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NEW QUESTION 39
You have an I/O and network-intensive application running on multiple Amazon EC2 instances that cannot
handle a large ongoing increase in traffic. The Amazon EC2 instances are using two Amazon EBS PIOPS
volumes each, and each instance is identical.
Which of the following approaches should be taken in order to reduce load on the instances with the least
disruption to the application?
- A. Addan Amazon EBS volume for each running Amazon EC2 instance and implement RAIDstripingto
improve I/O performance. - B. Createan AMI from an instance, and set up an Auto Scaling group with an instance typethat has
enhanced networking enabled and is Amazon EBS-optimized. - C. Stopeach instance and change each instance to a larger Amazon EC2 instance typethat has enhanced
networking enabled and is Amazon EBS-optimized. Ensure thatRAID striping is also set up on each
instance. - D. Addan instance-store volume for each running Amazon EC2 instance and implementRAID striping to
improve I/O performance. - E. Createan AMI from each instance, and set up Auto Scaling groups with a largerinstance type that has
enhanced networking enabled and is Amazon EBS-optimized.
Answer: B
Explanation:
Explanation
The AWS Documentation mentions the following on AMI's
An Amazon Machine Image (AMI) provides the information required to launch an instance, which is a virtual
server in the cloud. You specify an AM I when you launch
an instance, and you can launch as many instances from the AMI as you need. You can also launch instances
from as many different AMIs as you need.
For more information on AMI's, please visit the link:
* http://docs.aws.amazon.com/AWSCC2/latest/UserGuide/AMIs.html
NEW QUESTION 40
For auditing, analytics, and troubleshooting purposes, a DevOps Engineer for a data analytics application needs to collect all of the application and Linux system logs from the Amazon EC2 instances before termination. The company, on average, runs 10,000 instances in an Auto Scaling group. The company requires the ability to quickly find logs based on instance IDs and date ranges.
Which is the MOST cost-effective solution?
- A. Create an EC2 Instance-terminate Lifecycle Actionon the group, push the logs into Amazon Kinesis Data Firehose, and select Amazon ES as the destination for providing storage and search capability.
- B. Create an EC2 Instance-terminate Lifecycle Actionon the group, write a termination script for pushing logs into Amazon S3, and trigger an AWS Lambda function based on S3 PUT to create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.
- C. Create an EC2 Instance-terminate Lifecycle Action on the group, create an Amazon CloudWatch Events rule based on it to trigger an AWS Lambda function for storing the logs in Amazon S3, and create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.
- D. Create an EC2 Instance-terminate Lifecycle Actionon the group, write a termination script for pushing logs into Amazon CloudWatch Logs, create a CloudWatch Events rule to trigger an AWS Lambda function to create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.
Answer: A
Explanation:
Explanation/Reference:
NEW QUESTION 41
A company used AWS CloudFormation to deploy a three-tier web application that stores data in an Amazon RDS MySOL Multi-AZ DB instance. A DevOps Engineer must upgrade the RDS instance to the latest major version of MySQL while incurring minimal downtime.
How should the Engineer upgrade the instance while minimizing downtime?
- A. Update the EngineVersionproperty of the AWS::RDS::DBInstanceresource type in the CloudFormation template to the latest desired version. Launch a second stack and make the new RDS instance a read replica.
- B. Update the DBEngineVersionproperty of the AWS::RDS::DBInstanceresource type in the CloudFormation template to the latest desired version. Create a new RDS Read Replicas resource with the same properties as the instance to be upgraded. Perform an Update Stackoperation.
- C. Update the DBEngineVersionproperty of the AWS:: RDS::DBInstanceresource type in the CloudFormation template to the latest desired version. Perform an Update Stackoperation. Create a new RDS Read Replicas resource with the same properties as the instance to be upgraded. Perform a second Update Stackoperation.
- D. Update the EngineVersionproperty of the AWS::RDS::DBInstanceresource type in the CloudFormation template to the latest version, and perform an Update Stackoperation.
Answer: A
NEW QUESTION 42
A global company with distributed Development teams built a web application using a microservices architecture running on Amazon ECS. Each application service is independent and runs as a service in the ECS cluster. The container build files and source code reside in a private GitHub source code repository.
Separate ECS clusters exist for development, testing, and production environments.
Developers are required to push features to branches in the GitHub repository and then merge the changes into an environment-specific branch (development, test, or production). This merge needs to trigger an automated pipeline to run a build and a deployment to the appropriate ECS cluster.
What should the DevOps Engineer recommend as an automated solution to these requirements?
- A. Create an AWS CloudFormation stack for the ECS cluster and AWS CodePipeline services. Store the container build files in an Amazon S3 bucket. Use a post-commit hook to trigger a CloudFormation stack update that deploys the ECS cluster. Add a task in the ECS cluster to build and push images to Amazon ECR, based on the container build files in S3.
- B. Create a pipeline in AWS CodePipeline. Configure it to be triggered by commits to the master branch in GitHub. Add a stage to use the Git commit message to determine which environment the commit should be applied to, then call the create-imageAmazon ECR command to build the image, passing it to the container build file. Then add a stage to update the ECS task and service definitions in the appropriate cluster for that environment.
- C. Create a separate pipeline in AWS CodePipeline for each environment. Trigger each pipeline based on commits to the corresponding environment branch in GitHub. Add a build stage to launch AWS CodeBuild to create the container image from the build file and push it to Amazon ECR. Then add another stage to update the Amazon ECS task and service definitions in the appropriate cluster for that environment.
- D. Create a new repository in AWS CodeCommit. Configure a scheduled project in AWS CodeBuild to synchronize the GitHub repository to the new CodeCommit repository. Create a separate pipeline for each environment triggered by changes to the CodeCommit repository. Add a stage using AWS Lambda to build the container image and push to Amazon ECR. Then add another stage to update the ECS task and service definitions in the appropriate cluster for that environment.
Answer: A
NEW QUESTION 43
An Application team has three environments for their application: development, pre-production, and production. The team recently adopted AWS CodePipeline. However, the team has had several deployments of misconfigured or nonfunctional development code into the production environment, resulting in user disruption and downtime. The DevOps Engineer must review the pipeline and add steps to identify problems with the application before it is deployed.
What should the Engineer do to identify functional issues during the deployment process?
(Choose two.)
- A. Use Amazon Inspector to add a test action to the pipeline. Use the Amazon Inspector Runtime Behavior Analysis Inspector rules package to check that the deployed code complies with company security standards before deploying it to production.
- B. Add an AWS CodeDeploy action in the pipeline to deploy the latest version of the development code to pre-production. Add a manual approval action in the pipeline so that the QA team can test and confirm the expected functionality. After the manual approval action, add a second CodeDeploy action that deploys the approved code to the production environment.
- C. Create an AWS CodeDeploy action in the pipeline with a deployment configuration that automatically deploys the application code to a limited number of instances. The action then pauses the deployment so that the QA team can review the application functionality. When the review is complete, CodeDeploy resumes and deploys the application to the remaining production Amazon EC2 instances.
- D. Using AWS CodeBuild to add a test action to the pipeline to replicate common user activities and ensure that the results are as expected before progressing to production deployment.
- E. After the deployment process is complete, run a testing activity on an Amazon EC2 instance in a different region that accesses the application to simulate user behavior if unexpected results occur, the testing activity sends a warning to an Amazon SNS topic. Subscribe to the topic to get updates.
Answer: B,D
Explanation:
https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action- type.html#integrations-test
https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action- type.html#integrations-deploy
NEW QUESTION 44
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