Finance Company Website Project

CorrectAnswer - D.

AWS OpsWorks Stacks provides three ways to manage the number of server instances.

24/7 instances are started manually and run until they are manually stopped.

Time-based instances are automatically started and stopped by AWS OpsWorks Stacks on a user-specified schedule.

Load-based instances are automatically started and stopped by AWS OpsWorks Stacks when they cross a threshold for a user-specified load metric such as CPU or memory utilization.

If you are managing stacks with more than a few application server instances, it is recommended to use a mix of all three instance types.

https://docs.aws.amazon.com/opsworks/latest/userguide/best-practices-autoscale.html

has discussed this scenario in details.

OptionA is incorrect: Because schedule instances and spot instances should not be used for OpsWorks stack.

Option B is incorrect: Because On demand/schedule/spot are EC2 instance types instead of OpsWorks instance types.

Option C is incorrect: Because it is improper to use EC2 autoscalling to maintain instance volume in OpsWorks.

You can still configure that according to https://aws.amazon.com/blogs/devops/auto-scaling-aws-opsworks-instances/, however this is not a straightforward approach.

The best practice suggested by AWS is using 24/7 instances/Time-based instances/Load-based instances to optimize the Number of Application Servers.

The correct answer is C.

Explanation: OpsWorks is a configuration management service that enables the management of applications and server infrastructure on AWS. To handle the average request volume that varies throughout the day for a website project, the stack should have five 24/7 instances to handle the base load. Additionally, an EC2 autoscaling group should be added to the OpsWorks Stack with a proper launch configuration. The autoscaling group is capable of handling load changes automatically.

The autoscaling group can be configured to add or remove instances based on metrics like CPU utilization or network traffic. This means that when the load increases, the autoscaling group will add instances to handle the additional traffic, and when the load decreases, the group will remove instances to save costs.

Option A suggests adding ten schedule instances and modifying the number of schedule instances every two hours, and adding two spot instances to handle traffic spikes. However, scheduling instances may not be efficient and can lead to over-provisioning, while spot instances can be interrupted if the spot price goes above the maximum bid.

Option B suggests using five On Demand instances to serve the base load, adding ten schedule instances, modifying the number of schedule instances every two hours, and adding two spot instances to handle traffic spikes. However, On Demand instances are not as scalable and cost-effective as using an autoscaling group.

Option D suggests having five 24/7 instances to handle the base load, adding ten time-based instances, modifying the number of time-based instances every hour, and adding two load-based instances to handle traffic spikes. However, time-based instances and load-based instances are not as efficient and cost-effective as using an autoscaling group.

Therefore, option C is the best solution, as it offers cost-effectiveness and efficiency, with the ability to handle load changes automatically using an EC2 autoscaling group.