AMAZON DOP-C01 RELIABLE EXAM TUTORIAL, DOP-C01 EXAMCOLLECTION

Amazon DOP-C01 Reliable Exam Tutorial, DOP-C01 Examcollection

Amazon DOP-C01 Reliable Exam Tutorial, DOP-C01 Examcollection

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Tags: DOP-C01 Reliable Exam Tutorial, DOP-C01 Examcollection, DOP-C01 Exam Registration, Test DOP-C01 Engine Version, Reliable DOP-C01 Braindumps Ebook

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To prepare for the AWS Certified DevOps Engineer - Professional (DOP-C01) certification exam, individuals should have several years of experience working with AWS and should be familiar with DevOps practices and principles. AWS offers a range of training and certification resources, including instructor-led courses, online training, practice exams, and certification guides. By earning this certification, individuals can demonstrate their expertise in DevOps practices and become highly valuable assets to organizations that rely on AWS for their infrastructure needs.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q229-Q234):

NEW QUESTION # 229
Management has reported an increase in the monthly bill from Amazon Web Services, and they are extremely concerned with this increased cost. Management has asked you to determine the exact cause of this increase.
After reviewing the billing report, you notice an increase in the data transfer cost. How can you provide management with a better insight into data transfer use?

  • A. Update your Amazon CloudWatch metrics to use five-second granularity, which will give better detailed metrics that can be combined with your billing data to pinpoint anomalies.
  • B. Deliver custom metrics to Amazon CloudWatch per application that breaks down application data transfer into multiple, more specific data points.
    D- Using Amazon CloudWatch metrics, pull your Elastic Load Balancing outbound data transfer metrics monthly, and include them with your billing report to show which application is causing higher bandwidth usage.
  • C. Use Amazon CloudWatch Logs to run a map-reduce on your logs to determine high usage and data transfer.

Answer: B

Explanation:
Explanation
You can publish your own metrics to CloudWatch using the AWS CLI or an API. You can view statistical graphs of your published metrics with the AWS Management Console.
CloudWatch stores data about a metric as a series of data points. Each data point has an associated time stamp.
You can even publish an aggregated set of data points called a statistic set.
If you have custom metrics specific to your application, you can give a breakdown to the management on the exact issue.
Option A won't be sufficient to provide better insights.
Option B is an overhead when you can make the application publish custom metrics Option D is invalid because just the ELB metrics will not give the entire picture For more information on custom metrics, please refer to the below document link: from AWS
* http://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/publishingMetrics.htmI


NEW QUESTION # 230
You are using Autoscaling for managing the instances in your AWS environment. You need to deploy a new
version of your application. You'd prefer to use all new instances if possible, but you cannot have any
downtime. You also don't want to swap any environment urls. Which of the following deployment methods
would you implement

  • A. Using"RollingUpdates"deploymentmethod.
  • B. Using "All at once" deployment method.
  • C. Using "Blue Green" with "All at once" deployment method.
  • D. Using "Blue Green" deployment method.

Answer: A

Explanation:
Explanation
In Rolling deployment, you can mention a new set of servers which can replace the existing set of servers.
This replacement will happen in a phased out manner.
Since there is a requirement to not swap URL's, you must not use Blue Green deployments.
For more information on the differences between Rolling Updates and Blue Green deployments, please refer
to the below URL:
* https://cloudnative.io/docs/blue-green-deployment/


NEW QUESTION # 231
A company is deploying a container-based application using AWS CodeBuild. The Security team mandates that all containers are scanned for vulnerabilities prior to deployment using a password-protected endpoint. All sensitive information must be stored securely.
Which solution should be used to meet these requirements?

  • A. Use the AWS Encryption SDK to encrypt the password and embed in the buildspec.yml file as a variable under the secrets mapping. Attach a policy to CodeBuild to enable access to the required decryption key.
  • B. Import the password into an AWS CloudHSM key. Reference the CloudHSM key in the buildpec.yml file as an environment variable under the variables mapping. Reference the environment variable to initiate scanning.
  • C. Encrypt the password using AWS KMS. Store the encrypted password in the buildspec.yml file as an environment variable under the variables mapping. Reference the environment variable to initiate scanning.
  • D. Store the password in the AWS Systems Manager Parameter Store as a secure string. Add the Parameter Store key to the buildspec.yml file as an environment variable under the parameter-store mapping.
    Reference the environment variable to initiate scanning.

Answer: D


NEW QUESTION # 232
You have a large number of web servers in an Auto Scaling group behind a load balancer. On an hourly basis, you want to filter and process the logs to collect data on unique visitors, and then put that data in a durable data store in order to run reports. Web servers in the Auto Scaling group are constantly launching and terminating based on your scaling policies, but you do not want to lose any of the log data from these servers during a stop/termination initiated by a user or by Auto Scaling.
What two approaches will meet these requirements?
Choose 2 answers

  • A. On the web servers, create a scheduled task that executes a script to rotate and transmit the logs to Amazon Glacier.
    Ensure that the operating system shutdown procedure triggers a logs transmission when the Amazon EC2 instance is stopped/terminated.
    Use Amazon Data Pipeline to process the data in Amazon Glacier and run reports every hour.
  • B. Install an AWS Data Pipeline Logs Agent on every web server during the bootstrap process.
    Create a log group object in AWS Data Pipeline, and define Metric Filters to move processed log data directly from the web servers to Amazon Redshift and run reports every hour.
  • C. Install an Amazon Cloudwatch Logs Agent on every web server during the bootstrap process.
    Create a CloudWatch log group and define Metric Filters to create custom metrics that track unique visitors from the streaming web server logs.
    Create a scheduled task on an Amazon EC2 instance that runs every hour to generate a new report based on the Cloudwatch custom metrics.
  • D. On the web servers, create a scheduled task that executes a script to rotate and transmit the logs to an Amazon S3 bucket.
    Ensure that the operating system shutdown procedure triggers a logs transmission when the Amazon EC2 instance is stopped/terminated.
    Use AWS Data Pipeline to move log data from the Amazon S3 bucket to Amazon Redshift In order to process and run reports every hour.

Answer: C,D


NEW QUESTION # 233
An online company uses Amazon EC2 Auto Scaling extensively to provide an excellent customer experience while minimizing the number of running EC2 instances. The company's self-hosted Puppet environment in the application layer manages the configuration of the instances. The IT manager wants the lowest licensing costs and wants to ensure that whenever the EC2 Auto Scaling group scales down, removed EC2 instances are deregistered from the Puppet master as soon as possible.
How can the requirement be met?

  • A. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. Use CodeDeploy to install the Puppet agent. When the Auto Scaling group scales out, run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 Auto Scaling EC2_INSTANCE_TERMINATING lifecycle hook to trigger de- registration from the Puppet master.
  • B. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 user data instance stop script to run a script to de-register the instance from the Puppet master.
  • C. Bake the AWS Systems Manager agent into the base AMI. When the Auto Scaling group scales out, use the AWS Systems Manager to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the Systems Manager instance stop lifecycle hook to run a script to de-register the instance from the Puppet master.
  • D. Bake the AWS CodeDeploy agent into the base AMI. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and execute a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the CodeDeploy lifecycle hook to run a script to de-register the instance from the Puppet master.
    ApplicationStop

Answer: A

Explanation:
codedeploy agent is a software package that, when installed and configured on an instance, makes it possible for that instance to be used in CodeDeploy deployments.


NEW QUESTION # 234
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