The Disruptive Data Center Technologies of 2016

2015 will go down in history as one of widespread change to enterprise information technology. Many new technologies either arrived on the scene or demonstrated their mettle and brought disruption to the enterprise, creating a landslide of change that will continue into 2016 and beyond.

Software Defined Networking (and Everything Else)

Although hardware abstraction has been around for some time and the majority of enterprises already use some form of virtualization, 2015 brought forth a plethora of new or enhanced ways to transform the way that data centers are designed, applications provisioned and networks architected. Technologies such as Software Defined Networking (SDN), Software Defined Storage (SDS), Software Defined Infrastructure (SDI) and Software Defined Data Center (SDDC) all came to light with enhanced availability, increased vendor support and ramped-up adoption. Arguably, no other class of technologies has had as much impact on enterprise IT over the last year, paving the way for the adoption of open systems and rendering vendor lock in a thing of the past.

Hyper Convergence

For 2015, the path to hyper convergence was paved by the giants of the tech industry, with companies such as Facebook, Google and Amazon all laying out the rules for what it should be. With the path laid out, more and more enterprises were able to delve into the world of hyper convergence and realize increased ROI and reduced TCO. Hyper convergence brought with it the concept of open hardware paired with open software that could leverage software definition. That in turn allows enterprises to build powerful, complex networks based upon open standards, once again addressing the specter of vendor lock-in, while also bringing agility to the forefront of enterprise IT operations. For 2016, expect Hyper Convergence to be the new world order of the data center.

Internet of Things (IoT)

Many have predicted that the storm of connected devices would remain on the horizon for years to come as enterprises figured out how to manage and control those devices. However, 2015 saw a massive uptick in the adoption of IoT technologies, simply because connected sensors, connected devices, and connected components all bought measurable value to enterprises of any size. That said, IoT did fall short where others predicted that it would be big, in the connected home and wearables market. Those same pundits failed to predict the speed with which businesses would leverage the technology. In 2015, sensors used for data gathering and analytics were quickly adopted and added to networks, giving the rise to IoT management products and associated security products. IoT became the clarion call for security, production, delivery and product line engineering concepts, and started to feed massive databases with all sorts of structured and unstructured data. Cisco’s $1.4 billion acquisition of IoT vendor Jasper Technologies demonstrates the perceived value in the Internet of Things, which will continue to dominate the conversation in 2016.

Big Data Analytics

Big Data has long been the darling of the largest of enterprises, such as those in the financial, retail and insurance markets. However, 2015 bought new options to the table, enabling small and medium enterprises to play the big data game. Although those businesses deal with data sets a fraction of the size of those that huge businesses handle, the concept of identifying patterns and mining correlations between data sets remains applicable. 2015 saw the rise of a plethora of services and vendors that utilize cloud-delivered analysis systems to place big data in the hands of the little guy. What’s more, publicly available data sets have become more accessible to smaller organizations, allowing them to incorporate GIS, census and other data into their algorithms to uncover relationships between data elements and deliver enhanced insight into the business process. For 2016, expect Big Data as a service to become more commonplace and accessible by smaller enterprises.

The Rise of the Container

Thanks to Docker (and many others), the ideology of containers has moved from the world of Unix into the mainstream. In essence, a Docker container can house a virtualized representation of an application and allow that application to be moved with ease across different servers. In other words, Docker is a tool that can package an application and its dependencies in a virtual container that can run on any Linux server. 2015 saw more and more originations moving to containers instead of virtual machines, meaning that a virtual server could be created to house multiple containers, each isolated from the other and completely portable. With companies such as Microsoft adopting the concept of containerization natively in their server OSes, expect 2016 to show more growth in the container market.

Machine Learning (ML) / Artificial Intelligence (AI)

2015 gave us the smarter machine (and/or application), thanks to improvements in ML and AI algorithms.  ML has made inroads into many areas, ranging from data analytics to predictive systems. However, for many businesses, ML’s biggest inroads have been into the realm of security. “Smart” security appliances can now learn user and application behavior and then create reputations. That same type of ideology can be incorporated into data analytics, IoT monitoring and countless other applications. A “smart” application can learn and evolve to offer predictions as well as suggest improvements to processes. 2016 will see more of ML/AI technologies take root in everything from network optimization to hardware failure predictions.

2015 was a year of disruption for the enterprise. The establishment and adoption of new technologies should drive advances for years to come and perhaps cause enterprises to rethink how IT is deployed, managed and maintained. The changes set to take place in 2016 look nothing short of transformative.

Latest Articles

Follow Us On Social Media

Explore More