Looking back through previous content, I came across this post by Jerry Eshbaugh.

 

SQL Server Two Ways - SAM AppInsight for SQL and Database Performance Analyzer

 

I read through it again and realized it still resonates in a big way. I’d like to add this foreword and bring it up to speed given some recent changes. SolarWinds® Database Performance Analyzer (DPA) wait-time statistics and resource metrics were recently added to the Performance Analysis view (lovingly known as PerfStack) in the Orion® Platform. I believe this addition gives IT professionals the end-to-end visibility they want. I know we all tend to exist in silos, but that doesn’t mean we don’t want greater upstream and downstream performance metrics.

 

Now you can easily see if your database performance is impacting application response time, and if storage latency is causing longer I/O related database activities. Also, you can view existing dependencies and what relates to what. These customizable dashboards are way cool!

 

If you haven’t had a chance to check it out, you have a couple of ways to do so:

  • If you own just DPA (without any Orion products), you can now download a standalone DPA Integration Module (DPAIM) from your customer portal as part of your existing license. That’s right! It’s free. You will be limited to DPA data only, as there are no other modules running to collect application, server, storage, and network data, etc.
  • If you already have another Orion product and are on the latest release, DPAIM may be installed (it comes with Server and Application Monitor for example), or you can install the DPAIM module from your customer portal on your Orion Platform.
  • If you aren’t ready to commit to a download, you can check out oriondemo.solarwinds.com and try out the Performance Analysis view. This might be a good start to play around with, but remember, it is demo data. Things may not line up exactly. Some of the data might be invented. The best way to get the most out of the PerfStack dashboard would be to look at your own data with it, which is infinitely more interesting!

 

Let us know what you think about it!