In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical.
These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most companies have strategic plans for deploying clouds—on- or off-premises—to run distributed Java applications and databases. However, IT infrastructures that are underutilized, vulnerable, and complex pose a problem by becoming more difficult and expensive to maintain at precisely the moment that organizations are under pressure to increase operating efficiencies, drive down costs, and deliver innovative technologies that can generate new revenue streams.