Kyvos Deployment on Azure with Spark

Applies to: Kyvos Enterprise  Kyvos Cloud (SaaS on AWS) Kyvos AWS Marketplace

Kyvos Azure Marketplace   Kyvos GCP Marketplace Kyvos Single Node Installation (Kyvos SNI)

You can deploy Kyvos clusters on Azure using any of the following methods.

  1. Automated deployment: In this method, you can deploy Kyvos using the following methods:

    1. Deploying Kyvos through Template Specs: In this method, you can deploy Kyvos on Azure through Template Specs.

  2. Wizard-based deployment: In this method, the Kyvos Manager allows you to use a wizard that will help to deploy a cluster using any of the following options.

Regardless of which option you select, if you do not have permission to fetch resources from the cloud environment, you will need to manually enter the information related to resources (like the IP of instances and the name of the bucket). Resources are created by any of the means like Azure console, CLI, REST, or SDK.

Note

  • Before starting the installation and deployment, please ensure that you have all the prerequisites available.

  • Also, download the Azure Installation Files folder and keep all the requisite files handy during deployment.

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  • From Kyvos 2024.12 onwards, automated deployment of clusters is supported in environments where a system-assigned managed identity is pre-configured before deployment.

Important

  • Once you have completed the deployment, provide permissions for usage dashboard.

  • Ensure that using a single Kubernetes cluster for multiple Kyvos deployments is not supported.

Tips

  • In an Azure-based deployment, you can provide a mechanism to configure the database name for tables used in the semantic model Query Analyzer feature. It appends "CLUSTER_NAME" to the default DB name in an Azure-based deployment. "CLUSTER_NAME" is defined in the biserver.properties file and is unique for each Kyvos deployment. 

  • Post-deployment, you can add a new data disk on Query Engines. See the Resources Configuration section for more details. 

  • You can also add new nodes to an existing Azure cluster to add more instances for Query Engines and Analytical Servers.

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