The mainframe is built for complex, high-volume, data-intensive workloads. It is essentially a collection of specialized components, each of which supplies its own resources—controllers, power supplies, self-diagnostics, cooling, and so on. These in-box components communicate with each other efficiently via backplanes and specialized high-speed channels. Logical partitions (LPARs) each run their own OS, with flexible sharing of memory and CPU resources, and support for clustering.

Today’s mainframes support all of the latest computing technology trends. Virtualization can be implemented either via z/VM (IBM’s hypervisor technology) or KVM, a Linux-native hypervisor.  As of August 2017, Docker Enterprise Edition 17.06 supports containerized apps on mainframes running Linux, with no need to modify code. Launched in January 2015 after five years of development, IBM’s z13 Systems mainframe was specifically designed to handle billions of mobile transactions from a wide range of mobile devices. It also supports big data analytics and cloud interfaces. In July 2017, the z14 Systems mainframe appeared on the market, with all of the features introduced by the z13 plus new encryptiontechnology based on keys locked into cryptographic hardware, as well as enhanced support for machine learning analytics. With a 10-core CPU chip, the z14 is also IBM’s fastest ever mainframe.

It should not be surprising, therefore, that in a recent global survey of CIOs, 88% expect their mainframes to continue to be a key business asset over the next decade, and 81% reported that their mainframes continue to evolve—running new and different workloads.

There are platforms emerging to help mainframe managers make the best of both worlds, such as:

IBM Cloud’s Rocket Mainframe Data Service, which uses data virtualization technology to allow developers to easily incorporate data from z Systems into cloud or mobile applications.
Syncsort’s Ironstream that makes it less complex and less costly to bring operational and security log data from the mainframe into Splunk Enterprise and Splunk Cloud.
Model 9’s z/OS Backup, Archive and Recovery software , which provides a single dashboard for managing an enterprise’s backup and data archival policies—seamlessly storing and recovering mainframe data directly to and from any storage system, whether on-premise or cloud. Model 9 is the only platform that supports full mainframe system recovery from cloud-based data.
This is all good news for those large enterprises that are unlikely to forego the mighty mainframe as their platform of choice for running business- and mission-critical applications.

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