The OMEGAMON Storage PTF UJ09160 introduced several new features which could be useful for Realtime Data Set Metrics (RDM) and Tivoli Enterprise Portal (TEP) users.
The new view by “All Datasets” in the RDM.
We added the new view by “All Datasets” which shows unified information about datasets from the DASD farm, Tapes (DFSMSrmm or CA1), and HSM (Migrated and backed up).
To enable this new feature, you will need to open the RDM view by “All Datasets”, press on “Collection control” and define the USS directory which is required for persistence collection.
After collection completion you can look for data by defining data in 2 various modes:
- Basic Mode: you can specify attributes and values to filter
- Advanced Mode: free-form filter input that allows you to define a filter with any complexity.
Since data are unified from various data sources for your convenience you can create your own “column set” which could be used to overview specific attributes of datasets.
You can review the summary of data according to the specified filter or export these data to the USS file.
User ID mapping in the Storage Toolkit actions
With the new APAR, you can map TEP user IDs or LDAP users to the RACF when you submit jobs or commands in the TEP or RDM. For mapping, you just need to create a new member KGLUMAP member in the RKANPARU data set. Thus, you can map each user or user’s mask to the specific RACF users.
More details about this feature could be found by link: https://www.ibm.com/docs/en/osd?topic=commands-setting-up-user-id-mapping-capability
Saved JCL Job Cards in the RDM
With this APAR any RDM user can save the JCL Job Card for any submitted command or job. Thus, each user does not need to modify the Job Card before every submission, but just use the previously saved one.
Saved user’s actions in the RDM
In the RDM you can save your command or job and reuse it for any selected datasets. As a result, if you have some JCL which you need to submit for some datasets quite often – you can create a template and apply it for selected datasets in just a few clicks.
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