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Applies to: Kyvos Enterprise    Kyvos Cloud (Managed Services on AWS)     Kyvos Azure Marketplace

Kyvos AWS Marketplace    Kyvos Single Node Installation (Kyvos SNI)     Kyvos Free ( Limited offering for AWS)

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When the cluster usage duration is not fixed, you must use load-based scaling. This type of scaling allows you to set rules to automatically scale up or scale down the query engines based on usage patterns. By managing cluster scaling, you can enhance the utilization of your cloud cluster and save on compute costs. Additionally, you can set rules to automatically shut down or start the BI Servers and Query Engines to optimize resource utilization further.

To implement a scale-down rule, you can configure a setting to automatically reduce the capacity of your Query Engines when no queries are being executed. Additionally, you can set a rule to automatically shut down the Query Engines and BI Servers if no query traffic is received for a specified period of time.

Similarly, for a scale-up rule, you can set a rule to automatically start the BI Servers and Query Engines with the required capacity when a specified number of queries are executed over a defined time period.

Info

Note

  • The capacity of the BI Servers cannot be changed.

  • All BI Servers can be shut down except the Coordination Master. It is required to provide a response to a query. 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 set the default settings for the query engine cluster or create a new schedule using the Schedule option displayed on the Cluster Scheduling page. See the Creating schedule-based scaling section for more details. 

  • 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.

Cluster Scaling page to set load-based scaling 

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On this page, you can specify rules to scale down or scale up the query engines, as well as set rules to shut down or start the BI Servers and query engines.

Points to know

  • From Kyvos 2023.2 onwards, you can specify the time (in minutes)  to hold the queries when query engines are started by using the  QE_STARTUP_QUERY_HOLD_TIME  property. Note that if the query engines become active before the configured time, the query will be served; otherwise, it will fail.

  • Upon completion of the Change Cluster State schedule, the load-based rules will be implemented automatically if they have been saved. If no rules have been saved on the Load screen, the cluster will run using the Change Cluster State capacity.

  • The scale-down rule implements when the cluster runs at full capacity. The Query Engines can scale down either from full to moderate capacity or from full to low capacity.
    If the query engine scales down to moderate capacity, you cannot further scale down the Query Engine to low capacity.

  • The Kyvos cluster and the Query Engines automatically scale up at full capacity due to any MOLAP query.  

  • The Query Engines do not start for any ROLAP queries.  

  • The scale-down duration cannot be less than 30 minutes.

  • The duration to shut down the query engine must be at least 30 minutes greater than the scale-down duration.

  • 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."

  • 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 .

  • The following tables specify the approximate  time required to complete the process during the transitioning period. 

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 To set the scaling rules for the query engines, perform the following steps. 

  1. From the Toolbox, click  Setup, and then click  Cluster Scaling. The Cluster Scaling page is displayed.

  2. On the page, select the Load option. The Load page is displayed. 

  3. To scale down the query engines, you must set the following rules:

    1. Select the capacity option as Moderate, High, or Low from the list, and then set the time. You can also set the Shutdown rule for the query engines if no query is fired for a defined period. 

    2. Select Query Engines or BI Servers and Query Engines from the list, and then set the time. 

  4. If you want to scale up the query engines, you must set the following rules:  

    1. To start the BI Servers and query engines, select the capacity option as Moderate, High, or Low from the list when any query is fired. 

    2. To scale up the query engines with the desired capacity, you need to specify the number of queries and the duration for which the query engines should be scaled up.

  5. Click Save. 

Changing cluster state 

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  1. Select whether the service should remain online or offline.

  2. Click to select a query engine capacity. 

  3. Click Change Now.
    The Schedule entry is displayed in the schedule. 

Subscribe to notifications

Click the Actions menu (...) located in the upper right corner of a cluster scaling page, and then click  Subscribe Cluster Events  to subscribe to receive notifications for cluster events. These events include the cluster shutting down as per schedule, the cluster state scaling down due to Cluster scheduling, all query engines being up and in a running state, the cluster state scaling down, entity modifications, or a license expiring soon.

You can set up notifications and subscriptions as needed.

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