Alan Seal

By: Alan Seal on August 22nd, 2019

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5 Exciting Data Storage Trends Shaping the Data Center Industry

Data Center

New trends in data storage are forcing companies to reassess how they store their data and applications. In some cases, they simply face the challenge of adopting new technology. Some of these data storage trends, however, are far more significant and could lead many of them to completely rethink how they approach their network infrastructure. For colocation customers, data center storage trends are particularly important to their long-term storage technology strategy.

5 Exciting Data Storage Trends Shaping the Data Center Industry

1. Data Accessibility and Security

The global demands for the availability and protection of data have never been greater. No longer can organizations rest easy knowing that their mission-critical data is safely stored on servers in a highly secure mainframe. Today’s enterprise applications are spread across sprawling networks that utilize multiple vendors and hardware configurations. The consequences of mishandling that data can be severe and will certainly increase if more countries follow the lead of the European Union’s sweeping General Data Protection Regulations (GDPR). Organizations must utilize encryption and firewall technology in conjunction with logical security access procedures to ensure that the integrity of their data is maintained. At the same time, they are under intense pressure from end users and customers to make the services that rely on that data available as much as possible. Data centers can help companies to meet these conflicting demands, but the concerns over data breaches and downtime will continue to loom over many data storage technology trends.

2. Artificial Intelligence for IT Operations (AIOps)

Today’s data centers offer a broad range of storage options. Between multiple types of colocated hardware (such as hard disks and tape drives) and a multitude of cloud storage solutions, organizations could potentially have data and applications spread across multiple locations within their network infrastructure. As additional storage is provisioned to conduct software testing and development, the burden of managing all of that storage capacity can become overwhelming. That’s why many companies are responding to trends for data storage by investing in artificial intelligence and machine learning to better understand and optimize their enterprise storage solutions. With AIOps in place, it will be possible to know where data is located at any time, when it needs to be moved, and how that constant shuffling will impact bandwidth and storage capacity costs.

3. Rack Scale Design (RSD)

The push to streamline and simplify data storage has caused many organizations to turn to the same virtualization technologies driving the move to software defined data centers (SDDCs). An RSD strategy involves tying the storage, memory, and compute capacity of every individual rack in a cabinet together with an interconnection. Once connected, these resources can be configured into a virtual server that functions as a private cloud environment. New virtualization software even makes it possible to connect different hardware types and configurations. The latest generation of PCIe interconnects also facilitates higher bandwidth connections between virtualized resources, which greatly improves speed and performance.

4. Storage-Based Processing

As more and more data is gathered on the edge of networks by intelligent Internet of Things (IoT) devices, organizations are turning to edge computing architecture to reduce latency and increase flexibility. With intelligent storage strategies, network engineers can combine virtualization techniques and machine learning to synchronize memory at the network edge into a vast array of virtual machines capable of processing hundreds of terabytes of data without having to move that data across the network. This would significantly reduce latency for big data applications and ease the bandwidth requirements on both networks and data centers. Since more data can be managed on the edge, especially if machine learning techniques could help devices manage information autonomously, the volume of data moving through the facility’s routers would be greatly reduced, allowing the data center to improve performance in other areas.

5. High-Capacity Disk Drives

Although solid state drives (SSDs) are fast becoming more affordable and commonplace, hard disk drives (HDDs) aren’t going down without a fight. Many companies are developing technologies to overcome the physical limitations of traditional disk drive technology to improve both storage capacity and speed. Many cloud data centers are deploying drives that use helium to reduce drag and turbulence on disks, allowing them to fit more disks into the drive and spin them faster. Shingled magnetic recording drives can pack much more data onto a disk by reducing the space between tracks and overlapping them like shingles laid down on roof. Heat-assisted magnetic recording drives use lasers or microwaves to achieve a greater density when writing data to the disk. These technologies are poised to delay the widespread adoption of SSDs, which still have significant cost limitations compared to even the most sophisticated HDDs.

As one of the oldest challenges facing computing technology infrastructure, data storage is undergoing a period of rapid change that makes it difficult for companies to keep up with the latest data storage market trends. By identifying which data storage trends present the greatest opportunities for their business, organizations can adopt the right technologies for their data center infrastructure to facilitate growth and sustainable success.

 
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About Alan Seal

Alan Seal is the VP of Engineering at vXchnge. Alan is responsible for managing teams in IT support and infrastructure, app development, QA, and ERP business systems.

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