vRealize Operations Manager includes functions and operators that you can use in super metric formulas. The functions are either looping functions or single functions.

Looping Functions

Looping functions work on more than one value.

Table 1. Looping Functions

Function

Description

avg

Average of the collected values.

combine

Combines all of the values of the metrics of the included objects in a single metric timeline.

count

Number of values collected.

max

Maximum value of the collected values.

min

Minimum value of the collected values.

sum

Total of the collected values.

Note:

vRealize Operations Manager 5.x included two sum functions: sum (expr) and sumN (expr, depth). vRealize Operations Manager 6.x includes one sum function: sum (expr). Depth is set at depth=1 by default. For more information about setting depth, refer to Create a Super Metric.

Looping Function Arguments

The looping function returns an attribute or metric value for an object or object type. An attribute is metadata that describes the metric for the adapter to collect from the object. A metric is an instance of an attribute. The argument syntax defines the desired result.

For example, CPU usage is an attribute of a virtual machine object. If a virtual machine has multiple CPUs, the CPU usage for each CPU is a metric instance. If a virtual machine has one CPU, then the function for the attribute or the metric return the same result.

Table 2. Looping Function Formats

Argument syntax example

Description

funct(${this, metric =a|b:optional_instance|c})

Returns a single data point of a particular metric for the object to which the super metric is assigned. This super metric does not take values from the children or parents of the object.

funct(${this, attribute=a|b:optional_instance|c})

Returns a set of data points for attributes of the object to which the super metric is assigned. This super metric does not take values from the child or parent of the object.

funct(${adapterkind=adaptkind, resourcekind=reskind, resourcename=resname, identifiers={id1=val1id2=val2,…}, metric=a|b:instance|c})

Returns a single data point of a particular metric for the resname specified in the argument. This super metric does not take values from the children or parents of the object.

funct(${adapterkind=adaptkind, resourcekind=reskind, resourcename=resname, identifiers={id1=val1, id2=val2,…}, attribute=a|b:optional_instance|c})

Returns a set of data points. This function iterates attributes of the resname specified in the argument. This super metric does not take values from the child or parent of the object.

funct(${adapterkind=adaptkind, resourcekind=reskind, depth=dep}, metric=a|b:optional_instance|c})

Returns a set of data points. This function iterates metrics of the reskind specified in the argument. This super metric takes values from the child (depth > 0) or parent (depth < 0) objects, where depth describes the object location in the relationship chain.

For example, a typical relationship chain includes a datacenter, cluster, host, and virtual machines with the datacenter at the top and the virtual machines at the bottom. If the super metric is assigned to the cluster and the function definition includes depth = 2, the super metric takes values from the virtual machines. If the function definition include depth = -1, the super metric takes values from the datacenter.

funct(${adapterkind=adaptkind, resourcekind=reskind, depth=dep}, attribute=a|b:optional_instance|c})

Returns a set of data points. This function iterates attributes of the reskind specified in the argument. This super metric takes values from the child (depth > 0) or parent (depth < 0) objects.

For example, avg(${adapterkind=VMWARE, resourcekind=VirtualMachine, attribute=cpu|usage_average, depth=1}) averages the value of all metric instances with the cpu|usage_average attribute for all objects of type VirtualMachine that the vCenter adapter finds. vRealize Operations Manager searches for objects one level below the object type where you assign the super metric.

Single Functions

Single functions work on only a single value or a single pair of values.

Table 3. Single Functions

Function

Format

Description

abs

abs(x)

Absolute value of x. x can be any floating point number.

acos

acos(x)

Arccosine of x.

asin

asin(x)

Arcsine of x.

atan

atan(x)

Arctangent of x.

ceil

ceil(x)

The smallest integer that is greater than or equal to x.

cos

cos(x)

Cosine of x.

cosh

cosh(x)

Hyperbolic cosine of x.

exp

exp(x)

e raised to the power of x.

floor

floor(x)

The largest integer that is less than or equal to x.

log

log(x)

Natural logarithm (base x) of x.

log10

log10(x)

Common logarithm (base 10) of x.

pow

pow(x,y)

Raises x to the y power.

rand

rand()

Generates a pseudo random floating number greater than or equal to 0.0 and less than 1.0.

sin

sin(x)

Sine of x.

sinh

sinh(x)

Hyperbolic sine of x.

sqrt

sqrt(x)

Square root of x.

tan

tan(x)

Tangent of x.

tanh

tanh(x)

Hyperbolic tangent of x.

Operators

Operators are mathematical symbols to enclose or insert between functions.

Table 4. Operators

Operators

Description

+

Plus

-

Subtract

*

Multiply

/

Divide

%

Modulo

==

Equal

!=

Not equal

<

Less than

<=

Less than, or equal

>

Greater than

>=

Greater than, or equal

||

Or

&&

And

!

Not

? :

Ternary operator. If/then/else

For example: conditional_expression ? expression_if_condition_is_true : expression_if_condition_is_false

For more information about ternary operators, see Enhancing Your Super Metrics.

( )

Parentheses

[ ]

Use in an array of expressions

[x, y, z]

An array containing x, y, z. For example, min([x, y, z])