Edge computing opens organizations up to some security risks, but these can be mitigated with proper planning.
With the explosive growth of IoT devices and the accompanying flow of data, businesses are under more pressure than ever to find ways to reduce latency and improve productivity. That’s why edge computing, the technology that brings computing and data storage closer to the devices that generate the data, continues to grow in popularity.
According to a recent a study by Research and MarketsThe global computer peripherals market is expected to grow from $11.24 billion in 2022 to $155.9 billion by 2030, at a CAGR of 38.9%.
SEE: Don’t Curb Your Enthusiasm: Trends and Challenges in Peripheral Computing (TechRepublic)
But as with any new technology, there are risks inherent in embracing edge computing.
The risks of peripheral computing
Security issues around the edge
One of the most significant risks of edge computing is security. Adoptive parents are aware of this, as shown in a recent AT&T study which sampled 1,500 companies. The survey found that companies expect to spend between 11% and 20% of their final investment on security.
Security is a major risk for several reasons:
- Data handled outside the traditional corporate firewall is more vulnerable to attack.
- Edge devices are often deployed in uncontrolled environments, so they can be subject to physical tampering or damage.
- With more and more devices storing data at the edge of the network, virtual security risks are also increasing: For example, deploying hundreds of edge computing devices creates a larger attack surface and opens the door to security breaches such as DDoS attacks.
- Identifying and deploying endpoints also creates new challenges for security teams. Edge devices are often distributed over a wide geographic area, making it difficult to physically secure them. Because endpoint devices are often connected to other devices and systems, they can provide attackers with a way to gain access to an organization’s network if they are not adequately secured.
Therefore, there must be appropriate physical, network and cloud security measures, such as Secure Access Service Edge, to protect data processed at the edge. Otherwise, the risk of a security breach will outweigh the benefits of implementing edge computing.
The cost of final calculations
Cost is one of the main considerations when evaluating the viability of edge computing. While the potential benefits of deploying an edge network are significant, the costs associated with managing and maintaining an edge environment can quickly become prohibitive. This is especially true if the final implementation is not carefully planned, executed and managed. For example, as new IoT endpoints proliferate, effectively managing them from a centralized location can become increasingly complex.
In addition, because edge computing requires hardware and software, businesses must carefully consider the total cost of ownership before implementing a final solution. Hardware costs can be significant, as companies often need to buy new devices or upgrade existing ones to support edge computing. For example, enterprises may need to purchase new routers, switches, and servers to support an end-to-end deployment. In addition, they may need to upgrade their network infrastructure and bandwidth to accommodate the increased traffic generated by end devices.
The cost of software can also be high, as businesses often have to buy or develop new applications specifically for end devices. These applications must be able to operate in a distributed environment, manage data generated by peripheral devices, and integrate with the rest of the organization’s IT infrastructure.
One way to help control costs is to partner with a managed service provider that offers end-to-end support for edge deployments. This can help ensure that implementation is successful and that any cost issues that arise are resolved quickly.
The sheer scale of the data
The sheer scale of data generated by peripherals can also present a challenge to businesses. Edge devices generate large amounts of data that must be stored, processed and analyzed. As a result, enterprises need to have the infrastructure in place to support this data growth and to be able to manage and use the data effectively. Companies unprepared for this flood of data may find themselves overwhelmed, with little visibility into what is happening at the end of their network.
Installation of end components in existing network architectures
Another challenge companies face when implementing edge computing is fitting the new edge components into their existing legacy network architectures. Edge devices are often deployed in remote locations and must be able to communicate with the rest of the organization’s IT infrastructure. This can be challenging as many existing network architectures are not designed to accommodate end devices. As a result, businesses may need to make significant changes to their network architecture or purchase new network equipment to support end-to-end deployments.
Edge computing is becoming increasingly popular as more businesses want to take advantage of its benefits despite the risks. While these risks may seem daunting, they can be effectively mitigated through a careful and thoughtful approach to deployment.