The Dataset Group function provides a powerful facility for you to quickly examine and
monitor the space and performance attributes of a collection of data sets.
By defining a series of data set groups and masks, any collection of data sets can be displayed
as a report within the portal, and Situations can be written to monitor the space or
performance attributes of those data sets. This section presents examples and ideas of
how this function can add value for storage management and administration.
Dataset Groups can be thought of as a more powerful version of the ISPF DSLIST utility
(that is, 3.4). In addition to creating lists of data sets,
OMEGAMON allows you to name and save those lists in groups, and provides much more powerful
name masking capabilities. In addition, all of the attributes associated with the data
sets in the generated lists can be used in reports, alerts and Storage Toolkit actions.
The
OMEGAMON Dataset Group function, in its current form, is not intended as a direct substitute
for ISPF 3.4. While ISPF 3.4 is geared towards producing interactive, user-generated
ad-hoc lists of data sets and running simple actions against those data sets, one at a
time, the
OMEGAMON Dataset Groups are more static in nature, and are better used for viewing large sets
of related files and their attributes (individually and as a group), generating alerts
based on those attributes, and taking actions.
Note: The new Dataset Group function
differs from the User DASD Group and Application functions in that Dataset Groups
start at the system catalog by using a name mask to create a list of matching data
sets; User DASD Groups start at the volume or storage group level, and Applications
start at the job level, to create their volume/data set lists. The important
difference here is that using Dataset Groups you do not need to know where a data
set is located or which application accesses it. Using this data set orientation can
be more useful for end-users and storage administrators who prefer to perform
certain tasks from this perspective.
The following examples describe how to use
OMEGAMON for StorageOMEGAMON for Storage to monitor a number of events that might occur in your system. They are:
- “Obtaining an overview of space usage”
- “Identifying data sets with excess space”
- “Create an alert when response time exceeds specific thresholds”
- “Identify VSAM data sets with excessive CA/CI splits”
- “Cataloged and not-allocated data sets”
- “Notify the Production Scheduling group when a critical data set exceeds a
specified number of extents”
- “Automatically migrate infrequently used data sets”
Obtaining an overview of space usage
Follow this procedure if you want to determine the amount of space that is being used
by your applications. Initially you can create a group of your critical data sets,
possibly dividing them into development, test, and production data sets.
1. Use the processes described in Adding a dataset group to add a new data set group. In the
case of the example shown in Figure 2, there are four groups, for development, test, production, and
history data sets.