Database Autonomy Service (DAS) provides a prediction-based auto scaling policy for Tair (Redis OSS-compatible). This policy uses the historical data of an instance from the past 10 days to predict its performance metric values for the next 24 hours. If a predicted metric value is greater than or equal to the specified target value, a scale-out is recommended.
This feature only provides scale-out recommendations. You must perform scale-out operations manually. For solutions that perform scale-out operations automatically, see the following:
Automatic scale-out: Automatically and incrementally scales out instances based on preset thresholds. You must manually scale in the instances. This is suitable for scenarios with traffic bursts and dynamic workloads.
Scheduled auto scaling: Scales out instances at scheduled times based on preset policies. Automatic scale-in is supported. This is suitable for scenarios with known periodic high workloads.
Procedure
Log on to the console and go to the Instances page. In the top navigation bar, select the region in which the instance that you want to manage resides. Then, find the instance and click the instance ID.
In the navigation pane on the left, click CloudDBA > Performance Trends.
On the Performance Trends page, click Autonomy Service Settings.
ImportantIf the instance is in proxy mode, switch to a Proxy Node and then click Autonomy Service Settings.
On the Auto Scaling tab of the Autonomous Function Settings panel, click Add Policy. On the Add Policy page, set the following parameters:
Parameter
Description
Policy Name
The name of the policy.
Mode
The mode of the policy. Select Prediction-based Auto Scaling.
NoteCurrently, this mode only provides scale-out recommendations and does not perform scale-out operations.
Engine Type
The database engine type. The default value is Redis.
Metric Type
The type of the prediction metric. Select Memory Usage (%).
Destination Value
The target value for the metric, in percent (%). When the predicted metric value is greater than or equal to the target value, a scale-out is recommended.
For example, if you set the target value to 70, a scale-out is recommended when the predicted memory usage is greater than or equal to 70%.
Click OK.
In the Recommended Policies section, find the target policy and click Apply in the Actions column to add the policy to the instance.
NoteTo modify a created policy, click Modify in the Actions column of the policy and change the settings on the Update Policy tab.
To cancel a policy for an instance, find the policy in the Applied Policies section and click Cancel in the Actions column.
View prediction-based auto scaling results
Log on to the DAS console.
In the navigation pane on the left, click Instance Monitoring.
Find the target instance and click the instance ID to go to the instance details page.
In the navigation pane on the left, click Autonomy Center.
On the Autonomy Center page, view the Auto Scaling events that occurred within the selected time range.
Click Details for a Database Workload Prediction event to view the details of the prediction-based auto scaling.
