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How To Reduce Mainframe MIPS with Confluent
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Mainframes have been a fundamental part of the IT infrastructures of many organizations for decades, and with good reason. Able to process extremely large volumes of transactional data in a secure and reliable way, they’ve formed the backbone of numerous business-critical applications, especially across highly-regulated sectors.
Despite playing such an important role, however, mainframes have posed a number of challenges for organizations. Aside from being difficult to maintain and integrate with newer technologies, mainframes have proven increasingly expensive to operate, owing mostly to increased demand put on them.
In this paper, we explore a central component of mainframe operating cost – MIPS (Million of Instructions per Second) – and how data streaming with Confluent can help to significantly reduce it.
You’ll learn:
- What data streaming is and how it relates to mainframe computing.
- How data streaming with Confluent can reduce MIPS and CHINIT (Channel Initiator) costs, with example architectures.
- How specific organizations across banking and financial services have integrated their mainframes with Confluent in order to lower operational costs.
