Applies to: 
Kyvos Enterprise Kyvos Cloud (SaaS on AWS) Kyvos AWS Marketplace
Kyvos Azure Marketplace Kyvos GCP Marketplace 
Kyvos Single Node Installation (Kyvos SNI)
When the usage pattern of a cluster is not fixed, load-based scaling is recommended. This type of scaling allows you to automatically scale up or scale down the Query Engine instances based on the resource utilization of the Query Engine instances. By configuring cluster scaling in this way, you can optimize the utilization of your cloud cluster and reduce compute costs.
Setting Load-based cluster scaling rules
From Kyvos 2024.2 onwards, load based scaling is implemented based on the CPU and Memory usage of the Query Engine instances. System resources are monitored for all BI Servers and Query Engines every 30 seconds, and Query Engines’ scaling will be performed based on this data.
Note
If you select the Query Engine as a compute server, ensure the following:
Start the Query Engine when the semantic model process is started.
Skip the scaling and shutdown of the Query Engine when the semantic model is processing.
The cluster will be scaled up step-by-step. For instance, it will scale from Low to Moderate and then from Moderate to High. Similarly, when scaling down the cluster, it will scale from High to Moderate and then from Moderate to Low.
Load-based cluster scaling is enabled by default. You can further configure it on the Cluster Scaling page using the Load option.
To set a load-based scaling, from the Toolbox, click Setup > Cluster Scaling. The Cluster Scaling page is displayed.
Kyvos provides the following scaling modes for Load-based scaling:
Managed: In Managed scaling, Kyvos intelligently manages the cluster capacity to scale up and scale down Query Engine instances.
Custom: Custom scaling allows you to set rules based on your cluster usage patterns. This feature presently supports scaling based on CPU and Memory utilization. When the CPU or Memory load condition meets the configured parameters, the Query Engine instances can be scaled up or down accordingly.
To set the scaling modes for Load-Based scaling, perform the following steps.
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 configure the custom rules as per your cluster 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 or 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.
NOTE
A data point is information on resource utilization captured every 30 seconds.
Transitioning period
The following tables specify the approximate time required to complete the process during the transitioning period.
Important
If the cluster is down and a query is executed, the first query triggers the cluster startup process, and all queries fail until the cluster is up and running. In this case, the following messages are displayed:
Message 1: "Could not serve the query as Query Engine Cluster is not available. Query Engine is launched. Please try after some time."
Message 2: "Could not serve the query as Query Engine Cluster is starting. Please try after some time."
By default, the queries fail until Query Engines are started. If you want to hold the queries when query engines are down, you can specify the time (in minutes) for holding queries by using the QE_STARTUP_QUERY_HOLD_TIME property.
Ensure that if the query engines become active before the configured time, the query will be served; otherwise, it will fail.The capacity of the BI Servers cannot be changed.
All BI Servers can be shut down except the Coordination Master. If there is only one BI Server, this BI Server is treated as the Coordination Master.
The Settings option and Add Schedule option are disabled on the Load screen.
You can view on-screen notifications that provide you with timely information about the state of the cluster.
When you scale down the Query Engines, you reduce the capacity of the node, including the number of cores and memory. Conversely, when you scale up the Query Engines, you increase the capacity of the node by adding more cores and memory.
The Query Engines do not start for any ROLAP queries.
During the transitioning period of Query Engines; such as scale-up, scale-down, or shut down; you can design and refine the semantic model because the Coordination Master is always up and running .