Amazon Web Services help2pass passed Exam Today Dop-c02 by Kiyan q8 vce pdf

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Exam Name:	AWS Certified DevOps Engineer - Professional
Exam Code:	DOP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	449 Q&A's	Shared By:	kiyan

Question 64

A company uses AWS and has a VPC that contains critical compute infrastructure with predictable traffic patterns. The company has configured VPC flow logs that are published to a log group in Amazon CloudWatch Logs.

The company ' s DevOps team needs to configure a monitoring solution for the VPC flow logs to identify anomalies in network traffic to the VPC over time. If the monitoring solution detects an anomaly, the company needs the ability to initiate a response to the anomaly.

How should the DevOps team configure the monitoring solution to meet these requirements?

Options:

Create an Amazon Kinesis data stream. Subscribe the log group to the data stream. Configure Amazon Kinesis Data Analytics to detect log anomalies in the data stream. Create anAWS Lambda function to use as the output of the data stream. Configure the Lambda function to write to the default Amazon EventBridge event bus in the event of an anomaly finding.

Create an Amazon Kinesis Data Firehose delivery stream that delivers events to an Amazon S3 bucket. Subscribe the log group to the delivery stream. Configure Amazon Lookout for Metrics to monitor the data in the S3 bucket for anomalies. Create an AWS Lambda function to run in response to Lookout for Metrics anomaly findings. Configure the Lambda function to publish to the default Amazon EventBridge event bus.

Create an AWS Lambda function to detect anomalies. Configure the Lambda function to publish an event to the default Amazon EventBridge event bus if the Lambda function detects an anomaly. Subscribe the Lambda function to the log group.

Create an Amazon Kinesis data stream. Subscribe the log group to the data stream. Create an AWS Lambda function to detect log anomalies. Configure the Lambda function to write to the default Amazon EventBridge event bus if the Lambda function detects an anomaly. Set the Lambda function as the processor for the data stream.

Discussion

Question 65

A production account has a requirement that any Amazon EC2 instance that has been logged in to manually must be terminated within 24 hours. All applications in the production account are using Auto Scaling groups with the Amazon CloudWatch Logs agent configured.

How can this process be automated?

Options:

Create a CloudWatch Logs subscription to an AWS Step Functions application. Configure an AWS Lambda function to add a tag to the EC2 instance that produced the login event and mark the instance to be decommissioned. Create an Amazon EventBridge rule to invoke a second Lambda function once a day that will terminate all instances with this tag.

Create an Amazon CloudWatch alarm that will be invoked by the login event. Send the notification to an Amazon Simple Notification Service (Amazon SNS) topic that the operations team is subscribed to, and have them terminate the EC2 instance within 24 hours.

Create an Amazon CloudWatch alarm that will be invoked by the login event. Configure the alarm to send to an Amazon Simple Queue Service (Amazon SQS) queue. Use a group of worker instances to process messages from the queue, which then schedules an Amazon EventBridge rule to be invoked.

Create a CloudWatch Logs subscription to an AWS Lambda function. Configure the function to add a tag to the EC2 instance that produced the login event and mark the instance to be decommissioned. Create an Amazon EventBridge rule to invoke a daily Lambda function that terminates all instances with this tag.

Discussion

Question 66

A DevOps engineer is researching the least expensive way to implement an image batch processing cluster on AWS. The application cannot run in Docker containers and must run on Amazon EC2. The batch job stores checkpoint data on an NFS volume and can tolerate interruptions. Configuring the cluster software from a generic EC2 Linux image takes 30 minutes.

What is the MOST cost-effective solution?

Options:

Use Amazon EFS (or checkpoint data. To complete the job, use an EC2 Auto Scaling group and an On-Demand pricing model to provision EC2 instances temporally.

Use GlusterFS on EC2 instances for checkpoint data. To run the batch job configure EC2 instances manually When the job completes shut down the instances manually.

Use Amazon EFS for checkpoint data Use EC2 Fleet to launch EC2 Spot Instances and utilize user data to configure the EC2 Linux instance on startup.

