App-Centric Assessments with SQL Server Xplorer

By Jeremy Launier
| min

So you want to run Microsoft SQL Server on Nutanix? Nutanix fully supports Microsoft SQL server configurations ranging in scale up, scale out and high availability configurations. Nutanix has developed and leverages a number of software automations and best practices designed to ensure that you not only get the best possible performance and availability but also leverage the least amount of resources to do so. To support this effort, Nutanix recently made available Xplorer, a companion app to http://productsizer.nutanix.comNutanix Sizer. The intent of Xplorer is to provide a flexible, API enabled application and framework to drastically simplify how we capture and interpret sizing requirements, starting with Microsoft SQL Server.

Xplorer combines an app-centric approach to discovering and characterizing your SQL Servers with a best practice rules engine. Xplorer does this by talking directly to SQL Server at an application level. Xplorer is able to capture and interpret both configuration as well as performance related data without the installation of agents and fully supports the discovery of both physical and virtualized SQL Servers.

This captured data is kept within the confines of your network and is interpreted by a best-practice rules engine to automatically construct a best-practice based solution design template following a Simple YAML TOSCA specification.

Xplorer provides native integration with Nutanix Sizer and allows for a seamless flow from initial discovery of your SQL Servers, to design, to an automated hardware and software recommendation provided by Sizer.

How does this help you as a customer of Nutanix? Xplorer speeds up the process of understanding your requirements, helps you to gain insight into the inner workings of your database servers, provides you with a best practice template to follow based on your specific requirements, and ensures that any hardware recommended to you by Nutanix or Nutanix partners is substantiated by objective data. This process drives quality in the sizing process and provides continuity of pre-sales requirements to post-sales implementation.