Proactive storage decider

Proactive storage decider

The autoscaling proactive storage decider (proactive_storage) calculates the storage required to contain the current data set plus an estimated amount of expected additional data.

The proactive storage decider is enabled for all policies governing nodes with the data_hot role.

The estimation of expected additional data is based on past indexing that occurred within the forecast_window. Only indexing into data streams contributes to the estimate.

Configuration settings

forecast_window

(Optional, time value) The window of time to use for forecasting. Defaults to 30 minutes.

Examples

This example puts an autoscaling policy named my_autoscaling_policy, overriding the proactive decider’s forecast_window to be 10 minutes.

  1. resp = client.autoscaling.put_autoscaling_policy(
  2.     name="my_autoscaling_policy",
  3.     policy={
  4.         "roles": [
  5.             "data_hot"
  6.         ],
  7.         "deciders": {
  8.             "proactive_storage": {
  9.                 "forecast_window": "10m"
  10.             }
  11.         }
  12.     },
  13. )
  14. print(resp)
  1. const response = await client.autoscaling.putAutoscalingPolicy({
  2.   name: "my_autoscaling_policy",
  3.   policy: {
  4.     roles: ["data_hot"],
  5.     deciders: {
  6.       proactive_storage: {
  7.         forecast_window: "10m",
  8.       },
  9.     },
  10.   },
  11. });
  12. console.log(response);
  1. PUT /_autoscaling/policy/my_autoscaling_policy
  2. {
  3.   "roles" : [ "data_hot" ],
  4.   "deciders": {
  5.     "proactive_storage": {
  6.       "forecast_window": "10m"
  7.     }
  8.   }
  9. }

The API returns the following result:

  1. {
  2.   "acknowledged": true
  3. }