When an organization performs a data center assessment, they should do so with full knowledge of the various technology trends that have impacted the way modern data centers are designed and managed. Data center tech is an important differentiator for colocation facilities, which offer their customers data center technology that is far beyond the reach of many small or even medium-sized, companies. Understanding how data center technology trends can benefit their customers is vital to choosing the best colocation partner.
Data center storage is one of the most pressing concerns facing today’s companies. The US alone generates over three million gigabytes of data every minute, and the increasing reliance on big data analysis makes data storage more important than ever. This pressure has led many companies to invest in hard drive technology, increasing the performance of existing storage formats while working to develop new formats. For many years, hard disk drives (HDDs) were the go-to solution for data storage thanks to their reliability and low cost. Unfortunately, this technology has largely reached its performance limits. Solid state drives (SSDs) have yet to reach price parity HDDs, but flash memory has made significant strides in both capacity and access speed. As more organizations turn to SSDs for improved performance, data centers will also be able to use the technology to help colocation customers store and access data more effectively.
In an effort to reduce infrastructure burdens, many data centers and managed service providers (MSPs) have shifted to a software defined data center (SDDC) service model that utilizes virtualization technologies to abstract processing hardware into software form. Rather than inefficiently allocating one server to each user, virtualization allows providers to segment servers in such a way that multiple users can be housed on a single server. The same virtualization techniques also allow providers to distribute workloads across multiple servers, providing SDDC customers convenient scalability. The SDDC model effectively turns a data center into a cloud provider, parceling out the data floor’s processing and storage power on an “as needed” basis. Virtualization also helps to improve efficiency, ensuring that computing resources aren’t being underutilized.
Although many organizations were early adopters of public cloud technology, the lack of control and pricing challenges has caused many of them to abandon purely cloud-based solutions. At the same time, private infrastructure brings its own set of problems. Increasingly, companies are turning to hybrid cloud architecture to provide them with the control and security they expect from a private network as well as the expansive power of public cloud computing services. Hybrid clouds allow companies to store and manage valuable data assets on secure private servers and then shift them into a public cloud for various processing applications. Given the importance of big data analytics in today’s economy, having a network that offers secure and easy access to cloud-based service platforms is vital for business success.
The rapid proliferation of Internet of Things (IoT) devices has shifted the conventional architecture of many networks. Rather than forcing data to make the long journey back to a centralized server for processing, companies are keeping it closer to where it was generated on the network edge. Known as edge computing, this data center architecture uses the processing power of devices on the network edge to resolve requests and actions rather than relying on centralized processing resources. The reorientation greatly reduces latency, which translates to faster performance for IoT devices and less service interruption for end users, whether they’re trying to access cloud resources or stream content. Edge data centers positioned in pivotal growth markets have helped organizations to extend their edge computing networks, servicing local users and reducing strain on distant hyperscale facilities. With IoT edge devices gathering more and more information from users, edge computing strategies will help data centers better manage this data by only sending some of it back to the network’s central servers.
Perhaps no development has had a greater impact on data center efficiency than artificial intelligence (AI) programs that monitor and adjust performance over time. Predictive analytics can use historical operations data to identify problem areas and draw connections between various processes and energy usage. The most dramatic example of this was Google’s decision to hand over control of a data center’s cooling infrastructure to an AI program, which resulted in a 40 percent reduction in cooling costs. With AI applications, facility managers have a better idea of when data center components will need to be replaced or how a minor change in equipment deployment could impact energy costs over a period of time.
Data center technology has thoroughly transformed the modern colocation facility into a cutting-edge IT solution that can meet the needs of any organization, no matter their size or scale. As companies shift away from inefficient and expensive on-premises solutions and repatriate data from public cloud environments, colocation data centers will give them the storage solutions and network architectures they need to take their businesses into the future.