Your application has an Auto Scaling group of m3.large instances running an application that receives messages born an Amazon SQS queue. After a while, the number of instances reaches the maximum set for the group and the number of messages on the queue continues to increase. You have discovered that a third- party library used by the application has a bug that causes a memory leak.
What cost-effective steps can you take to continue message processing while the library developer fixes the bug?

A. Enable Elastic Load Balancing health checks for the Auto Scaling group. When Elastic Load Balancing has detected a failure, Auto Scaling will terminate the failing application's instance and launch a new one.
B. Use Amazon EC2 instance memory usage CloudWatch metrics to raise alerts when they reach a defined level and send a message to Auto Scaling to fail the instance health check.
C. Use application monitoring on the instance to restart the application when memory usage reaches a defined level.
D. Create a new Auto Scaling launch configuration to use the r3.large instance type. Update the Auto Scaling group with the new launch configuration.