Amazon Web Services Updated DOP-C02 Exam Questions and Answers by inara

Implement two-way S3 bucket replication between the primary Region ' s S3 buckets and the secondary Region ' s S3 buckets. Convert the DynamoDB tables into global tables. Set the secondary Region as the additional Region.

Implement S3 Batch Operations copy jobs between the primary Region and the secondary Region for all S3 buckets. Convert the DynamoDB tables into global tables. Set the secondary Region as the additional Region.

Implement two-way S3 bucket replication between the primary Region ' s S3 buckets and the secondary Region ' s S3 buckets. Enable DynamoDB streams on the DynamoDB tables in both Regions. In each Region, create an AWS Lambda function that subscribes to the DynamoDB streams. Configure the Lambda function to copy new records to the DynamoDB tables in the other Region.

Implement S3 Batch Operations copy jobs between the primary Region and the secondary Region for all S3 buckets. Enable DynamoDB streams on the DynamoDB tables in both Regions. In each Region, create an AWS Lambda function that subscribes to the DynamoDB streams. Configure the Lambda function to copy new records to the DynamoDB tables in the other Region.

Create an S3 bucket for each application. Configure S3 Same-Region Replication (SRR) from the raw data ' s S3 bucket to each application ' s S3 bucket. Configure each application to consume data from its own S3 bucket.

Create an Amazon Kinesis data stream. Create an AWS Lambda function that is invoked by object creation events in the raw data ' s S3 bucket. Program the Lambda function to redact data for each application. Publish the data on the Kinesis data stream. Configure each application to consume data from the Kinesis data stream.

For each application, create an S3 access point that uses the raw data ' s S3 bucket as the destination. Create an AWS Lambda function that is invoked by object creation events in the raw data ' s S3 bucket. Program the Lambda function to redact data for each application. Store the data in each application ' s S3 access point. Configure each application to consume data from its own S3 access point.

Create an S3 access point that uses the raw data ' s S3 bucket as the destination. For each application, create an S3 Object Lambda access point that uses the S3 access point. Configure the AWS Lambda function for each S3 Object Lambda access point to redact data when objects are retrieved. Configure each application to consume data from its own S3 Object Lambda access point.

Create an S3 bucket in each AWS account for the artifacts Allow the pipeline to write to the S3 buckets. Create a CodePipeline S3 action to copy the artifacts to the S3 bucket in each AWS account Update the CloudFormation actions to reference the artifacts S3 bucket in the production account.

Create a customer managed KMS key Configure the KMS key policy to allow the IAM roles used by the CloudFormation action to perform decrypt operations Modify the pipeline to use the customer managed KMS key to encrypt artifacts.

Create an AWS managed KMS key Configure the KMS key policy to allow the development account and the production account to perform decrypt operations. Modify the pipeline to use the KMS key to encrypt artifacts.

In the development account and in the production account create an IAM role for CodePipeline. Configure the roles with permissions to perform CloudFormation operations and with permissions to retrieve and decrypt objects from the artifacts S3 bucket. In the CodePipeline account configure the CodePipeline CloudFormation action to use the roles.

In the development account and in the production account create an IAM role for CodePipeline Configure the roles with permissions to perform CloudFormationoperations and with permissions to retrieve and decrypt objects from the artifacts S3 bucket. In the CodePipelme account modify the artifacts S3 bucket policy to allow the roles access Configure the CodePipeline CloudFormation action to use the roles.

Create an Amazon Aurora cluster in one Availability Zone across multiple Regions as the data store Use Aurora ' s automatic recovery capabilities in the event of a disaster

Create an Amazon Aurora global database in two Regions as the data store. In the event of a failure promote the secondary Region as the primary for the application.

Create an Amazon Aurora multi-master cluster across multiple Regions as the data store. Use a Network Load Balancer to balance the database traffic in different Regions.

Set up the application in two Regions and use Amazon Route 53 failover-based routing that points to the Application Load Balancers in both Regions. Use hearth checks to determine the availability in a given Region. Use Auto Scaling groups in each Region to adjust capacity based on demand.

Set up the application m two Regions and use a multi-Region Auto Scaling group behind Application Load Balancers to manage the capacity based on demand. In the event of a disaster adjust the Auto Scaling group ' s desired instance count to increase baseline capacity in the failover Region.