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Reducing Data Center Infrastructure Costs with Software-Defined Storage


The IT industry is in the midst of a storage cost crisis. This is largely due to the pace of change and innovation in enterprise computing during the last decade, which has created enormous pressure on the underlying data storage infrastructure. In the last few years alone, there has been an average enterprise data growth of 569%, with an evolution of organizations managing an average of 1.45 PB of data in 2016 to 9.7 PB in 2018. To keep up with this change, IT teams have rapidly expanded storage capacity, added expensive new storage arrays to their environment, and deployed a range of disparate point solutions.

However, despite representing a significant percentage of IT budgets, the storage layer has remained particularly problematic and continues to be the root of many IT challenges, including the inability to keep up with rapid data growth rates, vendor lock-in, lack of interoperability-and most significantly, increasing hardware costs. Given that IT teams cannot continue to simply outspend the problem, it has become clear that a more fundamental solution is required to address the cost and complexity issues of the storage infrastructure.

Software-Defined Storage Emerges as a Key Solution

As IT architects and decision-makers look for ways to effectively address this challenge, software-defined storage (SDS) is increasingly being recognized as a viable solution for the short and long term. The potential economic impact of software-defined storage is best understood in the context of the complexity and cost crisis that characterizes most enterprise IT environments today, including:

  • Hardware and Software Costs: The enterprise storage environment often contains many specialized products, built with proprietary technology. To meet all of the enterprise requirements, while accounting for both capacity growth of existing workloads and the addition of new workloads, IT teams have had to devote significant portions of their annual budget to these capital expenditures (CAPEX). Year over year growth in data, applications supported, number of users, and number of sites all drive further CAPEX spending-and that's just to maintain the status quo.
  • Operating Expenses (OPEX) and the Inability to Innovate: Infrastructure complexity also consumes significant manpower. This complexity increases with variables including storage arrays, vendors, locations, applications, and operating systems. The volume of activities required to keep the existing infrastructure available and working as expected means that the majority of the IT staff's time goes to simply maintaining the infrastructure, leaving a much smaller percentage of time to dedicate toward innovation or new programs that can enable growth and differentiation for the business.

Users of DataCore software-defined storage typically experience significant OPEX and CAPEX savings, yielding a superior total cost of ownership (TCO) due to the strength of its architecture, including a number of innovations that directly reduce the cost of a robust storage environment. With DataCore, customers can avoid or reduce new storage purchases by extending the life of existing storage, purchase less extensive storage without sacrificing performance or functionality, and can make more efficient use of existing capacity. Moreover, DataCore software-defined storage drives significant operational savings based on reduced complexity, improved uptime, lower maintenance cost, lower data center costs, and other indirect factors.

Conducting a TCO evaluation of all potential solutions is an important step in making any IT purchasing decision. This is particularly true for data storage, one of the most critical pieces of the overall data center infrastructure. If you are interested in learning more about how software-defined storage can help reduce data center infrastructure costs, including a table to help you structure your TCO analysis comparison, download this white paper.

Published Friday, July 12, 2019 1:41 PM by David Marshall
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