IBM Endpoint Manager Inspectors Reference

Terminology

Win: Windows
Lin: Red Hat and SUSE Linux
Sol: SUN Solaris
HPUX: Hewlett-Packard UNIX version
AIX: IBM AIX
Mac: Apple Macintosh
Ubu: Ubuntu/Debian
WM: Windows Mobile

The version (e.g. Lin:8.1) corresponds to the version of the IEM product (8.1) in which the inspector was introduced in the client on that platform.
The version number is not shown if it is less than 8.0.


Platform


Contents

Action Objects
Authorization Objects
Client Objects
Directory Services
Environment Objects
Filesystem Objects
Firewall Objects
Fixlet Objects
Formatting Objects
Installed System Software
Introspectors
License Objects
Microsoft IIS Metabase Objects
Miscellaneous
Networking Objects
Power Objects
Primitive Objects
Registry Objects
Session Objects
Session Statistics
exponential projection
fixlet count pair
historical computer count
historical fixlet count
linear projection
rate
rate with multiplicity
statistic range
statistical bin
Site Objects
SMBIOS objects
System Objects
Task Objects
User Objects
Windows Mobile Device Objects
WMI Objects
World Objects

IBM Endpoint Manager wiki

Session Statistics

These Inspectors allow you to gather data and perform statistics during a session. For more information about statistical aggregation, see the Resource section at the end of this guide.

fixlet count pair

The <fixlet count pair> Inspectors return information about the Fixlet count pair objects for each severity level.

Creation Methods

DeclarationDescriptionPlatforms (?)
count map of <historical fixlet count>Returns all of the <fixlet count pair> objects (one for each severity level) that were saved with the specified historical Fixlet count.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
count of <fixlet count pair><integer>

Plural: counts
Returns the Fixlet count for each severity level of the Fixlet count pairs.Win
source severity of <fixlet count pair><string>

Plural: source severitys
Returns the severity level corresponding to the given Fixlet count pair.Win

historical computer count

The <historical computer count> Inspectors provide information about historical computer count objects.

Creation Methods

DeclarationDescriptionPlatforms (?)
all computer countReturns a list of all <historical_computer_count> objects.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
count of <historical computer count><integer>

Plural: counts
Returns the count when the specified historical computer count was last archived.Win
database id of <historical computer count><integer>

Plural: database ids
In the Web Reports environment, this Inspector returns the numeric ID of the database containing the specified historical computer count.Win
time of <historical computer count><time>

Plural: times
Returns the time when the specified count was archived.Win

historical fixlet count

The <historical fixlet count> objects provide historical information about the number of Fixlets at different severity levels.

Creation Methods

DeclarationDescriptionPlatforms (?)
all fixlet countReturns a list of all the historical Fixlet counts.Note: This is a Web Reports-only Inspector.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
count map of <historical fixlet count><fixlet count pair>

Plural: count maps
Returns all of the <fixlet count pair> objects (one for each severity level) that were saved with the specified historical Fixlet count.Win
database id of <historical fixlet count><integer>

Plural: database ids
In the Web Reports environment, this Inspector returns the numeric ID of the database containing the specified historical Fixlet count.Win
time of <historical fixlet count><time>

Plural: times
Returns the time when the specified historical Fixlet count was calculated.Win

statistic range

Statistical ranges are time intervals used to examine particular statistical bins.

Creation Methods

DeclarationDescriptionPlatforms (?)
statistic range of <bes property>Returns the range of statistical bins associated with the given property. The property must be marked for statistical aggregation. If not, or if no clients have reported results, it throws NoSuchObject.Win
range <time range> of <statistic range>For the duration of the specified time range, (time0 to time1), this Inspector returns a sub-range of bins beginning with earliest bin containing time0 and going up to (but not including) the bin containing time1. If either of these bins does not exist, it throws NoSuchObject.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
bin at <time> of <statistic range><statistical bin>

Plural: bins at
Returns the bin in the specified statistical range which brackets the given time. If no such bin exists, it throws NoSuchObject.Win
bin of <statistic range><statistical bin>

Plural: bins
Returns a list of the individual bins in the specified range. Primarily useful after downsampling (see total <time interval> of <statistic range>).Win
end of <statistic range><time>

