This guide introduces MON-PRECALL (Predictive Recall), a specialized component of the Storage Control Center (SCC) suite that optimizes batch processing by proactively recalling migrated datasets before they're needed. Learn how this solution analyzes job scheduler information to identify and recall migrated datasets during system low-activity periods, eliminating production delays and reducing overall batch window duration. Intended for storage administrators, batch operations managers, and system programmers responsible for HSM environments who need to maximize system performance and minimize the impact of data recalls on critical production workloads. This publication explains how to configure, implement, and manage the MON-PRECALL solution to achieve more predictable batch processing times.
The Storage Control Center (SCC) is an integrated family of storage management prod- ucts that allows you to get the most out of your storage dollars. The SCC products improve disk space utilization, prevent storage-related errors, allow installations to monitor the storage subsystem in real-time, and proactively control the use of storage space.
This manual covers the product verification, configuration, and use of MON-PRECALL. The installation procedures for all the SCC products can be found in the Product Installa- tion Guide. The next chapter will highlight the product’s capabilities and components.
Easy to Install: The SCC product suite has been designed to work with your current environment; addi- tional hardware and software upgrades are NOT required. Since the products are dynami- cally installed, IPL is NOT required.
Documentation: The SCC Monitor documentation can be found in the following manuals:
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MON-SNAPSHOT: Snapshot Monitor using Batch and Started Tasks
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MON-RTM Real-Time Monitor for Storage Events
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MON-EXPLORER Explorer PC GUI Application
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MON-IPHONE The Monitor iPhone Application
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MON-ISPF Monitor ISPF Setup and Applications
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MON-JCLQA JCL Validation and Quality Assurance
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MON-PRECALL Predictive Recall for Migrated Datasets