Читать книгу AWS Certified Solutions Architect Study Guide - Ben Piper, David Higby Clinton - Страница 87

Most AWS‐managed resources are elastic—that is, they automatically scale to accommodate increased load. Some examples include S3, load balancers, Internet gateways, and NAT gateways. Regardless of how much traffic you throw at them, AWS is responsible for ensuring that they remain available while continuing to perform well. But when it comes to your EC2 instances, you're responsible for ensuring that they're powerful and plentiful enough to meet demand.

Running out of instance resources—be it CPU utilization, memory, or disk space—will almost always result in the failure of whatever you're running on it. To ensure that your instances never become overburdened, dynamic scaling policies automatically provision more instances before they hit that point. Auto Scaling generates the following aggregate metrics for all instances within the group:

 Aggregate CPU utilization

 Average request count per target

 Average network bytes in

 Average network bytes out

You're not limited to using just these native metrics. You can also use metric filters to extract metrics from CloudWatch logs and use those. As an example, your application may generate logs that indicate how long it takes to complete a process. If the process takes too long, you could have Auto Scaling spin up new instances.

Dynamic scaling policies work by monitoring a CloudWatch alarm and scaling out—by increasing the desired capacity—when the alarm is breaching. You can choose from three dynamic scaling policies: simple, step, and target tracking.