Balance cloud costs, performance with AWS Auto Scaling

Grazed from TechTarget. Author: Dan Sullivan.

The pay-as-you-go model of cloud computing favors developers and architects who can design applications that run with the optimal amount of resources at all times. Overprovisioning a server means paying more than necessary to meet your needs. Erring in the other direction can be even worse: Underprovisioning resources causes an application to suffer in performance. Variations in application demand make the challenge of server sizing even more difficult, as the optimal set of resources does not stay constant.

One way to address these variations when using the Amazon Web Services (AWS) cloud is to create a load-balanced cluster of servers, then add or remove servers according to demand. You can manage the load-balanced cluster yourself, but another option is the AWS Auto Scaling service. The service maintains adequate performance levels without overprovisioning, while also alleviating some administrative overhead. Good candidates for the service are use cases that allow for readily distributed workloads across multiple servers, with significant variation in workloads…

AWS Auto Scaling uses CloudWatch, Amazon’s monitoring utility, to provide the performance data needed to make scaling recommendations. CloudWatch collects performance statistics — including CPU utilization, disk usage and data transfer — from servers and other AWS resources at five-minute intervals for no charge. (For an additional fee, you can have performance metrics collected once per minute.) System administrators then can specify configuration policies to add or remove servers based on these metrics. For example, a policy could indicate that if the average CPU utilization exceeds 70%, an additional virtual instance should be brought online…

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