Plural: ends
Returns the ending time of the statistical range.Win
range <time range> of <statistic range><statistic range>

Plural: ranges
For the duration of the specified time range, (time0 to time1), this Inspector returns a sub-range of bins beginning with earliest bin containing time0 and going up to (but not including) the bin containing time1. If either of these bins does not exist, it throws NoSuchObject.Win
start of <statistic range><time>

Plural: starts
Returns the starting time of the statistical range.Win
total <time interval> of <statistic range><statistical bin>

Plural: totals
This Inspector can be used to downsample or consolidate bins. It statistically totals over the given range, producing a new series of bins broken down by the (larger) specified time interval. The resulting range will start and end on a multiple of the interval. For example, if you ask for day bins, the results will start and end at midnight. If the specified time interval is not a multiple of the length of the starting bin of the range, this Inspector throws NoSuchObject. For example, you cannot get 6 hour totals of a range which starts with day bins.Win
total of <statistic range><statistical bin>

Plural: totals
Totals the bins over the specified range, producing a single summary bin. This allows you to reduce the data by constraining the range.Win

statistical bin

Statistical bins contain property information summed over all computers in a given time period.

Creation Methods

DeclarationDescriptionPlatforms (?)
bin at <time> of <statistic range>Returns the bin in the specified statistical range which brackets the given time. If no such bin exists, it throws NoSuchObject.Win
bin of <statistic range>Returns a list of the individual bins in the specified range. Primarily useful after downsampling (see total <time interval> of <statistic range>).Win
total <time interval> of <statistic range>This Inspector can be used to downsample or consolidate bins. It statistically totals over the given range, producing a new series of bins broken down by the (larger) specified time interval. The resulting range will start and end on a multiple of the interval. For example, if you ask for day bins, the results will start and end at midnight. If the specified time interval is not a multiple of the length of the starting bin of the range, this Inspector throws NoSuchObject. For example, you cannot get 6 hour totals of a range which starts with day bins.Win
total of <statistic range>Totals the bins over the specified range, producing a single summary bin. This allows you to reduce the data by constraining the range.

Example:
mean of total of range ((now - day) & now) of statistics of property 1 of current analysis - Returns the mean (average) value across all reported values in the last day. Note that this might fail if there have been no reports in the last day.
Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
end of <statistical bin><time>

Plural: ends
Returns the ending time of the specified statistical bin.Win
exponential fit of <statistical bin><exponential projection>

Plural: exponential fits
Calculates a least-squares fit on the sum of the logarithms of the absolute values of the values. This provides a way to extrapolate an exponential change of values.Win
failure rate of <statistical bin><floating point>

Plural: failure rates
The integral over time of the number of failing computers divided by the integral over time of the number of reporting computers.Win
geometric mean of <statistical bin><floating point>

Plural: geometric means
Returns the geometric mean of the specified statistical bin.Win
javascript array <string> of <statistical bin><html>

Plural: javascript arrays
Produces a section of JavaScript which initializes the named array of objects, one for each input bin. Each object in the array has JavaScript properties which match the above bin data properties. For each inspector property, the equivalent JavaScript property is named by CamelCasing the name of the inspector property.Win
kurtosis of <statistical bin><floating point>

Plural: kurtoses
Returns the kurtosis (a measure of the "narrowness" of the distribution) of the specified statistical bin.Win
length of <statistical bin><time interval>

Plural: lengths
Returns a time interval corresponding to the length (or period) of the specified bin.Win
linear fit of <statistical bin><linear projection>

Plural: linear fits
Calculates a least-squares fit on the values, providing a tool for extrapolating a linear change of values.Win
logarithm kurtosis of <statistical bin><floating point>

Plural: logarithm kurtoses
The kurtosis of the logarithms of the absolute values of the nonzero reported values.Win
logarithm skewness of <statistical bin><floating point>

Plural: logarithm skewnesses
The skewness of the logarithms of the absolute values of the nonzero reported values.Win
logarithm standard deviation of <statistical bin><floating point>

Plural: logarithm standard deviations
The standard deviation of the logarithms of the absolute values of the nonzero reported values.Win
logarithm variance of <statistical bin><floating point>

Plural: logarithm variances
The variance of the logarithms of the absolute values of the nonzero reported values.Win
maximum single computer total of <statistical bin><floating point>

