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Mainframe Consolidation with Private Clouds (Legacy Modernization Pattern)

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Mainframes have been part of IT landscape of many a  large enterprises due to the critical business processing that is taken care by Mainframes,  replacement of Mainframe is not an solution for most organizations, However enterprises have been trying to reduce the  load on  mainframe and consolidate them.

Organizations will go for Private  Cloud among other things like Workload optimization and dynamic infrastructure , so in that context utilizing Private Clouds  for Mainframe Consolidation  will be a very viable and cost effective option.

Typical Mainframe Workload

  • Large amounts of data storage typically in TB (Terra Bytes)
  • Most of the data is sourced using the interfaces from external systems
  • Batch jobs which are sequence of job steps tied using JCL (Job Control Language) perform all the business logic processing and leave the databases in a consistent state at the end of it
  • Data entry screens do exist in Mainframe (like CICS, IMS/DC) but their usage is going down and web interfaces on the rise
  • Lot of reporting needs of the legacy data using the modernized reporting platforms
  • Work load splits across multiple sub systems and servers resulting in less utilization of over all computing resources
  • High cost with respect to capital expenditure and operational expenditure

Reducing the Mainframe Processing & Shifting The Workload to Cloud
As evident,  mainframes have, over the years, been doing several business-critical  business logic and it is not easy to replace and retire them completely.

However, the batch nature of the mainframe enables movement of  reporting of the mainframe data to thecloud so that much of the work load can be migrated to private clouds resulting in  much needed Mainframe consolidation to reduce the capital expenditure and operational expenditure.

Cloud Cache Pattern to Reduce Mainframe Work Loads
The scalability and performance of Mainframes can be matched by a  huge array of Virtual machines on the Cloud.

The data from the Mainframe can be moved to the massive parallel virtual storage devices within the Cloud.

The Cloud Virtualized Platform will act as a CACHE for the Mainframe data to support reporting from a PaaS  or SaaS enabled application as part of the private cloud.

All the reporting  will be done from the Cloud platform rather than the Mainframe.

When ever needed the Cloud data residing in the virtualized storage can be refreshed from Mainframe. For example if there is a Billing database on the Mainframe then the data can be refreshed to the Cloud based on the billing cycle batch run.

The following diagram gives how the Cloud CACHE works in migrating the Mainframe work load:

Summary

  • Cloud platforms satisfy many of the guiding principles of mainframe computing such as stability, reliability, ability to split larger work load, accounting per usage and multi tenancy
  • Migrating much of the processing of mainframes to Private Clouds lead to a larger Mainframe consolidation and the organizations can invest on the reduction in capital expenditure towards Cloud infrastructure.

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