Setting the Record Straight on Mainframe Security and Compliance
Last November, Syncsort announced the results of an industry survey that confirmed the mainframe’s role at center stage in large corporations around the world. The findings also highlighted how the mainframe has evolved to meet the growing need to process and analyze large volumes of Big Data. The survey also uncovered several other key findings about the mainframe’s use in large businesses, where it still houses the lion’s share of corporate data, is the system of record, and is now at the heart of their Big Data strategies.
Data from the survey also shed light on why mainframe vendors cannot be complacent about mainframe security.
In a recently published column in Enterprise Executive, “Setting the Record Straight on Mainframe Security and Compliance,” Harvey Tessler, a Syncsort founder who has decades of product and market knowledge in IBM mainframe, leveraged survey data to clarify some of the questions about how secure, reliable, and compliant the mainframe is, given endless security threats and cyber-attacks from within and outside businesses, as well as escalating regulatory requirements.
An excerpt of Harvey’s column follows below:
Not surprisingly, in a recent “State of the Mainframe” study, polling 187 respondents including IT Strategic Planners, Directors/Managers, Architects and Administrators at Global Enterprises with $1B or more in annual revenues, Syncsort found that 82.9 and 83.4 percent of respondents cited security and availability as key strengths of the mainframe. Even fortresses can be vulnerable if repeatedly attacked — mainframes are not impregnable.
Please rank security of critical enterprise data as a key strength of the mainframe at your company on a scale of 1 being very important to 5 not important.
This isn’t a mainframe only issue — IT departments need to ensure that their organizations have the security measures in place to protect business data in an increasingly decentralized, Big Iron to Big Data world, with higher and higher volumes of diverse data types coming from multiple data sources, including mainframe, data warehouses, open systems, mobile devices and the IoT. They also have to comply with a number of industry and federal regulations (PCI DSS, FISMA, Sarbanes-Oxley, HIPAA and HITECH) designed to keep sensitive customer information safe.
Organizations are also looking to leverage advanced analytics on Big Data and analytics platforms. In the “State of the Mainframe” study, when asked to rank their use of the for transferring Big Iron data to big data and analytics platforms, respondents showed a high level of interest (see figure 2)
In fact, in recent commentary on the “State of the Mainframe” study, Denny Yost, associate publisher and editor-in-chief of Enterprise Systems Media, said, “The survey demonstrates that many big companies are using mainframe as the back-end, transaction hub for their Big Data strategies, grappling with the same data cost and management challenges they used to tackle before, but applying it to more complex use cases with more dauntingly large and diverse amounts of data.”
Please rank your use of the mainframe for transferring data to big data and analytics platforms on a scale of 1 being very important to 5 not important.
Rising to the challenge, IBM continues to reinvent the mainframe for modern computing needs. With the model z13, for example, announced in January 2015, over two billion transactions per day can be crunched, and it “eats mobile application data for lunch.” In the z13, IBM also focused on directly integrating security measures, including embedded cryptography. Big Blue says the new entry level z13 offers encryption at twice the speed as previous mid-range systems, without compromising performance. Still, of course, there is more to be done to fortify mainframe security and compliance, and software providers need to ante up.
And it’s not just about mainframe anymore.
Recent customer use cases indicate that Big Iron’s evolving future will center on processing and analyzing exploding data volumes, and working together with legacy and new computing platforms and data delivery technologies, all to support data-driven decision-making for the business. This trend reflects the mainframe’s ability to be that hub for emerging Big Data analytics platforms, mobile applications and the IoT.