Use Amazon EFS for checkpoint data Use EC2 Fleet to launch EC2 Spot Instances Create a custom AMI for the cluster and use the latest AMI when creating instances.

Discussion

Question 67

A DevOps engineer wants to find a solution to migrate an application from on premises to AWS The application is running on Linux and needs to run on specific versions of Apache Tomcat HAProxy and Varnish Cache to function properly. The application ' s operating system-level parameters require tuning The solution must include a way to automate the deployment of new application versions. The infrastructure should be scalable and faulty servers should be replaced automatically.

Which solution should the DevOps engineer use?

Options:

Upload the application as a Docker image that contains all the necessary software to Amazon ECR Create an Amazon ECS cluster using an AWS Fargate launch type and an Auto Scaling group. Create an AWS CodePipeline pipeline that uses Amazon ECR as a source and Amazon ECS as a deployment provider

Upload the application code to an AWS CodeCommit repository with a saved configuration file to configure and install the software Create an AWS Elastic Beanstalk web server tier and a load balanced-type environment that uses the Tomcat solution stack Create an AWS CodePipeline pipeline that uses CodeCommit as a source and Elastic Beanstalk as a deployment provider

Upload the application code to an AWS CodeCommit repository with a set of ebextensions files to configure and install the software. Create an AWS Elastic Beanstalk worker tier environment that uses the Tomcat solution stack Create an AWS CodePipeline pipeline that uses CodeCommit as a source and Elastic Beanstalk as a deployment provider

Upload the application code to an AWS CodeCommit repository with an appspec.yml file to configure and install the necessary software. Create an AWS CodeDeploy deployment group associated with an Amazon EC2 Auto Scaling group Create an AWS CodePipeline pipeline that uses CodeCommit as a source and CodeDeploy as a deployment provider

Discussion

Answer:

Explanation:

The correct answer is D. The scenario requires a solution that can migrate an application from on premises to AWS, run on specific versions of Apache Tomcat, HAProxy, and Varnish Cache, tune the operating system-level parameters, automate the deployment of new application versions, and scale and replace faulty servers automatically. Option D meets all these requirements by using AWS CodeCommit, AWS CodeDeploy, AWS CodePipeline, and Amazon EC2 Auto Scaling. AWS CodeCommit is a fully managed source control service that hosts Git repositories and works with Git-based tools. AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services, including Amazon EC2, AWS Fargate, AWS Lambda, and on-premises servers. AWS CodePipeline is a fully managed continuous delivery service that helps automate the release pipelines for fast and reliable application updates. Amazon EC2 Auto Scaling helps maintain application availability and allows scaling of Amazon EC2 capacity up or down automatically according to the defined conditions. By using these services together, the DevOps engineer can migrate the application code to AWS, configure and install the necessary software using the appspec.yml file, automate the deployment process using the pipeline, and scale and replace the servers using the Auto Scaling group.

Option A is incorrect because AWS Fargate is a serverless compute engine for containers that works with Amazon ECS and Amazon EKS. Fargate removes the need to provision and manage servers, but it also limits the ability to tune the operating system-level parameters, which is a requirement in the scenario. Moreover, Fargate does not support HAProxy and Varnish Cache as sidecar containers, which are needed to run the application properly.

Option B is incorrect because AWS Elastic Beanstalk is a fully managed service that automates the deployment and scaling of web applications and services using familiar servers such as Apache, Nginx, Passenger, and IIS. However, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly. Moreover, Elastic Beanstalk web server tier environments are designed to serve HTTP requests, not to process background tasks, which is the purpose of worker tier environments.

Option C is incorrect because AWS Elastic Beanstalk worker tier environments are designed to process background tasks using a daemon process that runs on each Amazon EC2 instance in the environment. Worker tier environments are not suitable for running web applications that serve HTTP requests, which is the case in the scenario. Moreover, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly.

AWS CodeCommit

AWS CodeDeploy

AWS CodePipeline

Amazon EC2 Auto Scaling

AWS Fargate

AWS Elastic Beanstalk

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