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NEW QUESTION 35
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?
- A. 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.
- B. 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.
- C. 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.
- 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. 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.
NEW QUESTION 36
Your CTO thinks your AWS account was hacked. What is the only way to know for certain if there was unauthorized access and what they did, assuming your hackers are very sophisticated AWS engineers and doing everything they can to cover their tracks?
- A. Use CloudTrail Log File Integrity Validation.
- B. Use AWS Config Timeline forensics.
- C. Use AWS Config SNS Subscriptions and process events in real time.
- D. Use CloudTrail backed up to AWS S3 and Glacier.
To determine whether a log file was modified, deleted, or unchanged after CloudTrail delivered it, you can use CloudTrail log file integrity validation. This feature is built using industry standard algorithms: SHA-256 for hashing and SHA-256 with RSA for digital signing. This makes it computationally infeasible to modify, delete or forge CloudTrail log files without detection. You can use the AWS CLI to validate the files in the location where CloudTrail delivered them Validated log files are invaluable in security and forensic investigations. For example, a validated log file enables you to assert positively that the log file itself has not changed, or that particular user credentials performed specific API activity. The CloudTrail log file integrity validation process also lets you know if a log file has been deleted or changed, or assert positively that no log files were delivered to your account during a given period of time.
For more information on Cloudtrail log file validation, please visit the below URL:
NEW QUESTION 37
By default, Amazon CloudTrail logs ____ actions defined by the CloudTrail ____ APIs.
- A. bucket-level; SDK
- B. bucket-level; RESTful
- C. object-level; SDK
- D. object-level; RESTful
By default, CloudTrail logs bucket-level actions. Amazon S3 records are written together with other AWS service records in a log file. Amazon S3 bucket-level actions supported for logging by CloudTrail are defined in its RESTful API.
NEW QUESTION 38