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Tag Archives: mainframe

5 Steps to Mainframe Modernization with a Big Fast Data Fabric

For growth initiatives, many companies are looking to innovate by ramping analytical, mobile, social, big data, and cloud initiatives. For example, GE is one growth-oriented company and just announced heavy investment in the Industrial Internet with GoPivotal. One area of concern to many well-established businesses is what to do with their mainframe powered applications. Mainframes are expensive to run, but the applications that run off of them are typically very important and the business can not afford to risk downtime or any degradation in service.  So, until now the idea of modernizing a mainframe application has often faced major roadblocks.

There are ways to preserve the mainframe and improve application performance, reliability and even usability.  As one of the world’s largest banks sees, big, fast data grids can provide an incremental approach to mainframe modernization and reduce risk, lower operational costs, increase data processing performance, and provide innovative analytics capabilities for the business—all based on the same types of cloud computing technologies that power internet powerhouses and financial trading markets. Continue reading

Banks Are Breaking Away From Mainframes to Big, Fast Data Grids

The world’s largest banks have historically relied on mainframes to manage all their transactions and the related cash and profit. In mainframe terms, hundreds of thousands of MIPS are used to keep the mainframe running these transactions, and the cost per MIP can make mainframes extremely expensive to operate. For example, Sears was seeing the overall cost per MIP at $3000-$7000 per year and didn’t see that as a cost-effective way to compete with Amazon. While the price of MIPS has continued to improve, mainframes can also face pure capacity issues.

In today’s world of financial regulations, risk, and compliance, the entire history of all transactions must be captured, stored, and available to report on or search both immediately and over time. This way, banks can meet audit requirements and allow for scenarios like a customer service call that results in an agent search for the transaction history leading up to a customer’s current account balance. The volume of information created across checking, savings, credit card, insurance, and other financial products is tremendous—it’s large enough to bring a mainframe to its knees. Continue reading