Edge computing has been around for the better part of three decades, but it only entered the mainstream technology conversation a few years ago when it became a key enabler of Internet of Things (IoT) projects. While it remains essential for facilitating IoT initiatives, the edge model now has far more broad appeal with important use cases in practically every industry vertical.
Organizations in healthcare, manufacturing, retail, financial services, agriculture, energy and more have all found ways to leverage the computing model. Three-quarters of organizations report they plan to increase spending on edge initiatives over the next two years, according to a new study from IDC.
Why the Edge Matters
Several factors are driving increased activity at the edge. By pushing data processing closer to data sources in order to minimize latency and preserve bandwidth, the edge model minimizes numerous network bottlenecks and allows users and devices to work with near-real-time data. That’s critical for supporting processing-intensive artificial intelligence (AI) and machine learning (ML) applications that are performing algorithmic analyses of larger and larger data sets.
Additionally, the edge’s short-hop data transmissions create speed and performance gains that have been invaluable for increasingly distributed workforces. Plus, edge computing improves overall network performance by reducing the volume of data moving through on-premises data centers.
While large enterprises have been quick to leverage such performance gains, small to midsized businesses (SMBs) are also using edge solutions to achieve important operational improvements. According to a new study from Techaisle, SMBs say edge deployments have helped them improve operations monitoring, increase business agility, reduce costs, increase productivity and automation, develop new products and services, and increase revenue from existing products and services.
Key Challenges
Those benefits don’t come easily, however. As with any major technology infrastructure initiative, edge computing presents a variety of challenges. Chief among them is the inherent complexity that comes with highly dispersed IT environments. With data, devices, storage and processing power distributed across a network of remote micro data centers that have little or no local IT staff, edge management becomes a highly complex process.
Security is another challenge. Placing key resources outside the perimeter of a centralized data center greatly expands your attack surface — particularly since many edge computing devices have built-in Internet connectivity. Additionally, small edge devices typically lack many of the built-in protections you’d expect to see in traditional data center gear. That makes them vulnerable to a range of threats, including malware injection, ransomware, distributed denial of service (DDoS) attacks, data theft and data leaks.
A lack of in-house IT talent is another barrier to effective edge adoption. Edge systems require people with a deep understanding of system design and how edge devices, software resources and data center infrastructure are tied together. They may also require expertise in cloud services, data exchange formats, network communication protocols and database management. Typically, only the largest enterprise organizations can afford to have such specialized expertise on staff.
Verteks Can Help
These challenges are not insurmountable, however. Even SMBs that have a single “IT guy” on staff can gain the benefits of edge computing with help from a managed services provider (MSP) with demonstrated networking expertise.
Verteks, for example, has decades of experience in the design, installation and provisioning of distributed networking solutions. We would welcome the opportunity to show you how our managed network services can help you implement an edge architecture that can resolve many of your most critical networking challenges and facilitate the use of new applications and services.
