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Davide Mauri

A place for my thoughts and experiences the Microsoft Data Platform

Azure SQL Database DTU Calculator

One of the most common questions when you start to use SQL Azure is related to the choice of the level of service needed for your needs. On the cloud every wasted resource is a tangible additional cost, so it is good to chose the best service level the fits your needs, no more and no less. You can always scale it up later if needed.

The "problem" is that the level is measured in DTU - Database Transaction Units - which a value that represents a mix of CPU, memory and I / O. The problem is that it is very difficult, if not impossible, to calculate this value for an existing on-premises server, so that you can have a compare it with the performance of your well-known on-premises server.

Well, it *was* impossible. Now you can, thanks to this tool:

Azure SQL Database DTU Calculator

developed by Justin Henriksen, a Solution Architect specializing on Azure, that simplifies a lot the estimation effort. After running a PowerShell script to detect some metrics on the On-Premises Server, you have to upload the collected values n that site to get an idea of ​​what level of DTU is optimal in case you want to move that database or server to the cloud.

Of course the more your workload is representative of a real-world scenario, the better estimates you will have: keep this in mind before taking any decision. In addition to this website, there are also two links very useful to better understand what level of service is best suited to your situation:

Enjoy!

Published Tuesday, September 20, 2016 3:28 AM by Davide Mauri
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About Davide Mauri

Director of Software Development & Cloud Infrastructure @ Sensoria, an innovative smart garments and wearable company. After more than 15 year playing with the Microsoft Data Platform, with a specific focus on High Performance databases, Business Intelligence, Data Science and Data Architectures, he's now applying all his skills to IoT, defining architectures to crunch numbers, create nice user experiences and provide meaningful insights, all leveraging Microsoft Azure cloud. MVP on Data Platform since 2006 he has a very strong background development and love both the ER model and OO principles. He is also a fan of Agile Methodology and Automation, which he tries to apply everywhere he can, to make sure that "people think, machines do".

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