You have an application consisting of a stateless web server tier running on Amazon EC2 instances behind load balancer, and are using Amazon RDS with read replicas. Which of the following methods should you use to implement a self-healing and cost-effective architecture? Choose 2 answers from the optionsgiven below
The scaling of CC2 Instances in the Autoscaling group is normally done with the metric of the CPU
utilization of the current instances in the Autoscaling group
For more information on scaling in your Autoscaling Group, please refer to the below link:
* http://docs.aws.a mazon.com/autoscaling/latest/userguide/as-scaling-si mple-step.html
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Cach AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure, Amazon RDS performs an automatic failover to the standby for to a read replica in the case of Amazon Aurora), so that you can resume database operations as soon as the failover is complete. For more information on RDS Multi-AZ please refer to the below link:
https://aws.amazon.com/rds/details/multi-az/
Option A is invalid because if you already have in-built metrics from Cloudwatch, why would you want to spend more in using a a third-party monitoring solution.
Option B is invalid because health checks are already a feature of AWS CLB
Option C is invalid because the database CPU usage should not be used to scale the web tier.
Option C is invalid because increasing the instance size does not always guarantee that the solution will not become unhealthy.
Option F is invalid because increasing Read-Replica's will not suffice for write operations if the primary DB fails.
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