IT業種で仕事しているあなたは、夢を達成するためにどんな方法を利用するつもりですか。実際には、IT認定試験を受験して認証資格を取るのは一つの良い方法です。最近、AmazonのAWS-DevOps-Engineer-Professionalテキスト試験は非常に人気のある認定試験です。 しかし、AmazonのAWS-DevOps-Engineer-Professionalテキスト認定試験に合格するという夢は、NewValidDumpsに対して、絶対に掴められます。NewValidDumpsは親切なサービスで、AmazonのAWS-DevOps-Engineer-Professionalテキスト問題集が質の良くて、AmazonのAWS-DevOps-Engineer-Professionalテキスト認定試験に合格する率も１００パッセントになっています。 あなたは試験の最新バージョンを提供することを要求することもできます。

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AWS-DevOps-Engineer-Professional PDF DEMO:

QUESTION NO: 1
A DevOps Engineer must create a Linux AMI in an automated fashion. The newly created AMI identification must be stored in a location where other build pipelines can access the new identification programmatically What is the MOST cost-effective way to do this?
A. Build a pipeline in AWS CodePipeline to download and save the latest operating system Open
Virtualization Format (OVF) image to an Amazon S3 bucket, then customize the image using the guestfish utility. Use the virtual machine (VM) import command to convert the OVF to an AMI, and store the AMI identification output as an AWS Systems Manager parameter.
B. Create an AWS Systems Manager automation document with values instructing how the image should be created. Then build a pipeline in AWS CodePipeline to execute the automation document to build the AMI when triggered. Store the AMI identification output as a Systems Manager parameter.
C. Launch an Amazon EC2 instance and install Packer. Then configure a Packer build with values defining how the image should be created. Build a Jenkins pipeline to invoke the Packer build when triggered to build an AMI. Store the AMI identification output in an Amazon DynamoDB table.
D. Build a pipeline in AWS CodePipeline to take a snapshot of an Amazon EC2 instance running the latest version of the application. Then start a new EC2 instance from the snapshot and update the running instance using an AWS Lambda function. Take a snapshot of the updated instance, then convert it to an AMI. Store the AMI identification output in an Amazon DynamoDB table.
Answer: C

QUESTION NO: 2
A company is migrating an application to AWS that runs on a single Amazon EC2 instance.
Because of licensing limitations, the application does not support horizontal scaling. The application will be using Amazon Aurora for its database.
How can the DevOps Engineer architect automated healing to automatically recover from EC2 and
Aurora failures, in addition to recovering across Availability Zones (AZs), in the MOST cost-effective manner?
A. Create an EC2 instance and enable instance recovery. Create an Aurora database with a read replica in a second AZ, and promote it to a primary database instance if the primary database instance fails.
B. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to start a new EC2 instance in an available AZ when the instance status reaches a failure state. Create an Aurora database with a read replica in a second AZ, and promote it to a primary database instance when the primary database instance fails.
C. Create an EC2 Auto Scaling group with a minimum and maximum instance count of 1, and have it span across AZs. Use a single-node Aurora instance.
D. Assign an Elastic IP address on the instance. Create a second EC2 instance in a second AZ. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to move the Elastic IP address to the second instance when the first instance fails. Use a single-node Aurora instance.
Answer: B

QUESTION NO: 3
An Application team is refactoring one of its internal tools to run in AWS instead of on- premises hardware.
All of the code is currently written in Python and is standalone. There is also no external state store or relational database to be queried.
Which deployment pipeline incurs the LEAST amount of changes between development and production?
A. Developers should use their native Python environment. When Dependencies are changed and a new container is ready, use AWS CodePipeline and AWS CodeBuild to perform functional tests and then upload the new container to the Amazon ECR. Use AWS CloudFormation with the custom container to deploy the new Amazon ECS.
B. Developers should use Docker for local development. Use AWS SMS to import these containers as
AMIs for Amazon EC2 whenever dependencies are updated. Use AWS CodePipeline to test new code changes against the Auto Scaling group.
C. Developers should use their native Python environment. When Dependencies are changed and a new code is ready, use AWS CodePipeline and AWS CodeBuild to perform functional tests and then upload the new container to the Amazon ECR. Use CodePipeline and CodeBuild with the custom container to test new code changes inside AWS Elastic Beanstalk
Answer: B

QUESTION NO: 4
Am Amazon EC2 instance with no internet access is running in a Virtual Private Cloud (VPC) and needs to download an object from a restricted Amazon S3 bucket. When the DevOps Engineer tries to gain access to the object, an Access Denied error is received.
What are the possible causes for this error? (Select THREE.)
A. There is an error in the S3 bucket policy.
B. S3 versioning is enabled.
C. The object has been moved to Amazon Glacier.
D. There is an error in the VPC endpoint policy.
E. The S3 bucket default encryption is enabled.
F. There is an error in the IAM role configuration.
Answer: A,D,F

QUESTION NO: 5
A company has an application that has predictable peak traffic times. The company wants the application instances to scale up only during the peak times. The application stores state in Amazon
DynamoDB. The application environment uses a standard Node.js application stack and custom Chef recipes stored in a private Git repository.
Which solution is MOST cost-effective and requires the LEAST amount of management overhead when performing rolling updates of the application environment?
A. Configure AWS OpsWorks stacks and push the custom recipes to an Amazon S3 bucket and configure custom recipes to point to the S3 bucket. Then add an application layer type for a standard
Node.js application server and configure the custom recipe to deploy the application in the deploy step from the S3 bucket. Configure time-based instances and attach an Amazon EC2 IAM role that provides permission to access DynamoDB
B. Create a custom AMI with the Node.js environment and application stack using Chef recipes. Use the AMI in an Auto Scaling group and set up scheduled scaling for the required times, then set up an
Amazon EC2 IAM role that provides permission to access DynamoDB.
C. Create a Docker file that uses the Chef recipes for the application environment based on an official
Node.js Docker image. Create an Amazon ECS cluster and a service for the application environment, then create a task based on this Docker image. Use scheduled scaling to scale the containers at the appropriate times and attach a task-level IAM role that provides permission to access DynamoD
D. Configure AWS OpsWorks stacks and use custom Chef cookbooks. Add the Git repository information where the custom recipes are stored, and add a layer in OpsWorks for the Node.js application server.
Then configure the custom recipe to deploy the application in the deploy step. Configure time-based instances and attach an Amazon EC2 IAM role that provides permission to access DynamoDB.
Answer: A

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Updated: May 28, 2022