A. Create an Amazon ECS cluster with the container instances in an Auto Scaling group. Configure the ECS service to use Service Auto Scaling. Set up Amazon CloudWatch alarms to scale the ECS service and cluster.

B. Deploy containers on an AWS Elastic Beanstalk Multicontainer Docker environment. Configure Elastic Beanstalk to automatically scale the environment based on Amazon CloudWatch metrics.

C. Create an Amazon ECS cluster using Spot Instances. Configure the ECS service to use Service Auto Scaling. Set up Amazon CloudWatch alarms to scale the ECS service and cluster.

D. Deploy containers on Amazon EC2 instances. Deploy a container scheduler to schedule containers onto EC2 instances. Configure EC2 Auto Scaling for EC2 instances based on available Amazon CloudWatch metrics.

A. Create an AWS CloudWatch Logs subscription that filters on ג€detail-typeג€: ג€CodePipeline Pipeline Execution State Change.ג€ Forward that to an Amazon SNS topic. Add the chat webhook URL to the SNS topic as a subscriber and complete the subscription validation.

B. Create an AWS Lambda function that is triggered by the updating of AWS CloudTrail events. When a ג€CodePipeline Pipeline Execution State Changeג€ event is detected in the updated events, send the event details to the chat webhook URL.

C. Create an AWS CloudWatch Events rule that filters on ג€CodePipeline Pipeline Execution State Change.ג€ Forward that to an Amazon SNS topic. Subscribe an AWS Lambda function to the Amazon SNS topic and have it forward the event to the chat webhook URL.

D. Modify the pipeline code to send event details to the chat webhook URL at the end of each stage. Parameterize the URL so each pipeline can send to a different URL based on the pipeline environment.

A. Apply constraints to the parameters in the templates, limiting the VPCs available for deployments. Store the templates on Amazon S3. Create an IAM group for beginners and give them access to the templates and CloudFormation. Create a separate group for experts, giving them access to the templates, CloudFormation, and other AWS services.

B. Store the templates on Amazon S3. Use AWS Service Catalog to create a portfolio of products based on those templates. Apply template constraints to the products with rules limiting VPCs available for deployments. Create an IAM group for beginners giving them access to the portfolio. Create a separate group for experts giving them access to the templates, CloudFormation, and other AWS services.

C. Store the templates on Amazon S3. Use AWS Service Catalog to create a portfolio of products based on those templates. Create an IAM role restricting VPCs available for creation of AWS resources. Apply a launch constraint to the products using this role. Create an IAM group for beginners giving them access to the portfolio. Create a separate group for experts giving them access to the portfolio and other AWS services.

D. Create two templates for each architecture blueprint where only one of them limits the VPC available for deployments. Store the templates in Amazon DynamoDB. Create an IAM group for beginners giving them access to the constrained templates and CloudFormation. Create a separate group for experts giving them access to the unconstrained templates, CloudFormation, and other AWS services.

A. The AWS user or role attempting to execute the CloudFormation template does not have the permissions required to create the resources within the template. The Engineer must review the user policies and add any permissions needed to create the resources and then rerun the template execution.

B. The AWS CloudFormation service cannot be reached and is not capable of creating the cluster. The Engineer needs to confirm that routing and firewall rules are not preventing the AWS CloudFormation script from communicating with the AWS service endpoints, and then rerun the template execution.

C. The CloudFormation execution was not granted the capability to create IAM resources. The Engineer needs to provide CAPABILITY_IAM and CAPABILITY_NAMED_IAM as capabilities in the CloudFormation execution parameters or provide the capabilities in the AWS Management Console.

D. CloudFormation is not capable of fulfilling the request of the specified resources in the current AWS Region. The Engineer needs to specify a new region and rerun the template.

A. Create an AWS CodeDeploy deployment group and associate it with an Auto Scaling group configured to launch instances across subnets in different Availability Zones. Configure an in-place deployment with a CodeDeploy.HalfAtAtime configuration for application deployments.

B. Create an AWS Elastic Beanstalk Java-based environment using Auto Scaling and load balancing. Configure the network setting for the environment to launch instances across subnets in different Availability Zones. Use ג€Rolling with additional batchג€ as a deployment strategy with a batch size of 50%.

C. Create an AWS CodeDeploy deployment group and associate it with an Auto Scaling group configured to launch instances across subnets in different Availability Zones. Configure an in-place deployment with a custom deployment configuration with the MinimumHealthyHosts option set to type FLEET_PERCENT and a value of 50.

