A company has multiple AWS accounts. The company uses AWS IAM Identity Center (AWS Single Sign-On) that is integrated with AWS Toolkit for Microsoft Azure DevOps. The attributes for access control feature is enabled in IAM Identity Center.
The attribute mapping list contains two entries. The department key is mapped to ${path:enterprise.department}. The costCenter key is mapped to ${path:enterprise.costCenter}.
All existing Amazon EC2 instances have a department tag that corresponds to three company departments (d1, d2, d3). A DevOps engineer must create policies based on the matching attributes. The policies must minimize administrative effort and must grant each Azure AD user access to only the EC2 instances that are tagged with the user’s respective department name.
Which condition key should the DevOps engineer include in the custom permissions policies to meet these requirements?
A company uses AWS CloudFormation to deploy application environments. A deployment failed due to manual modifications in stack resources. The DevOps engineer wants to detect manual modifications and alert the DevOps lead with the least effort.
Which solution meets these requirements?
A company needs to implement failover for its application. The application includes an Amazon CloudFront distribution and a public Application Load Balancer (ALB) in an AWS Region. The company has configured the ALB as the default origin for the distribution.
After some recent application outages, the company wants a zero-second RTO. The company deploys the application to a secondary Region in a warm standby configuration. A DevOps engineer needs to automate the failover of the application to the secondary Region so that HTTP GET requests meet the desired R TO.
Which solution will meet these requirements?
A company has application code in an AWS CodeConnections compatible Git repository. The company wants to configure unit tests to run when pull requests are opened. The company wants to ensure that the test status is visible in pull requests when the tests are completed. The company wants to save output data files that the tests generate to an Amazon S3 bucket after the tests are finished. Which combination of solutions will meet these requirements? (Select THREE.)
A company has a new AWS account that teams will use to deploy various applications. The teams will create many Amazon S3 buckets for application- specific purposes and to store AWS CloudTrail logs. The company has enabled Amazon Macie for the account.
A DevOps engineer needs to optimize the Macie costs for the account without compromising the account's functionality.
Which solutions will meet these requirements? (Select TWO.)
A DevOps team is deploying microservices for an application on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The cluster uses managed node groups.
The DevOps team wants to enable auto scaling for the microservice Pods based on a specific CPU utilization percentage. The DevOps team has already installed the Kubernetes Metrics Server on the cluster.
Which solution will meet these requirements in the MOST operationally efficient way?
A DevOps engineer is creating an AWS CloudFormation template to deploy a web service. The web service will run on Amazon EC2 instances in a private subnet behind an Application Load Balancer (ALB). The DevOps engineer must ensure that the service can accept requests from clients that have IPv6 addresses.
What should the DevOps engineer do with the CloudFormation template so that IPv6 clients can access the web service?
A company releases a new application in a new AWS account. The application includes an AWS Lambda function that processes messages from an Amazon Simple Queue Service (Amazon SOS) standard queue. The Lambda function stores the results in an Amazon S3 bucket for further downstream processing. The Lambda function needs to process the messages within a specific period of time after the messages are published. The Lambda function has a batch size of 10 messages and takes a few seconds to process a batch of messages.
As load increases on the application's first day of service, messages in the queue accumulate at a greater rate than the Lambda function can process the messages. Some messages miss the required processing timelines. The logs show that many messages in the queue have data that is not valid. The company needs to meet the timeline requirements for messages that have valid data.
Which solution will meet these requirements?