A rollup super metric is the most common example of a super metric. It uses transformation type functions such as sum, avg, min, and count. It then applies them through a looping function of all child objects matching the object and attribute type. The result of this calculation is then available as a super metric on the object where the super metric is applied.
Let's go through an example using Cluster Level Datastore free disk space. Now, before you email me and point out that this metric already exists by default in the vCenter adapter and there is no need to create a super metric, I will point out that you are correct, however, this example well illustrates the point of rollups. We will go through a unique example later:
The preceding ...