D. Create an AWS Elastic Beanstalk Java-based environment using Auto Scaling and load balancing. Configure the network options for the environment to launch instances across subnets in different Availability Zones. Use ג€Rollingג€ as a deployment strategy with a batch size of 50%.

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 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.

C. 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-image Amazon 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.

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.

A. Create an EC2 Instance-terminate Lifecycle Action on 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.

B. Create an EC2 Instance-terminate Lifecycle Action on 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.

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 Action on the group, push the logs into Amazon Kinesis Data Firehose, and select Amazon ES as the destination for providing storage and search capability.

A. Modify the Kinesis consumer application to store the logs durably in Amazon S3. Use Amazon EMR to process the data directly on S3 to derive customer insights and store the results in S3.

B. Horizontally scale the Kinesis consumer application by adding more EC2 instances based on the GetRecord.IteratorAgeMilliseconds Amazon CloudWatch metric. Increase the Kinesis Data Streams retention period.

C. Convert the Kinesis consumer application to run as an AWS Lambda function. Configure the Kinesis Data Streams as the event source for the Lambda function to process the data streams.

D. Increase the number of shards in the Kinesis Data Streams to increase the overall throughput so that the consumer application processes data faster.

A. Create an AWS Lambda function that calls the IAM Access Advisor API to pull service permissions granted on a user-by-user basis for all users in the AWS account. Ensure that Access Advisor is configured with a tracking period of 90 days. Invoke the Lambda function using an Amazon CloudWatch Events rule on a weekly schedule. For each record, by user, by service, if the Access Advisor Last Accesses field indicates a day count instead of ג€Not accesses in the tracking period,ג€ this indicates a delta compared to what is in the userג€™s currently attached access polices. After Lambda has iterated through all users in the AWS account, configure it to generate a report and send the report using Amazon SES.

B. Configure an AWS CloudTrail trail that spans all AWS Regions and all read/write events, and point this trail to an Amazon S3 bucket. Create Amazon Athena table and specify the S3 bucket ARN in the CREATE TABLE query. Create an AWS Lambda function that accesses the Athena table using the SDK, which performs a SELECT, ensuring that the WHERE clause includes userIdentity, eventName, and eventTime. Compare the results against the userג€™s currently attached IAM access policies to determine any deltas. Configure an Amazon CloudWatch Events schedule to automate this process to run once a week. Configure Amazon SES to send a consolidated report to the Information Security team.

C. Configure VPC Flow Logs on all subnets across all VPCs in all regions to capture user traffic across the entire account. Ensure that all logs are being sent to a centralized Amazon S3 bucket, so all flow logs can be consolidated and aggregated. Create an AWS Lambda function that is triggered once a week by an Amazon CloudWatch Events schedule. Ensure that the Lambda function parses the flow log files for the following information: IAM user ID, subnet ID, VPC ID, Allow/Reject status per API call, and service name. Then have the function determine the deltas on a user-by-user basis. Configure the Lambda function to send the consolidated report using Amazon SES.

D. Create an Amazon ES cluster and note its endpoint URL, which will be provided as an environment variable into a Lambda function. Configure an Amazon S3 event on a AWS CloudTrail trail destination S3 bucket and ensure that the event is configured to send to a Lambda function. Create the Lambda function to consume the events, parse the input from JSON, and transform it to an Amazon ES document format. POST the documents to the Amazon ES clusterג€™s endpoint by way of the passed-in environment variable. Make sure that the proper indexing exists in Amazon ES and use Apache Lucene queries to parse the permissions on a user-by-user basis. Export the deltas into a report and have Amazon ES send the reports to the Information Security team using Amazon SES every week.

A. In both regions, deploy the application on AWS Elastic Beanstalk and use Amazon DynamoDB global tables for session data. Use an Amazon Route 53 weighted routing policy with health checks to distribute the traffic across the regions.

B. In both regions, launch the application in Auto Scaling groups and use DynamoDB for session data. Use a Route 53 failover routing policy with health checks to distribute the traffic across the regions.

C. In both regions, deploy the application in AWS Lambda, exposed by Amazon API Gateway, and use Amazon RDS PostgreSQL with cross-region replication for session data. Deploy the web application with client-side logic to call the API Gateway directly.

D. In both regions, launch the application in Auto Scaling groups and use DynamoDB global tables for session data. Enable an Amazon CloudFront weighted distribution across regions. Point the Amazon Route 53 DNS record at the CloudFront distribution.