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AWS Certified DevOps Engineer AWS-DevOps-Engineer-Professional IT認定試験に合格するのは難しいと思いますか。
弊社のAmazonのAWS-DevOps-Engineer-Professional - AWS Certified DevOps Engineer - Professional学習範囲練習問題を利用したら、あなたは気楽に勉強するだけではなく、順調に試験に合格します。 このAWS-DevOps-Engineer-Professional 受験対策解説集問題集はあなたを楽に試験に合格させる素晴らしいツールですから、この成功できチャンスを見逃せば絶対後悔になりますから、尻込みしないで急いで行動しましょう。ただ一つの試験の準備をするだけで時間をたくさん無駄にすることをやめてください。
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今競争の激しいIT業界で地位を固めたいですが、Amazon AWS-DevOps-Engineer-Professional学習範囲認証試験に合格しなければなりません。IT業界ではさらに強くなるために強い専門知識が必要です。
AWS-DevOps-Engineer-Professional PDF DEMO:
QUESTION NO: 1
A web application for healthcare services runs on Amazon EC2 instances behind an ELB
Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group across multiple
Availability Zones. A DevOps Engineer must create a mechanism in which an EC2 instance can be taken out of production so its system logs can be analyzed for issues to quickly troubleshot problems on the web tier.
How can the Engineer accomplish this task while ensuring availability and minimizing downtime?
A. Terminate the EC2 instances manually. The Auto Scaling service will upload all log information to
CloudWatch Logs for analysis prior to instance termination.
B. Implement EC2 Auto Scaling groups cooldown periods. Use EC2 instance metadata to determine the instance state, and an AWS Lambda function to snapshot Amazon EBS volumes to preserve system logs.
C. Implement Amazon CloudWatch Events rules. Create an AWS Lambda function that can react to an instance termination to deploy the CloudWatch Logs agent to upload the system and access logs to
Amazon S3 for analysis.
D. Implement EC2 Auto Scaling groups with lifecycle hooks. Create an AWS Lambda function that can modify an EC2 instance lifecycle hook into a standby state, extract logs from the instance through a remote script execution, and place them in an Amazon S3 bucket for analysis.
Answer: B
QUESTION NO: 2
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: 3
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: 4
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: 5
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
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Updated: May 28, 2022