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When the usage pattern of a cluster is not fixed, load-based scaling is recommended. This type of scaling automatically adjusts the number of allows you to automatically scale up or scale down the query engines based on the resource utilization of the Query Engine instancesnode. By configuring cluster scaling in this way, you can optimize the utilization of your cloud cluster and reduce compute costs.
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From Kyvos 2024.2 onwards, load based scaling is implemented based on the CPU and Memory usage of the Query Engine instances. System resources will be are monitored for all BI Servers and Query Engines every 30 seconds, and Query Engines’ scaling will be performed based on this data.
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On the Cluster Scaling page, the Load option is selected by default.
To set the scaling mode, select one of the following:
Managed: Select the required capacity from the list to start Query Engine when any query is fired.
Custom: Select this option to set the rules for resource utilizationaccording to the usage pattern.
To set scale up rules,
Select the required capacity from the list to start Query Engine when any query is fired.
Enter a percentage to scale up the cluster if CPU and Memory utilization threshold goes above the specified percentage. Also, specify the number of data points and the total number of data points to set.
To set scale down rules,
Specify the BI Server and/or Query Engine from the list to shut down when no queries are fired for the specified period of time.
Enter a percentage to scale down the cluster if CPU and memory utilization threshold remains below the specified percentage. Also, specify the number of data points and the total number of data points to set.
Click Save. The load-based scaling mode is set.
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| Aura tab collection |
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| params | 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 |
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| Aura tab |
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| summary | AWS |
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| params | JTdCJTIydGl0bGUlMjIlM0ElMjJBV1MlMjIlN0Q= |
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The process with the number of Query Engine =10 | The time required for Load-based scaling |
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scale up | 16 mins. | scale down | 12 mins. | startup | 4 mins. |
| Aura tab |
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| summary | Azure |
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| params | JTdCJTIydGl0bGUlMjIlM0ElMjJBenVyZSUyMiU3RA== |
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The process with the number of Query Engine =7 | The previous time required for Load-based scaling | New time Time required for Load-based scaling |
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Scale up | 15-19 minutes | 11-13 minutes | Scale down | 15-19 minutes | 11-13 minutes | Startup8-10 minutes | 8-10 minutes |
| Aura tab |
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| summary | GCP |
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| params | JTdCJTIydGl0bGUlMjIlM0ElMjJHQ1AlMjIlN0Q= |
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The process with the number of Query Engine =10 | The time required for Load-based scaling |
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scale up | 4-5 mins. | scale down | 5-6 mins. | startup | 3-4 mins. |
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