Which two options can be applied as a super metric? (Choose two.)

Question

Options

• AThe average CPU usage of VMs within a Datacenter
• BThe difference of CPU utilization for each VM between two defined time stamps
• CString operators that are valid to be used with mathematical calculations in a function
• DCount of Non-Windows VMs in a vSphere cluster
• EThe average SCSI count with disk size of VMs within an ESXi host

• A
  82% (27)
• B
  9% (3)
• C
  3% (1)
• E
  6% (2)

Explanation

Super metrics in VMware vRealize Operations aggregate numeric metric data across multiple objects within a container (e.g., cluster, datacenter, host). Options A and D are correct because they both represent exactly this: A calculates an average of a single numeric metric (CPU usage) across multiple child objects (VMs) rolled up to a parent object (Datacenter), and D uses a count function to tally a filtered subset of objects (non-Windows VMs) within a container (vSphere cluster) - both are standard, supported super metric patterns.

B is wrong because super metrics operate across multiple objects at a point in time, not across two timestamps for a single object - time-based delta comparisons belong to trend or transformation features, not super metrics.

C is wrong because super metrics only support mathematical/numeric operators; string operators cannot be used in super metric formulas and are therefore invalid.

E is a distractor because it combines two unrelated metrics (SCSI count and disk size) in an ambiguous compound way that doesn't represent a valid, coherent super metric formula - super metrics aggregate one metric across many objects, not blend two dissimilar metrics together.

Memory tip: Think "Aggregate or Count across many objects in a container" - if the operation is an average/sum/min/max/count of one metric rolled up to a parent object, it's a super metric. If it involves time deltas, strings, or blended multi-metric mashups, it's not.

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