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AWS Certified DevOps Engineer AWS-DevOps-Engineer-Professional 成功を祈ります。
AWS Certified DevOps Engineer AWS-DevOps-Engineer-Professional復習対策書 - AWS Certified DevOps Engineer - Professional (DOP-C01) 試験問題と解答に関する質問があるなら、当社は直後に解決方法を差し上げます。 Omgzlookの専門家が研究された問題集を利用してください。まだAmazonのAWS-DevOps-Engineer-Professional サンプル問題集認定試験を悩んでいますかこの情報の時代の中で専門なトレーニングを選択するのと思っていますか？良いターゲットのトレーニングを利用すれば有効で君のIT方面の大量の知識を補充 できます。
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Amazon AWS-DevOps-Engineer-Professional復習対策書 - 君の夢は1歩更に近くなります。
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AWS-DevOps-Engineer-Professional PDF DEMO:
QUESTION NO: 1
A company is hosting a web application in an AWS Region. For disaster recovery purposes, a second region is being used as a standby. Disaster recovery requirements state that session data must be replicated between regions in near-real time and 1% of requests should route to the secondary region to continuously verify system functionality. Additionally, if there is a disruption in service in the main region, traffic should be automatically routed to the secondary region, and the secondary region must be able to scale up to handle all traffic.
How should a DevOps Engineer meet these requirements?
A. In both regions, deploy the application on AWS Elastic Beanstalk and use Amazon DynamoDB global tables for session data. Use an Amazon Route 53 weighted routing policy with health checks to distribute the traffic across the regions.
B. In both regions, launch the application in Auto Scaling groups and use DynamoDB for session data.
Use a Route 53 failover routing policy with health checks to distribute the traffic across the regions.
C. In both regions, deploy the application in AWS Lambda, exposed by Amazon API Gateway, and use
Amazon RDS PostgreSQL with cross-region replication for session data. Deploy the web application with client-side logic to call the API Gateway directly.
D. In both regions, launch the application in Auto Scaling groups and use DynamoDB global tables for session data. Enable an Amazon CloudFront weighted distribution across regions. Point the Amazon
Route 53 DNS record at the CloudFront distribution.
Answer: C
QUESTION NO: 2
A defect was discovered in production and a new sprint item has been created for deploying a hotfix.
However, any code change must go through the following steps before going into production:
*Scan the code for security breaches, such as password and access key leaks.
Run the code through extensive, long running unit tests.
Which source control strategy should a DevOps Engineer use in combination with AWS CodePipeline to complete this process?
A. Create a hotfix branch from the master branch. Triger the development pipeline from the hotfix branch.
Use AWS Lambda to do a content scan and run unit tests. Add a manual approval stage that merges the hotfix branch into the master branch.
B. Create a hotfix branch from the master branch. Create a separate source stage for the hotfix branch in the production pipeline. Trigger the pipeline from the hotfix branch. Use AWS Lambda to do a content scan and use AWS CodeBuild to run unit tests. Add a manual approval stage that merges the hotfix branch into the master branch.
C. Create a hotfix branch from the master branch. Triger the development pipeline from the hotfix branch.
Use AWS CodeBuild to do a content scan and run unit tests. Add a manual approval stage that merges the hotfix branch into the master branch.
D. Create a hotfix tag on the last commit of the master branch. Trigger the development pipeline from the hotfix tag. Use AWS CodeDeploy with Amazon ECS to do a content scan and run unit tests.
Add a manual approval stage that merges the hotfix tag into the master branch.
Answer: D
QUESTION NO: 3
A government agency has multiple AWS accounts, many of which store sensitive citizen information. A Security team wants to detect anomalous account and network activities (such as SSH brute force attacks) in any account and centralize that information in a dedicated security account.
Event information should be stored in an Amazon S3 bucket in the security account, which is monitored by the department's Security Information and Even Manager (SIEM) system.
How can this be accomplished?
A. Enable Amazon Macie in the security account only. Configure the security account as the Macie
Administrator for every member account using invitation/ acceptance. Create an Amazon
CloudWatch Events rule in the security account to send all findings to Amazon Kinesis Data Streams.
