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Wait Stats: Necessary but not Sufficient

Greg Gonzalez explains how wait stats are not the only thing you should look at to determine system health:

Waits and Queues has been used as a SQL Server performance tuning methodology since Tom Davidson published the above article as well as the well-known SQL Server 2005 Waits and Queues whitepaper in 2006. When used in combination with resource metrics, waits can be valuable for assessing certain performance characteristics of the workload and aid in steering tuning efforts. Waits data is surfaced by many SQL Server performance monitoring solutions, and I’ve been an advocate of tuning using this methodology since the beginning. The approach was influential in the design of the SQL Sentry performance dashboard, which presents waits flanked by queues (key resource metrics) to deliver a comprehensive view of server performance.

However, some seem to have missed Davidson’s point regarding the importance of resources and rely almost entirely on waits to present a picture of query performance and system health. Waitstats come directly from the SQL Server engine and are easy to consume and categorize. Waiting queries mean waiting applications and users, and no one likes to wait! From a marketing standpoint this is pure gold for a SQL Server monitoring tools vendor – it is easier to evangelize waits analysis as a singular solution for making queries and applications faster than the full story, which is more involved.

Unfortunately, a waits-focused approach to the exclusion of resource analysis can mislead users, and worst-case leave them flying blind. SentryOne team members Kevin Kline and Steve Wright have previously touched on this here and here. In this post I’m going to take a deeper dive into some recent research made possible by Query Store that has shed new light on how deficient waits-focused tuning can truly be.

Interesting research and Greg does a great job of explaining it.