Last week I got an email from a community member who had read this older article of mine on baselining, and asked if there were any updates related to SQL Server 2016, SQL Server 2017, or vNext (SQL Server 2019). It was a really good question. I haven’t visited that article in a while and so I took the time to re-read it. I’m rather proud to say that what I said then still holds up today.
The fundamentals of baselining are the same as they were back in 2012 when that article was first published. What is different about today? First, there are a lot more metrics in the current release of SQL Server that you can baseline (e.g. more events in Extended Events, new DMVs, new PerfMon counters, sp_server_diagnostics_component_results). Second, options for capturing baselines have changed. In the article I mostly talked about rolling your own scripts for baselining. If you’re looking to establish baselines for your servers you still have the option to develop your own scripts, but you also can use a third-party tool, and if you’re running SQL Server 2016+ or Azure SQL Database, you can use Query Store.
As much as I love Query Store, I admit that it is not all-encompassing in terms of baselining a server. It does not replace a third-party tool, nor does it fully replace rolling your own scripts. Query Store captures metrics specific to query execution, and you’re not familiar with this feature, feel free to check out my posts about it.
Consider this core question: What should we baseline in our SQL Server environment? If you have a third-party tool, the data captured is determined by the application, and some of them allow you to customize and capture additional metrics. But if you roll your own scripts, there are some fundamental things that I think you should capture such as instance configuration, file space and usage information, and wait statistics.
Beyond that, it really goes back to the question of what problem are you trying to solve? If you are looking at implementing In-Memory OLTP, then you want to capture information related to query execution times and frequency, locking, latching, and memory use. After you implement In-Memory OLTP, you look at those exact same metrics and compare the data. If you’re looking at using Columnstore indexes, you need to look at query performance as it stands right now (duration, I/O, CPU) and capture how it changes after you’ve added one or more Columnstore indexes. But to be really thorough you should also look at index usage for the involved tables, as well as query performance for other queries against those tables to see if and/or how performance changes after you’ve added the index. Very few things in SQL Server work truly in isolation, they’re all interacting with each other in some way…which is why baselining can be a little bit overwhelming and why I recommend that you start small.
Back to the original question: is there anything new to consider with SQL Server 2016 and higher? While third-party tools continue to improve and more metrics are available as new features are added and SQL Server continues to evolve, the only thing “really new” is the addition of Query Store and its ability to capture query performance metrics natively within SQL Server. Hopefully this helps as you either look at different third-party tools that you may want to purchase, or you look at rolling your own set of scripts. If you’re interested in writing your own scripts, I have a set of references that might be of use here.
Lastly, you’ll note that I haven’t said much about Azure SQL Database, and that’s because it’s an entirely different beast. If you have one or more Azure SQL Databases, then you may know that within the Portal there are multiple options for looking at system performance, including Intelligent Insights and Query Performance Insight. Theoretically, you could still roll your own scripts in Azure SQL DB, but I would first explore what Microsoft provides to see if it meets your needs. Have fun!