Write and application using KCL to read data from the Kinesis Data Streams and write to the S3 bucket.
B. Enable Amazon GuardDuty in every account. Configure the security account as the GuardDuty
Administrator for every member account using invitation/ acceptance. Create an Amazon
CloudWatch rule in the security account to send all findings to Amazon Kinesis Data Firehouse, which will push the findings to the S3 bucket.
C. Enable Amazon GuardDuty in the security account only. Configure the security account as the
GuardDuty Administrator for every member account using invitation/acceptance. Create an Amazon
CloudWatch rule in the security account to send all findings to Amazon Kinesis Data Streams. Write and application using KCL to read data from Kinesis Data Streams and write to the S3 bucket.
D. Enable Amazon Macie in every account. Configure the security account as the Macie
Administrator for every member account using invitation/acceptance. Create an Amazon CloudWatch
Events rule in the security account to send all findings to Amazon Kinesis Data Firehouse, which should push the findings to the S3 bucket.
Answer: C
QUESTION NO: 4
A DevOps Engineer administers an application that manages video files for a video production company. The application runs on Amazon EC2 instances behind an ELB Application Load Balancer.
The instances run in an Auto Scaling group across multiple Availability Zones. Data is stored in an
Amazon RDS PostgreSQL Multi-AZ DB instance, and the video files are stored in an Amazon S3 bucket.
On a typical day, 50 GB of new video are added to the S3 bucket. The Engineer must implement a multi-region disaster recovery plan with the least data loss and the lowest recovery times. The current application infrastructure is already described using AWS CloudFormation.
Which deployment option should the Engineer choose to meet the uptime and recovery objectives for the system?
A. Launch the application from the CloudFormation template in the second region, which sets the capacity of the Auto Scaling group to 1. Create a scheduled task to take daily Amazon RDS cross- region snapshots to the second region. In the second region, enable cross-region replication between the original S3 bucket and Amazon Glacier. In a disaster, launch a new application stack in the second region and restore the database from the most recent snapshot.
B. Use Amazon CloudWatch Events to schedule a nightly task to take a snapshot of the database and copy the snapshot to the second region. Create an AWS Lambda function that copies each object to a new S3 bucket in the second region in response to S3 event notifications. In the second region, launch the application from the CloudFormation template and restore the database from the most recent snapshot.
C. Launch the application from the CloudFormation template in the second region, which sets the capacity of the Auto Scaling group to 1. Create an Amazon RDS read replica in the second region. In the second region, enable cross-region replication between the original S3 bucket and a new S3 bucket. To fail over, promote the read replica as master. Update the CloudFormation stack and increase the capacity of the Auto Scaling group.
D. Launch the application from the CloudFormation template in the second region which sets the capacity of the Auto Scaling group to 1. Use Amazon CloudWatch Events to schedule a nightly task to take a snapshot of the database, copy the snapshot to the second region, and replace the DB instance in the second region from the snapshot. In the second region, enable cross-region replication between the original S3 bucket and a new S3 bucket. To fail over, increase the capacity of the Auto Scaling group.
Answer: D
QUESTION NO: 5
A DevOps Engineer is using AWS CodeDeploy across a fleet of Amazon EC2 instances in an
EC2 Auto Scaling group. The associated CodeDeploy deployment group, which is integrated with EC2
Auto Scaling, is configured to perform in-place deployments with CodeDeployDefault.OneAtATime.
During an ongoing new deployment, the Engineer discovers that, although the overall deployment finished successfully, two out of five instances have the previous application revision deployed. The other three instances have the newest application revision.
What is likely causing this issue?
A. A failed AfterInstall lifecycle event hook caused the CodeDeploy agent to roll back to the previous version on the affected instances.
B. EC2 Auto Scaling launched two new instances while the new deployment had not yet finished, causing the previous version to be deployed on the affected instances.
C. The CodeDeploy agent was not installed in two affected instances.
D. The two affected instances failed to fetch the new deployment.
Answer: B
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Updated: May 28, 2022