Plural: maximum single computer totals
Returns a floating point number representing the largest computer total in the specified bin.Win
maximum value of <statistical bin><floating point>

Plural: maximum values
The maximum single value reported by any computer over the duration of the bin.Win
mean computer count of <statistical bin><floating point>

Plural: mean computer counts
This is the integral over time of the number of computers reporting this property divided by the duration of the bin. It might be fractional if computers started or stopped reporting this property during the interval of the bin.Win
mean failing computer count of <statistical bin><floating point>

Plural: mean failing computer counts
Returns the mean count of the computers where the inspection has failed.Win
mean logarithm of <statistical bin><floating point>

Plural: mean logarithms
The integral over time of the sum of the logarithms of the absolute values of all nonzero reported values, divided by the integral over time of the number of nonzero reported values.Win
mean nonzero value count of <statistical bin><floating point>

Plural: mean nonzero value counts
Provides a measure of nonzero values, which is useful in interpreting the logarithmic results, which ignore zero values. The logarithmic results generally aren't interesting for any property that can be zero, so this Inspector can be used to validate property statistics.Win
mean of <statistical bin><floating point>

Plural: means
The integral over time of the sum of all reported values, divided by the integral over time of the number of reported values. The variance, standard deviation, skewness, and kurtosis inspectors have this same domain. In particular, computers that fail and computers that report no values don't affect these statistics.Win
mean sample interval of <statistical bin><time interval>

Plural: mean sample intervals
The sample interval is the time between consecutive samples on a single computer. The mean sample interval is the integral over time of the sum over computers of the sample interval divided by the integral over time of the number of reporting computers. This is the inverse of the mean sample rate.Win
mean sample rate of <statistical bin><rate>

Plural: mean sample rates
This is the inverse of the mean sample interval.Win
mean successful computer count of <statistical bin><floating point>

Plural: mean successful computer counts
Returns the mean count of the computers where the inspection has succeeded.Win
mean total of <statistical bin><floating point>

Plural: mean totals
The integral over time of the sum of all values reported divided by the integral over time of the number of computers reporting this property (successfully or failing).Win
mean value count of <statistical bin><floating point>

Plural: mean value counts
This is the integral over time of the number of values reported divided by the integral over time of the number of computers reporting. That is, this is a mean over both time and computers.Win
mean zero value count of <statistical bin><floating point>

Plural: mean zero value counts
Provides a measure of zero values, which is useful in interpreting the logarithmic results, which ignore zero values. The logarithmic results generally aren't interesting for any property that can be zero, so this Inspector can be used to test for that issue.Win
minimum single computer total of <statistical bin><floating point>

Plural: minimum single computer totals
The minimum over time and computers of the total of simultaneous values. (Thus, for a singular property, the same as "minimum value.").Win
minimum value of <statistical bin><floating point>

Plural: minimum values
The minimum single value reported by any computer over the duration of the bin.Win
skewness of <statistical bin><floating point>

Plural: skewnesses
Returns a floating point number representing the skewness (a measure the assymetry of the data) over the specified bin.Win
standard deviation of <statistical bin><floating point>

Plural: standard deviations
Returns a floating point number representing the standard deviation of the data over the specified bin.Win
start of <statistical bin><time>

Plural: starts
Returns the starting time of the statistical bin.Win
success rate of <statistical bin><floating point>

Plural: success rates
The integral over time of the number of successful computers divided by the integral over time of the number of reporting computers.Win
total lower bound of <statistical bin><floating point>

Plural: total lower bounds
Returns the lower bound of a group of statistical bins.Win
total upper bound of <statistical bin><floating point>

Plural: total upper bounds
Returns the upper bound of a group of statistical bins.Win
variance of <statistical bin><floating point>

Plural: variances
Returns the variance of the specified statistical bin.Win

rate

Rates are floating point numbers divided by time intervals. These Inspectors let you examine and convert rate objects.

