I wanted to announce the first open source project officially released by ChannelAdvisor: the QDS Toolbox. This is an effort which Pablo Lozano and Efraim Sharon pushed hard internally and several database administrators and database engineers contributed to (though I wasn’t one of them).

From the summary page:

This is a collection of tools (comprised of a combination of views, procedures, functions…) developed using the Query Store functionality as a base to facilitate its usage and reports’ generation. These include but are not limited to:

– Implementations of SSMS’ GUI reports that can be invoked using T-SQL code, with added funcionalities (parameterization, saving results to tables) so they can be programmatically executed and used to send out mails.
– Quick analysis of a server’s overall activity to identify bottlenecks and points of high pressure on the SQL instance at any given time, both in real time or in the past.
– Cleanup of QDS’ cache with a smaller footprint than the internal one generates, with customization parameters to enable a customizable cleanup (such as removing information regarding dropped objects, cleaning details of ad-hoc or internal queries executed on the server as index maintenance operations).

The biggest of these is the third item. In our environment, Query Store could be a beast when trying to delete old data, and would often be the biggest performance problem on a given server.

In addition, several procedures exist as a way of aggregating data across databases. We have a sharded multi-tenant environment, where we might have 5-15 replicas of a database schema and assign customers to those databases. QDS Toolbox helps aggregate information across these databases so that you don’t need to look at each individually to understand performance problems. The database team has then created reports off of this to improve their understanding of what’s going on.

Check out the QDS Toolbox as a way to clean up data better than the built-in cleanup process and get additional information aggregated in a smart way.


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