Free SAP-C03 – AWS Certified Solutions Architect - Professional Practice Test Question

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  Modify the Auto Scaling group by setting the Update policy to target the oldest launch configuration for replacement.

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  Create a new Auto Scaling group before the next patch maintenance During the maintenance window patch both groups and reboot the instances.

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  Create an Elastic Load Balancer in front of the Auto Scaling group Configure monitoring to ensure that target group health checks return healthy after the Auto Scaling group replaces the terminated instances

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  Create automation scripts to patch an AMI. update the launch configuration, and invoke an Auto Scaling instance refresh.

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  Create an Elastic Load Balancer in front of the Auto Scaling group Configure termination protection on the instances.

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  Lift and shift the Oracle data warehouse to Amazon EC2 using AWS DMS.

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  Migrate the Oracle data warehouse to Amazon Redshift using AWS SCT and AWS QMS.

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  Lift and shift the PostgreSQL databases to Amazon EC2 using AWS DMS.

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  Migrate the PostgreSQL databases to Amazon RDS for PostgreSQL using AWS DMS

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  Migrate the Oracle data warehouse to an Amazon EMR managed cluster using AWS DMS.
  

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  Create multiple read replicas and put them into an Auto Scaling group.

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  Create multiple read replicas in different Availability Zones.

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  Create an Amazon Route 53 hosted zone and a record set for each read replica with a TTL and a weighted routing policy.

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  Create an Application Load Balancer (ALB) and put the read replicas behind the ALB.

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  Configure an Amazon CloudWatch alarm to detect a failed read replica. Set the alarm to directly invoke an AWS Lambda function to delete its Route 53 record set.

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  Configure an Amazon Route 53 health check for each read replica using its endpoint

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  Move the objects in the user content S3 bucket to S3 Intelligent-Tiering immediately

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  Move the objects in the user content S3 bucket to S3 Intelligent-Tiering after 30 days

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  Move the objects in the replication S3 bucket to S3 Standard-Infrequent Access (S3 Standard-IA) after 30 days and to S3 Glacier after 90 days

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  Move the objects in the replication S3 bucket to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 30 days and to S3 Glacier Deep Archive after 90 days

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  Move the objects in the replication S3 bucket to S3 Standard-infrequent Access (S3 Standard-IA) after 30 days and to S3 Glacier Deep Archive after 180 days

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  Resize the MySQL General Purpose SSD storage to 6 TB to improve the volume's IOPS

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  Re-architect the database tier to use Amazon Aurora instead of an RDS MySQL DB instance and add read replicas

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  Leverage Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data

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  Use AWS X-Ray to analyze and debug application issues and add more API servers to match the load

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  Re-architect the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance

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  Place the Tomcat server in an Auto Scaling group with multiple EC2 instances behind an Application Load Balancer

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  Provision an additional VPC peering connection

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  Migrate the MySQL database to Amazon Aurora with one Aurora Replica

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  Provision two NAT gateways in the database VPC

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  Move the Tomcat server to the database VPC

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  Create an additional public subnet in a different Availability Zone in the website VPC

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  Create an S3 access point for each application in the AWS account that owns the S3 bucket. Configure each access point to be accessible only from the application's VPC. Update the bucket policy to require access from an access point.

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  Create an interface endpoint for Amazon S3 in each application's VPC. Configure the endpoint policy to allow access to an S3 access point. Create a VPC gateway attachment for the S3 endpoint.

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  Create a gateway endpoint lor Amazon S3 in each application's VPConfigure the endpoint policy to allow access to an S3 access point. Specify the route table that is used to access the access point.

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  Create an S3 access point for each application in each AWS account and attach the access points to the S3 bucket. Configure each access point to be accessible only from the application's VPC. Update the bucket policy to require access from an access point.

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  Create a gateway endpoint for Amazon S3 in the data lake's VPC. Attach an endpoint policy to allow access to the S3 bucket. Specify the route table that is used to access the bucket.

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  Establish a networking account in the AWS Cloud Create a private VPC in the networking account Set up an AWS Direct Connect connection with a private VIF between the on-premises environment and the private VPC

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  Establish a networking account in the AWS Cloud Create a private VPC in the networking account Set up an AWS Direct Connect connection with a public VIF between the on-premises environment and the private VPC

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  Create an Amazon S3 interface endpoint in the networking account

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  Create an Amazon S3 gateway endpoint in the networking account

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  Establish a networking account in the AWS Cloud. Create a private VPC in the networking account Peer VPCs from the accounts that host the S3 buckets with the VPC in the network account

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  Ensure that the container has the environment variable with name "DB_PASSWORD" specified with a "ValueFrom" and the ARN of the secret

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  Ensure that the container has the environment variable with name *D8_PASSWORD" specified with a "ValueFrom" and the secret name of the secret.

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  Ensure that the Fargate service security group allows inbound network traffic from the Aurora MySQL database on the MySQL TCP port 3306.

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  Ensure that the Aurora MySQL database security group allows inbound network traffic from the Fargate service on the MySQL TCP port 3306.

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  Ensure that the container has the environment variable with name "D8_HOST" specified with the hostname of a DB instance endpoint.

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  Ensure that the container has the environment variable with name "DB_HOST" specified with the hostname of the OB duster endpoint.

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  Create a REST API in Amazon API Gateway and use AWS Lambda functions as the application layer.

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  Create an Application Load Balancer and migrate the Docker container to AWS Fargate.

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  Migrate the storage layer to Amazon DynamoD8.

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  Migrate the storage layer to Amazon DocumentD8 (with MongoDB compatibility).

