Example 1 of the Domino DB Access Chart article [ Domino DB Access Chart - Example I ] has shown you one practical example. We would like to continue with a second example in which you easy depict a document count and/or view count of a Database in a Chart for multiple servers.

The aim is basically to see if there have been any replication issues - different document counts - over time.



Create a Domino DB Access sensor

Before we can create a chart, we need to have a sensor in place.
In this example we create a simple Domino DB Access sensor definition where the sensor should open a random document within the People View of the names.nsf . 



Last but not least, specify all your servers on which you want to monitor the document / view count as well provide a certain schedule for the sensor.


Create a Line Chart

Now let’s create a line chart and select the following two statistics. You can find them easier if you enter “count” within the search field.


-Click Next

-Make sure you leave the Ascending Value Filter disabled.

-Make sure to add the correct Target as well to specify a schedule and a name for this charting definition.

-Whenever you have done this, just generate the chart.

The initial chart needs to be adjusted in a way that you specify a maximum value for all Y-Axes. The outcome should be something like below where you get per server and per statistic one line. If the lines are overlapping with each other the replication seems to be fine.

Create a Bar Chart

Furthermore you can create a Bar Chart which draws you a different picture out of these values. With the Bar Chart you can choose between the average values, sum of all values, a.s.o… for the specified timeframe.

In our example we have chosen the average value. The total document count as well view count is in our case equal across the two servers.



The Domino DB Access Sensor gives you certain information which you further can use for drawing individual charts. It simulates a DB access from a user point of view which gives you further insight of the performance of your environment. If you combine the time_to_view timing information with the Update.PendingList statistic you may see some correlation (possible high Update.Pendinglist, possible high time_to_view).

Please note, that this article covers only the charting part so no information was given regarding individual actions you can trigger. For this you will find specific knowledge base article in the near future