After you create a super metrics, you assign it to one or more object types. For instance, you could assign a super metrics to cluster object (resource kinds) that calculates the average memory demand on all virtual machines in the cluster.
Super metrics can be found on the Content page.
When creating a super metric, there are several different functions to choose from for your formula. They are either looping functions or single functions. Looping functions work on more than one value and single functions on a single value.
Also, there are three different
: The ability to apply a looping function (sum, Rollup , avg ) to a group of resources that all have the same metrics. etc
- Generic Resource: The ability to combine metrics on a type of resource using standard mathematical operators.
Specific resource or pass-through: The ability to combine specific resource and apply them to any resource. metris
The looping functions are:
: Average of avg values collected : Combines all of the values of the metrics of the included objects in a single metric timeline combine : Number of values collected count : Maximum value of the collected values max : Minimum value of the collected values min : Total of the collected values sum
The last function that needs to be discussed is depth, depth supports multilayer
Let's build out a super metric to show the average CPU utilization for all the virtual machines on a host. First, we are going to select the looping function of
Next we are going to select the left parenthesis
On the Object Types, we are going to drop down the Adapter Type drop-down list and select
From the object types that appear, we are going to scroll down until we find Virtual Machine and select it. In the lower left panel, on the Metrics list, we are going to expand the CPU category, then scroll down and double-click the Usage (%) metric.
In the above picture, we can see that the formula shows in the top panel as
Give your super metric a name, you can see in my example I have used the name Average Virtual Machine CPU Usage %.
Next we are going to verify the super metric formula is working. Click the Visualize Super Metric button. On Object Types, click the Adapter Type drop-down menu and select
After you verified that your super metric works, we need to add it to an object. On the Objects Types tab we are going to click the + button to add a new object type.
Before we can see our super metric in All Metrics on the Troubleshooting tab, we need to add it to the default policy. We are going to edit the
Drop-down the Attribute Type filter and uncheck Metric and Property, this will bring up only the super metric you created.
Change the State of the super metrics from Inherited to Local and save your changes.
Our super metrics should now be available in All Metrics under Troubleshooting, because we set the Object Type as Host System, we will only see this super metrics when a host has been selected. In the picture below, I
the Super Metrics tree and Average Virtual Machine CPU Usage % is available have expand labesx07.home.virtlab.com. for
After double-clicking the metrics, a chart for the average virtual machine CPU usage % on labesx07 displays on the right; below that chart is CPU usage of the two virtual machines on the host. The SCOM virtual machine is running between 4.14% and 4.76% and the VMware vCenter Server Production virtual machine is running between 8.43% and 9.58%. The virtual machine average for both is 6.45% at that specific point in time.
This is merely a sample of what you can do with super metrics. Super metrics are really powerful, they are certainly worth exploring to find out how it can enhance your monitoring capabilities.