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  Create an Application Load Balancer and move the storage layer to an EC2 Auto Scaling group.
  

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  Ensure that all organizations in the partnership have AWS accounts. In the account with the S3 bucket, create a cross-account role for each account in the partnership that allows read access to the data. Have the organizations assume and use that read role when accessing the data.

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  Ensure that all organizations in the partnership have AWS accounts. Create a bucket policy on the bucket that owns the data The policy should allow the accounts in the partnership read access to the bucket. Enable Requester Pays on the bucket. Have the organizations use their AWS credentials when accessing the data.

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  Ensure that all organizations in the partnership have AWS accounts. Configure buckets in each of the accounts with a bucket policy that allows the institute that owns the data the ability to write to the bucket Periodically sync the data from the institute's account to the other organizations. Have the organizations use their AWS credentials when accessing the data using their accounts

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  Ensure that all organizations in the partnership have AWS accounts. In the account with the S3 bucket, create a cross-account role for each account in the partnership that allows read access to the data. Enable Requester Pays on the bucket. Have the organizations assume and use that read role when accessing the data.
  

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  Set up an Amazon CloudFront distribution Set the ALB as the origin Move all customer traffic to the CloudFront distribution endpoint

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  Use Amazon RDS Proxy Reconfigure the database connections to use the proxy

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  Increase the number of reader nodes in the Aurora MySQL cluster

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  Increase the number of nodes in the ElastiCache for Redis cluster

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  Change the CloudFront origin to an Amazon API Gateway proxy endpoint. Rewrite the S3 request URL by using an AWS Lambda function.

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  Change the CloudFront origin to an Amazon API Gateway endpoint. Rewrite the S3 request URL in an AWS service integration.

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  Change the CloudFront configuration to use an AWS Lambda@Edge function that is invoked by a viewer request event to rewrite the S3 request URL.

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  Change the CloudFront configuration to use an AWS Lambda@Edge function that is invoked by an origin request event to rewrite the S3 request URL.
  

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  Enable VPC Flow Logs. Store the flow logs in an Amazon S3 bucket for analysis.

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  Enable Traffic Mirroring on the network interface of the EC2 instances. Send the mirrored traffic lo a target for storage and analysis.

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  Create an AWS WAF web ACL. and associate it with the ALB. Configure AWS WAF logging.

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  Enable logging for the ALB. Store the logs in an Amazon S3 bucket for analysis.
  

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  Configure a DHCP options set with the on-premises NTP server address Assign the options set to the VPC. Ensure that NTP traffic is allowed between AWS and the on-premises networks.

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  Create a custom AMI to use the Amazon Time Sync Service at 169.254.169.123 Use this AMI for the application Use AWS Config to audit the NTP configuration.

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  Deploy a third-party time server from the AWS Marketplace. Configure the time server to synchronize with the on-premises atomic clock network appliance. Ensure that NTP traffic is allowed inbound in the network ACLs for the VPC that contains the third-party server.
  D Create an IPsec VPN tunnel from the on-premises atomic clock network appliance to the VPC to encrypt the traffic over the Direct Connect connection. Configure the VPC route tables to direct NTP traffic over the tunnel.
  

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  Receive the orders in an Amazon EC2-hosted database and use EC2 instances to process them.

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  Receive the orders in an Amazon SOS queue and trigger an AWS Lambda function lo process them.

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  Receive the orders using the AWS Step Functions program and trigger an Amazon ECS container lo process them.

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  Receive the orders in Amazon Kinesis Data Streams and use Amazon EC2 instances to process them.
  

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  Pre-warming Elastic Load Balancers, using a bigger instance type, changing all Amazon EBS volumes to GP2 volumes.

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  Performing a one-time migration of the database cluster to Amazon RDS. and creating several additional read replicas to handle the load during end of month

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  Using Amazon CioudWatch with AWS Lambda to change the type. size, or IOPS of Amazon EBS volumes in the cluster based on a specific CloudWatch metric

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  Replacing all existing Amazon EBS volumes with new PIOPS volumes that have the maximum available storage size and I/O per second by taking snapshots before the end of the month and reverting back afterwards.
  

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  Kms:GenerateDataKey

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  KmsGetKeyPolpcy

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  kmsGetPubKKey

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  kms:SKjn

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  Copy the DynamoDB tables into Apache Hive tables on Amazon EMR every hour and analyze them (or anomalous behaviors. Send Amazon SNS notifications when anomalous behaviors are detected.

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  Use AWS CloudTrail to capture all the APIs that change the DynamoDB tables. Send SNS notifications when anomalous behaviors are detected using CloudTrail event filtering.

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  Use Amazon DynamoDB Streams to capture and send updates to AWS Lambda. Create a Lambda function to output records lo Amazon Kinesis Data Streams. Analyze any anomalies with Amazon Kinesis Data Analytics. Send SNS notifications when anomalous behaviors are detected.

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  Use event patterns in Amazon CloudWatch Events to capture DynamoDB API call events with an AWS Lambda (unction as a target to analyze behavior. Send SNS notifications when anomalous behaviors are detected.
  

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  Use AWS Application Auto Scaling to increase capacity during the peak period. Purchase reserved RCUs and WCUs to match the average load.

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  Configure on-demand capacity mode for the table.

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  Configure DynamoDB Accelerator (DAX) in front of the table. Reduce the provisioned read capacity to match the new peak load on the table.

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  Configure DynamoDB Accelerator (DAX) in front of the table. Configure on-demand capacity mode for the table.