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Auto Scaling

Last Updated: Mar 12, 2018

To ensure the service quality and availability of a distributed cluster, an important O&M capability is to detect the status of each server in the cluster and to scale in or out in real time based on the system load.

EDAS provides the auto scaling function to automatically scale in or out a cluster based on the CPU, RT, and Load of the servers in the cluster.

Metric description:

  • CPU: The CPU utilization of the server in percentage. If multiple servers exist in the application, the average value of all servers is used.
  • RT: The time for the system to respond to a request, in ms.
  • Load: The system load, which is a positive integer.

All these metrics are entered in positive integers without floating point numbers. If multiple servers exist in the application, the average values of all servers are used for all the preceding metrics.

Auto scaling includes automatic scale-in and scale-out, for which the rules can be configured separately.

Automatic scale-out

  1. Log on to the EDAS console.

  2. Select Applications in the left-side navigation pane, and click the name of the application.

  3. Select Auto Scaling > Scaling Rules from the left-side menu bar of the application details page.

  4. Select Scale Out Rule to enable scale-out rule configuration.

  5. Configure the scale-out rules.

    • Trigger Indicators: Set CPU, RT, and Load.

    • Trigger Conditions:

      • Any One of the Indicators: Automatic scale-out is implemented if any of the set indicators is triggered.
      • All Indicators: Automatic scale-out is implemented only when all of the set indicators are triggered.
    • Duration: The period in which the indicator is continuously triggered by minute. If the average value in a minute continuously reaches the set threshold in this period, automatic scale-out is implemented. You can configure this parameter based on the sensitivity of the cluster service capabilities.

    • Number of Instances for Each Scale-Out: The number of servers automatically added after each scale-out operation is triggered. You can configure this parameter based on the service capabilities of a single server of the application.

    • Maximum Number of Instances: When the number of servers in the cluster reaches this threshold, scale-out is not implemented. You can configure this parameter based on your resource quota.

Automatic scale-in

The method for configuring rules of Automatic scale in is the same as that for configuring rules of Automatic scale out. For details about the indicator meanings and setting methods, see Automatic scale out.

Note: When the scale-in and scale-out rules are configured simultaneously, the indicator values of the scale-in rules cannot be larger than those of the scale-out rules. Otherwise, an error message is displayed when you click Save.

View auto scaling results

After the auto scaling rules are set, if automatic scale-out or scale-in is implemented, use any of the following methods to view the auto scaling results:

  • On the application details page, select Instance Information tab to check whether the number of instances is increased or reduced.

  • On the applciation details page, select Auto Scaling > Scaling history from the left-side navigation pane to view the scale-out and scale-in history records.

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