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NEW QUESTION 30
You recently encountered a major bug in your web application during a deployment cycle. During this failed
deployment, it took the team four hours to roll back to a previously working state, which left customers with a
poor user experience. During the post-mortem, you team discussed the need to provide a quicker, more robust
way to roll back failed deployments. You currently run your web application on Amazon EC2 and use Elastic
Load Balancingforyour load balancing needs.
Which technique should you use to solve this problem?
- A. UsingElastic BeanStalk redeploy your web application and use the Elastic BeanStalkAPI to trigger a
FailedDeployment API call to initiate a rollback to theprevious version. - B. Createdeployable versioned bundles of your application. Store the bundle on AmazonS3. Use an AWS
OpsWorks stack to redeploy your web application and use AWSOpsWorks application versioningto
initiate a rollback during failures. - C. Usean AWS OpsWorks stack to re-deploy your web application and use AWS
OpsWorksDeploymentCommand to initiate a rollback during failures. - D. Createdeployable versioned bundles of your application. Store the bundle on AmazonS3. Re-deploy
your web application on Elastic Beanstalk and enable the ElasticBeanstalk auto - rollbackfeature tied to
Cloud Watch metrics that definefailure.
Answer: C
Explanation:
Explanation
The AWS Documentation mentions the following
AWS DeploymentCommand has a rollback option in it. Following commands are available for apps to use:
deploy: Deploy App.
Ruby on Rails apps have an optional args parameter named migrate. Set Args to {"migrate":["true"]) to
migrate the database.
The default setting is {"migrate": ["false"]).
The "rollback" feature Rolls the app back to the previous version.
When we are updating an app, AWS OpsWorks stores the previous versions, maximum of upto five versions.
We can use this command to roll an app back as many as four versions.
Reference Link:
* http://docs^ws.amazon.com/opsworks/latest/APIReference/API_DeploymentCommand.html
NEW QUESTION 31
A company is using AWS for an application. The Development team must automate its deployments. The team has set up an AWS CodePipeline to deploy the application to Amazon EC2 instances by using AWS CodeDeploy after it has been built using the AWS CodeBuild service. The team would like to add automated testing to the pipeline to confirm that the application is healthy before deploying it to the next stage of the pipeline using the same code. The team requires a manual approval action before the application is deployed, even if the test is successful. The testing and approval must be accomplished at the lowest costs, using the simplest management solution. Which solution will meet these requirements?
- A. Add a test action after the last deploy action of the pipeline. Configure the action to use CodeBuild to perform the required tests. If these tests are successful, mark the action as successful. Add a manual approval action that uses Amazon SNS to notify the team, and add a deploy action to deploy the application to the next stage.
- B. Add a manual approval action after the last deploy action of the pipeline. Use Amazon SNS to inform the team of the stage being triggered. Next, add a test action using CodeBuild to do the required tests. At the end of the pipeline, add a deploy action to deploy the application to the next stage.
- C. Add a test action after the last deployment action. Use a Jenkins server on Amazon EC2 to do the required tests and mark the action as successful if the tests pass. Create a manual approval action that uses Amazon SQS to notify the team and add a deploy action to deploy the application to the next stage.
- D. Create a new pipeline that uses a source action that gets the code from the same repository as the first pipeline. Add a deploy action to deploy the code to a test environment. Use a test action using AWS Lambda to test the deployment. Add a manual approval action by using Amazon SNS to notify the team, and add a deploy action to deploy the application to the next stage.
Answer: A
Explanation:
https://docs.aws.amazon.com/codebuild/latest/userguide/sample-build-notifications.html
NEW QUESTION 32
You are building an AWS CloudFormation template for a multi-tier web application.
The user data of your Linux web server resource contains a complex script that can take a long time to run.
Which techniques could you use to ensure that these servers are fully configured and running before attaching them to the load balancer? Choose 2 answers
- A. In your AWS CloudFormation template, position the load balancer resource JSON block directly below your Linux server resource.
- B. Launch your Linux servers from a nested stack that is called from within the load balancer resource in your AWS CloudFormation template.
- C. Add an AWS CloudFormation Wait Condition that depends on the web server resource.
When the UserData script finishes on the web servers, use curl to send a signal the Wait Condition at http://169.254.169.254/waithandle/. - D. Add an AWS CloudFormation Wait Condition that depends on the web server resource.
When the UserData script finishes on the web servers, use the command "cfn-signal" to signal that they are ready. - E. Add an AWS CloudFormation wait Condition that depends on the web server resource.
When the UserData script finishes on the web servers, use curl to signal to the Wait Condition pre-signed URL that they are ready.
Answer: D,E
NEW QUESTION 33
You want to pass queue messages that are 1GB each. How should you achieve this?
- A. Use the Amazon SQS Extended Client Library for Java and Amazon S3 as a storage mechanism for message bodies.
- B. Use AWS EFS as a shared pool storage medium. Store filesystem pointers to the files on disk in the SQS message bodies.
- C. Use SQS's support for message partitioning and multi-part uploads on Amazon S3.
- D. Use Kinesis as a buffer stream for message bodies. Store the checkpoint id for the placement in the Kinesis Stream in SQS.
Answer: A
Explanation:
Explanation
You can manage Amazon SQS messages with Amazon S3. This is especially useful for storing and consuming messages with a message size of up to 2 GB. To manage Amazon SQS messages with Amazon S3, use the Amazon SQS Extended Client Library for Java. Specifically, you use this library to:
* Specify whether messages are always stored in Amazon S3 or only when a message's size exceeds 256 KB.
* Send a message that references a single message object stored in an Amazon S3 bucket.
* Get the corresponding message object from an Amazon S3 bucket.
* Delete the corresponding message object from an Amazon S3 bucket.
For more information on processing large messages for SQS, please visit the below URL:
* http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-s3-messages.
html
NEW QUESTION 34
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