SharePoint: Monitoring individual List usage and performance

Update Nov 27, 2014: Just posted this YouTube video that shows how to easily identify top SharePoint Performance Problems: SharePoint Performance Analysis in 15 Minutes

We all know that SharePoint list performance can degrade the more items are stored in the lists and depending on how the lists are filtered when viewed. You will find many arcticles and blog entries talking about the 2000 items per list limit. The 2000 items however are not the real problem – you can in fact have much more items in the list. It all depends on how those lists are viewed. The question therefore is: How can we identify which lists have degraded in performance and how are they commonly used?

In order to do the correct performance correcting actions we first need to understand the current usage scenarios and analyse the resulting performance problems.

Scenario 6: Which are my slowest lists, how are they used and why are they slow?

There are multiple ways to figure out current access statistics of your SharePoint application. You can analyze IIS log files or you can make use of the SharePoint Usage Reporting Feature.

The easiest way monitor list performance is by analyzing the http response times to the respective SharePoint List and SharePoint View URLs. A SharePoint URLs has the following format: http://servername/site/{LISTNAME}/{VIEWNAME}.aspx. In order to analyze it we can group the requests based on those two indicators. I used dynaTrace’s Business Transaction Feature to group the captured PurePath’s according to a regular expression. Following images show the usage scenario of my lists and views:

Shows Individual List Performance and Usage counts
Shows Individual List Performance and Usage counts
Shows individual View Performance and Usage count
Shows individual View Performance and Usage count

These results give us a good indication about which lists and views are used more frequently and how well they perform.

Additionally to analyzing the HTTP Requests – which only provides accurate data for pages that display the specific list or view – we can analyze the list usage of custom web parts or custom pages that access more than just a single list or view or that access a list in a special filtered way.
We can do that by analyzing the interaction with the SharePoint object model like SPRequest.RenderViewAsHtml which is used to render lists and views or access to the SPList and SPView. The following illustration shows usage and performance metrics based on SPRequest method invocations:

Analyzing Performance and Usage through SharePoint Object Model
Analyzing Performance and Usage through SharePoint Object Model

The illustration above shows us the internal GUIDs of the Lists. Each list and view is uniquely identified with a GUID. There are different ways to find out the actual list name: You can paste the GUID in the URL to edit the settings of the list or view. Here is an example: http://servername/_layouts/listedit.aspx?List={GUID} (GUID must be URL-Encoded). The other option would be to open your content database and query the table AllLists. This table contains both the GUID and the List name.

Why are certain lists slower?

Now as we know which lists and views are accessed frequently we can focus on those that show bad signs of performance. In order to improve the end user experience we should focus on lists that are accessed very frequently rather than lists that are accessed just occasionally.

There can be multiple reasons why lists perform slow:

  • Too many items are displayed in the list view
  • Too many items in the list without using filters and indexed columns
  • Inefficient data access by custom web parts

I already covered list performance in my previous blog posts and therefore suggest that you check them out. I am also going to focus the next blog entries on indexed columns which will show you how indexing in SharePoint really works and what you want to consider when setting up indices.


Its important to understand which lists and views are accessed frequently and what the performance characteristics are. Knowing the usage patterns allows you to specifically focus on those lists and views that impact most of our end users.

Andreas Grabner has 20+ years of experience as a software developer, tester and architect and is an advocate for high-performing cloud scale applications. He is a regular contributor to the DevOps community, a frequent speaker at technology conferences and regularly publishes articles on You can follow him on Twitter: @grabnerandi