AWS Certified Solutions Architect Study Guide. David Higby Clinton

optionally set the desired number of instances you want Auto Scaling to provision and maintain.

       Minimum Auto Scaling will ensure the number of healthy instances never goes below the minimum. If you set this to 0, Auto Scaling will not spawn any instances and will terminate any running instances in the group.

       Maximum Auto Scaling will make sure the number of healthy instances never exceeds this amount. This might seem strange but remember that you might have budget limitations and need to be protected from unexpected (and unaffordable) usage demands.

       Desired Capacity The desired capacity is an optional setting that must lie within the minimum and maximum values. If you don't specify a desired capacity, Auto Scaling will launch the number of instances as the minimum value. If you specify a desired capacity, Auto Scaling will add or terminate instances to stay at the desired capacity. For example, if you set the minimum to 1, the maximum to 10, and the desired capacity to 4, then Auto Scaling will create four instances. If one of those instances gets terminated—for example, because of human action or a host crash—Auto Scaling will replace it to maintain the desired capacity setting of 4. In the web console, desired capacity is also called the group size.

      Specifying an Application Load Balancer Target Group

      If you want to use an application load balancer (ALB) to distribute traffic to instances in your Auto Scaling group, just plug in the name of the ALB target group when creating the Auto Scaling group. Whenever Auto Scaling creates a new instance, it will automatically add it to the ALB target group.

      Health Checks Against Application Instances

      When you create an Auto Scaling group, Auto Scaling will strive to maintain the minimum number of instances, or the desired number if you've specified it. If an instance becomes unhealthy, Auto Scaling will terminate and replace it.

      By default, Auto Scaling determines an instance's health based on EC2 health checks. Chapter 7, “CloudTrail, CloudWatch, and AWS Config,” covers how EC2 automatically performs system and instance status checks. These checks monitor for instance problems such as memory exhaustion, filesystem corruption, or an incorrect network or startup configuration, as well as for system problems that require AWS involvement to repair. Although these checks can catch a variety of instance and host‐related problems, they won't necessarily catch application‐specific problems.

      If you're using an application load balancer to route traffic to your instances, you can configure health checks for the load balancer's target group. Target group health checks can check for HTTP response codes from 200 to 499. You can then configure your Auto Scaling group to use the results of these health checks to determine whether an instance is healthy.

If an instance fails the ALB health check, it will route traffic away from the failed instance, ensuring that users don't reach it. At the same time, Auto Scaling will remove the instance, create a replacement, and add the new instance to the load balancer's target group. The load balancer will then route traffic to the new instance.

      

A good design practice is to have a few recovery actions that work for a variety of circumstances. An instance may crash due to an out‐of‐memory condition, a bug, a deleted file, or an isolated network failure, but simply terminating and replacing the instance using Auto Scaling resolves all these cases. There's no need to come up with a separate recovery action for each cause when simply re‐creating the instance solves them all.

      Auto Scaling Options

      Once you create an Auto Scaling group, you can leave it be and it will continue to maintain the minimum or desired number of instances indefinitely. However, maintaining the current number of instances is just one option. Auto Scaling provides several other options to scale out the number of instances to meet demand.

      Manual Scaling

      If you change the minimum, desired, or maximum values at any time after creating the group, Auto Scaling will immediately adjust. For example, if you have the desired capacity value set to 2 and change it to 4, Auto Scaling will launch two more instances. If you have four instances and set the desired capacity value to 2, Auto Scaling will terminate two instances. Think of the desired capacity as a thermostat.

      Dynamic Scaling Policies

      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.

      Simple Scaling Policies

      With a simple scaling policy, whenever the metric rises above the threshold, Auto Scaling simply increases the desired capacity. How much it increases the desired capacity, however, depends on which of the following adjustment types you choose:

       ChangeInCapacity Increases the capacity by a specified amount. For instance, you could start with a desired capacity value of 4 and then have Auto Scaling increase the value by 2 when the load increases.

       ExactCapacity Sets the capacity to a specific value, regardless of the current value. For example, suppose the desired capacity value is 4. You create a policy to change the value to 6 when the load increases.

       PercentChangeInCapacity Increases the capacity by a percentage of the current amount. If the current desired capacity value is 4 and you specify the percent change in capacity as 50 percent, then Auto Scaling will bump the desired capacity value to 6.

      For example, suppose you have four instances and create a simple scaling policy that specifies a PercentChangeInCapacity adjustment of 50 percent. When the monitored alarm triggers, Auto Scaling will increment the desired capacity by 2, which will in turn add two instances to the Auto Scaling group, for a total of six.

      After Auto Scaling completes the adjustment, it waits a cooldown period before executing the policy again, even if the alarm is still breaching. The default cooldown period is 300 seconds, but you can set it as high as you want or as low as 0—effectively disabling it. Note that if an instance is unhealthy, Auto Scaling will not wait for the cooldown period before replacing the unhealthy instance.

      Referring to the preceding example, suppose that after the scaling adjustment completes and the cooldown period