Creation Methods

DeclarationDescriptionPlatforms (?)
<floating point> * <rate>Operate on a rate with a floating point number, returning a new rate, where {op} is one of: *, /.Win, Mac
<floating point> / <time interval>Divides a floating point number by a time interval to yield a rate.Win, Mac
<rate> {op} <floating point>Operate on a rate with a floating point number, returning a new rate, where {op} is one of: *, /.Win, Mac
mean sample rate of <statistical bin>This is the inverse of the mean sample interval.Win
maximum of <rate>Returns the maximum value from a list of <rate> types.Win, Mac
minimum of <rate>Returns the minimum value from a list of <rate> types.Win, Mac
- <rate>Returns the negative of the given rate.Win, Mac
<rate> {op} <rate>Operate on two rates, returning a new rate, where {op} is one of: -, +.Win, Mac
rate of <linear projection>Returns the slope of the linear projection. Multiply this by a time interval to compute the projected growth over that period.Win, Mac

Operators

DeclarationReturn TypeDescriptionPlatforms (?)
- <rate><rate>Returns the negative of the given rate.Win, Mac
<rate> * <time interval><floating point>Multiplies a <rate> by a <time interval>, producing a floating point number.Win, Mac
<rate> {cmp} <rate><boolean>Compare two rates, returning a boolean TRUE or FALSE, where {cmp} is one of: <, <=, =.Win, Mac
<rate> {op} <rate><rate>Operate on two rates, returning a new rate, where {op} is one of: -, +.Win, Mac
<time interval> * <rate><floating point>Multiplies a <time interval> by a <rate>, producing a floating point number.Win, Mac

Properties

DeclarationReturn typeDescriptionPlatforms (?)
<rate> as string<string>Casts a rate as a string.Win, Mac
extrema of <rate><( rate, rate )>

Plural: extremas
Returns the minimum and maximum extreme values of the given list of <rate> types.Win, Mac
maximum of <rate><rate>

Plural: maxima
Returns the maximum value from a list of <rate> types.Win, Mac
minimum of <rate><rate>

Plural: minima
Returns the minimum value from a list of <rate> types.Win, Mac
unique value of <rate><rate with multiplicity>

Plural: unique values
Returns the unique values of a given list of <rate> types, removing duplicates and sorting by value.Win, Mac

rate with multiplicity

The <rate with multiplicity> Inspectors deal with rate arrays, allowing you to extract unique rate values and count them.

Creation Methods

DeclarationDescriptionPlatforms (?)
unique value of <rate>Returns the unique values of a given list of <rate> types, removing duplicates and sorting by value.Win, Mac

Properties

DeclarationReturn typeDescriptionPlatforms (?)
multiplicity of <rate with multiplicity><integer>

Plural: multiplicities
Sorts the list and returns the multiplicity, or count, of each unique element in the specified list of multiple <rate> types.Win, Mac

linear projection

The <linear projection> Inspectors return statistical correlation information about the linearity of specific aggregated properties.

Creation Methods

DeclarationDescriptionPlatforms (?)
linear fit of <statistical bin>Calculates a least-squares fit on the values, providing a tool for extrapolating a linear change of values.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
correlation coefficient of <linear projection><floating point>

Plural: correlation coefficients
Returns a floating-point number between -1 and 1, representing how well a linear projection fits the data.Win, Mac
extrapolation <time> of <linear projection><floating point>

Plural: extrapolations
Returns the projected value at the specified time, assuming a linear projection.Win, Mac
rate of <linear projection><rate>

Plural: rates
Returns the slope of the linear projection. Multiply this by a time interval to compute the projected growth over that period.Win, Mac

exponential projection

The <exponential projection> Inspectors return statistical correlation information about the logarithms of the aggregated properties.

Creation Methods

DeclarationDescriptionPlatforms (?)
exponential fit of <statistical bin>Calculates a least-squares fit on the sum of the logarithms of the absolute values of the values. This provides a way to extrapolate an exponential change of values.Win

Properties

DeclarationReturn typeDescriptionPlatforms (?)
correlation coefficient of <exponential projection><floating point>

Plural: correlation coefficients
Returns a floating-point number between -1 and 1, representing how well an exponential projection fits the data.Win, Mac
extrapolation <time> of <exponential projection><floating point>

Plural: extrapolations
Returns the projected value at the specified time, assuming an exponential projection.Win, Mac
rate <time interval> of <exponential projection><floating point>

Plural: rates
Returns the slope of the exponential projection over the specified time interval.Win, Mac