30 minutes before the jobs run.
정답:D
설명:
This option is the most efficient because it uses a predictive scaling policy for the Auto Scaling group, which is a type of scaling policy that uses machine learning to predict capacity requirements based on historical data from CloudWatch1. It also configures the policy to scale based on forecast, which enables the Auto Scaling group to adjust its capacity in advance of traffic changes. It also sets the scaling metric to CPU utilization and the target value for the metric to 60%, which aligns with the baseline CPU utilization that is noted on each run. It also sets the instances to pre-launch 30 minutes before the jobs run, which ensures that enough capacity is provisioned before the weekly scripted batch jobs start. This solution meets the requirement of provisioning the capacity 30 minutes before the jobs run with the least operational overhead. Option A is less efficient because it uses a dynamic scaling policy for the Auto Scaling group, which is a type of scaling policy that adjusts your Auto Scaling group's capacity in response to changing demand2. However, this does not provide a way to provision the capacity 30 minutes before the jobs run, as it only reacts to changing traffic. Option B is less efficient because it uses a scheduled scaling policy for the Auto Scaling group, which is a type of scaling policy that lets you scale your Auto Scaling group based on a schedule that you create3. However, this does not provide a way to scale based on forecast or CPU utilization, as it only scales based on predefined metrics and policies. Option D is less efficient because it uses an Amazon EventBridge event to invoke an AWS Lambda function when the CPU utilization metric value for the Auto Scaling group reaches 60%, which is a way to trigger serverless functions based on events. However, this does not provide a way to provision the capacity 30 minutes before the jobs run, as it only reacts to changing traffic.
질문 # 378
A company is implementing a shared storage solution for a media application that is hosted m the AWS Cloud The company needs the ability to use SMB clients to access data The solution must he fully managed.
Which AWS solution meets these requirements?
- A. Create an Amazon EC2 Windows instance Install and configure a Windows file share role on the instance. Connect the application server to the file share.
- B. Create an AWS Storage Gateway tape gateway Configure (apes to use Amazon S3 Connect the application server lo the tape gateway
- C. Create an Amazon FSx for Windows File Server tile system Attach the fie system to the origin server. Connect the application server to the tile system
- D. Create an AWS Storage Gateway volume gateway. Create a file share that uses the required client protocol Connect the application server to the tile share.
정답:C
질문 # 379
A development team is collaborating with another company to create an integrated product. The other company needs to access an Amazon Simple Queue Service (Amazon SQS) queue that is contained in the development team's account. The other company wants to poll the queue without giving up its own account permissions to do so.
How should a solutions architect provide access to the SQS queue?
- A. Create an Amazon Simple Notification Service (Amazon SNS) access policy that provides the other company access to the SQS queue.
- B. Create an 1AM policy that provides the other company access to the SQS queue.
- C. Create an instance profile that provides the other company access to the SQS queue.
- D. Create an SQS access policy that provides the other company access to the SQS queue.
정답:D
설명:
To provide access to the SQS queue to the other company without giving up its own account permissions, a solutions architect should create an SQS access policy that provides the other company access to the SQS queue. An SQS access policy is a resource-based policy that defines who can access the queue and what actions they can perform. The policy can specify the AWS account ID of the other company as a principal, and grant permissions for actions such as sqs:ReceiveMessage, sqs:DeleteMessage, and sqs:GetQueueAttributes. This way, the other company can poll the queue using its own credentials, without needing to assume a role or use cross-account access keys. Reference:
Using identity-based policies (IAM policies) for Amazon SQS
Using custom policies with the Amazon SQS access policy language
질문 # 380
A company is using AWS Fargate to run a batch job whenever an object is uploaded to an Amazon S3 bucket. The minimum ECS task count is initially set to 1 to save on costs and should only be increased based on new objects uploaded to the S3 bucket.
Which is the most suitable option to implement with the LEAST amount of effort?
- A. Set up an alarm in CloudWatch to monitor S3 object-level operations recorded on CloudTrail. Set two alarm actions to update the ECS task count to scale-out/scale-in depending on the S3 event.
- B. Set up an alarm in Amazon CloudWatch to monitor S3 object-level operations that are recorded on CloudTrail. Create an Amazon EventBridge rule that triggers the ECS cluster when new CloudTrail events are detected.
- C. Set up an Amazon EventBridge rule to detect S3 object PUT operations and set the target to a Lambda function that will run the StartTask API command.
- D. Set up an Amazon EventBridge rule to detect S3 object PUT operations and set the target to the ECS cluster to run a new ECS task.
정답:D
설명:
Amazon EventBridge (formerly called CloudWatch Events) is a serverless event bus that makes it easy to connect applications together. It uses data from your own applications, integrated software as a service (SaaS) applications, and AWS services. This simplifies the process of building event-driven architectures by decoupling event producers from event consumers. This allows producers and consumers to be scaled, updated, and deployed independently. Loose coupling improves developer agility in addition to application resiliency.
You can use Amazon EventBridge to run Amazon ECS tasks when certain AWS events occur. You can set up an EventBridge rule that runs an Amazon ECS task whenever a file is uploaded to a certain Amazon S3 bucket using the Amazon S3 PUT operation.
Hence, the correct answer is: Set up an Amazon EventBridge rule to detect S3 object PUT operations and set the target to the ECS cluster to run a new ECS task.
The option that says: Set up an Amazon EventBridge rule to detect S3 object PUT operations and set the target to a Lambda function that will run the StartTask API command is incorrect. Although this solution meets the requirement, creating your own Lambda function for this scenario is not really necessary. It is much simpler to control ECS tasks directly as targets for the CloudWatch Event rule. Take note that the scenario asks for a solution that is the easiest to implement.
The option that says: Set up an alarm in Amazon CloudWatch to monitor S3 object-level operations that are recorded on CloudTrail. Create an Amazon EventBridge rule that triggers the ECS cluster when new CloudTrail events are detected is incorrect because using CloudTrail and CloudWatch Alarm creates an unnecessary complexity to what you want to achieve. Amazon EventBridge can directly target an ECS task on the Targets section when you create a new rule.
The option that says: Set up an alarm in CloudWatch to monitor CloudTrail since this S3 object-level operations are recorded on CloudTrail. Set two alarm actions to update ECS task count to scale- out/scale-in depending on the S3 event is incorrect because you can't directly set CloudWatch Alarms to update the ECS task count.
References:
https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/CloudWatch-Events-tutorial-ECS.html
https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/Create-CloudWatch-Events-Rule.html Check out this Amazon CloudWatch Cheat Sheet:
https://tutorialsdojo.com/amazon-cloudwatch/
Amazon CloudWatch Overview:
https://youtu.be/q0DmxfyGkeU
질문 # 381
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