AWS Certified Solutions Architect Study Guide. David Higby Clinton

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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 expires, the monitored alarm drops below the threshold. At this point, the desired capacity value is 6. If the alarm triggers again, the simple scaling action will execute again and add three more instances. Keep in mind that Auto Scaling will never increase the desired capacity beyond the group's maximum setting.

      Step Scaling Policies

      If the demand on your application is rapidly increasing, a simple scaling policy may not add enough instances quickly enough. Using a step scaling policy, you can instead add instances based on how much the aggregate metric exceeds the threshold.

      To illustrate, suppose your group starts out with four instances. You want to add more instances to the group as the average CPU utilization of the group increases. When the utilization hits 50 percent, you want to add two more instances. When it goes above 60 percent, you want to add four more instances.

      You'd first create a CloudWatch Alarm to monitor the average CPU utilization and set the alarm threshold to 50 percent, since this is the utilization level at which you want to start increasing the desired capacity.

      You must then specify at least one step adjustment. Each step adjustment consists of the following:

       A lower bound

       An upper bound

       The adjustment type

       The amount by which to increase the desired capacity

      The upper and lower bounds define a range that the metric has to fall within for the step adjustment to execute. Suppose that for the first step you set a lower bound of 50 and an upper bound of 60, with a ChangeInCapacity adjustment of 2. When the alarm triggers, Auto Scaling will consider the metric value of the group's average CPU utilization. Suppose it's 55 percent. Because 55 is between 50 and 60, Auto Scaling will execute the action specified in this step, which is to add two instances to the desired capacity.

      Suppose now that you create another step with a lower bound of 60 and an upper bound of infinity. You also set a ChangeInCapacity adjustment of 4. If the average CPU utilization increases to 62 percent, Auto Scaling will note that 60 <= 62 < infinity and will execute the action for this step, adding four instances to the desired capacity.

      You might be wondering what would happen if the utilization were 60 percent. Step ranges can't overlap. A metric of 60 percent would fall within the lower bound of the second step.

      With a step scaling policy, you can optionally specify a warm‐up time, which is how long Auto Scaling will wait until considering the metrics of newly added instances. The default warm‐up time is 300 seconds. Note that there are no cooldown periods in step scaling policies.

      Target Tracking Policies

      If step scaling policies are too involved for your taste, you can instead use target tracking policies. All you do is select a metric and target value, and Auto Scaling will create a CloudWatch Alarm and a scaling policy to adjust the number of instances to keep the metric near that target.

      In addition to scaling out, target tracking will scale in by deleting instances to maintain the target metric value. If you don't want this behavior, you can disable scaling in. Also, just as with a step scaling policy, you can optionally specify a warm‐up time.

      Scheduled Actions

      Scheduled actions are useful if you have a predictable load pattern and want to adjust your capacity proactively, ensuring you have enough instances before demand hits.

      When you create a scheduled action, you must specify the following:

       A minimum, maximum, or desired capacity value

       A start date and time

      You may optionally set the policy to recur at regular intervals, which is useful if you have a repeating load pattern. You can also set an end time, after which the scheduled policy gets deleted.

Snapshot depicts the scheduled action setting the desired capacity to 4 every Friday.

      This action will run every Friday, setting the desired capacity to 4, prior

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