Further Liberation of the Data Center

By Brian Cox
| min

With the rise of open systems in the 1980s, IBM helped unfurl new freedom in datacenter computing. Moving beyond the proprietary silos of prior generation minicomputers and mainframes, IBM pioneered the open systems of UNIX interoperability with POSIX-compliant software stacks. This enabled much greater ease for customers in transitioning between different vendors’ UNIX operating systems. In 2001 IBM, unveiled Linux on System p and other platforms further democratizing availability of the advanced RISC-based Power architecture. Now, we are working with IBM to take this liberation further with a plan to offer the Nutanix Enterprise Cloud Platform software on IBM Power Systems. With the planned design, the ease of the public cloud will be available to IBM customers in their own datacenters.

With an Enterprise Cloud Platform, IBM customers will be able to tap scalability, ease of infrastructure provisioning and management inspired by Google, Microsoft Azure and Amazon Web Services, but provided on-premises. The same simplicity and flexibility provided by Nutanix to over 5000 customers in over 100 countries will be available to IBM’s global IT customers.

The IBM-Nutanix hyperconverged system will focus on established opportunities such as IBM WebSphere Application Server (WAS) and open source databases (OSDBMS), as well as emerging high performance, predictive analytics workloads which IBM refers to as Cognitive Computing.

WAS optimizes application infrastructure to reduce costs with hybrid cloud capabilities. As a development framework, WAS is used to create cloud-native and web-based apps and microservices and deploy and manage apps across any cloud and any container service.

Furthermore, according to IBM, “By 2018, more than 70% of new in-house applications will be developed on an OSDBMS, and 50% of existing commercial RDBMS instances will have been converted.” ( Names you are likely to hear include EnterpriseDB on the relational DBMS side and MongoDB, Neo4J, and Redis Labs on the NoSQL side.

As an emerging workload, Cognitive Computing is defined as “. . . the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance. Cognitive computing is used in numerous artificial intelligence (AI) applications, including expert systems, natural language programming, neural networks, robotics and virtual reality.” (

This is very much in line with the Nutanix approach to unleash computers to do what they do best — simplifying tasks at large scale. IBM customers do this by using analytics to capture and mine disparate data in massive volumes to detect patterns and offer recommendations which are beyond the scope of what a single human mind or even a team of people could do in a timely manner. Basically, automate processes to free humans from dreary tasks to focus on more value-add work. As computing continues to evolve to infer associations even with incomplete data, they must make the leap to more human-like thought (aka Cognitive Computing). Similarly, Nutanix is harnessing this type of inference computing, what Nutanix Chief Architect Binny Gill has been referring to as Intentful Machines (

IBM’s embrace of the Nutanix Enterprise Cloud Platform is further validation that hyperconverged infrastructure and hybrid cloud is now a mainstream IT architecture. New research from the Enterprise Strategy Group point out the following:

  • 87% of HCI users feel that deploying HCI has made IT more agile (25% say significantly more agile)
  • 73% of respondents believe that HCI plays a role in positioning them to be more cloudlike and deliver IT as a service: 44% believe HCI give them the best chance to be more cloudlike and offer IT as a service.

(ESG Research, Converged & Hyperconverged Infrastructure Trends Survey, May 2017)

When Cognitive Computing is combined with the simplification and scale of an Enterprise Cloud, customers achieve what Enterprise Strategy Group Senior Analyst Terri McClure calls a “Cognitive Cloud.” In other words, this collaboration between IBM and Nutanix brings the power of predictive analytics, along with the ease of modular scalability and streamlined infrastructure management of hyperconvergence to make deploying Cognitive Computing an achievable reality.

IBM customers will be able to marry these capabilities in OSDBMS, WAS and Cognitive Computing with mainstream commercial applications in ERP, CRM, VDI and Unified Communications, which Nutanix has proven out in thousands of deployments around the globe.

These Nutanix customers leverage the Acropolis common data and compute fabric, including the native AHV hypervisor. And with Nutanix’s Prism Central, clusters can all be managed from a central console – regardless whether the cluster is running the Power or x86 architecture.

This commonality and this ease of use is what makes Nutanix’s underlying infrastructure invisible, and enables customers to focus on the applications and services which power their business. In collaboration with Nutanix, IBM is once again planning to liberate the datacenter.

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Forward-Looking Statements
This blog includes forward-looking statements concerning our plans and expectations relating to our relationship with IBM and the deployment of our software on, and interoperability of our software with, IBM Power Systems. These forward-looking statements are not historical facts, and instead are based on our current expectations, estimates, opinions and beliefs. The accuracy of such forward-looking statements depends upon future events, and involves risks, uncertainties and other factors beyond our control that may cause these statements to be inaccurate and cause our actual results, performance or achievements to differ materially and adversely from those anticipated or implied by such statements, including, among others: failure to develop, or unexpected difficulties or delays in developing, new product features or technology on a timely or cost-effective basis; the introduction, or acceleration of adoption of, competing solutions, including public cloud infrastructure; a shift in industry or competitive dynamics or customer demand; and other risks detailed in our quarterly report on Form 10-Q for the fiscal quarter ended January 31, 2017, filed with the Securities and Exchange Commission. These forward-looking statements speak only as of the date of this blog and, except as required by law, we assume no obligation to update forward-looking statements to reflect actual results or subsequent events or circumstances.