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Businesses are pursuing digital transformation at an unprecedented pace, often driven by the innovation enabled by edge computing. Aware of the limitations of legacy systems and cloud computing, companies want to use edge devices to leverage data, streamline operations, and run complex workloads in a flexible, fast, and resilient way.
The data reflect this story. Recent estimates predict that there will be 27 billion connected IoT devices by 2025 (IoT Analytics 2022). Demand is driven by strong demand from certain sectors, such as automotive, telecom, manufacturing and retail, where optimized supply chains and advanced automation are having too much of an impact. Industry 4.0 is no longer just a buzzword; it’s happening now.
But while there’s a shared vision of edge and the role it will play in renewing traditional infrastructure, this consensus doesn’t change the fact that there are significant challenges to overcome.
At a fundamental level, companies are often at very different levels of maturity in the transition to edge solutions. At annual SUSECON Digital 2022 conference, we saw firsthand that edge cases are diverse and no one solution is right for everyone. Instead, solutions need to be aligned with where a business is in its journey, resulting in an urgent need to create optimal solutions in mixed environments with legacy hardware while adopting Kubernetes.
As enterprises seek to realise their edge vision in these environments, there are three central hurdles to address beyond the inherent complexity of containerised workloads.
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Scaling is the first major challenge for most customers. Edge environments are much larger than those introduced in traditional enterprises. For example, if we look at the automotive sector, a modern car is itself a computer: from the engine to the braking system, even a rear view camera – when a calculation takes place, an analytical event takes place in the car, instead of data being sent to a central location must be shared.
Your car represents a range of peripherals. Consider the number of edge devices operated by BMW — not just the cars, but stores and manufacturing sites — the scale is significant. The same goes for major retail chains like Home Depot, which uses edge to manage thousands of its storefronts to streamline operations and applications.
Security is the second challenge. Edge deployments introduce new threat vectors and significantly increase the attack surface. With systems located outside a traditional data center, they need to be secured from the base applications to the operating environments and the workloads themselves.
Management is the third challenge. If you have thousands of edge devices, how can you quickly configure them all? This can be practically managed from a central location, with a single device connected to a cluster of edge devices, enabling a batch update without the need for physical intervention on site. Having a common platform around K3s allows one to quickly and effectively deploy and update the underlying container platform. As a result, resilience is often paramount, as consistent communication is never guaranteed in edge deployments.
How can enterprises deal with security risks?
Security should be the invisible thread that runs through the entire environment. As such, it should be baked into full lifecycle management.
Resilience must be woven into the edge infrastructure from the start, meaning the onboarding process must be secure. To be secure, it must also be easy to implement. Practically speaking, if you have three edge nodes on a site and need to add a fourth, you don’t need a team of IT people. The point is that the node (a box) is shipped to the site, has someone who can physically connect it on site, so that the node is then updated from a central location without any intervention on site.
This is the full lifecycle management where any updates are done remotely to that node, connected to the other nodes as a cluster. It is an integral part of navigating security risks, requiring a zero trust security approach. This is a practical approach to mitigate risk and deal with the new threat vectors introduced by edge deployments. With the proliferation of devices in edge environments and the shortcomings of traditional authentication approaches, models that don’t trust by default are becoming mandatory.
If these challenges are addressed, enterprises can truly deploy IoT devices at a scale that far exceeds traditional infrastructure. This scale can be safe.
We need only look at the industrial IoT field to see that the possibilities are vast, from predictive maintenance of machines to rapid, remote monitoring of equipment.
For example, if you are in a wood factory, there may be a device installed that can predict how long a saw blade will last, reducing the number of people needed to manage it and extending the life of the saw. sheet. Timely analysis input using edge devices saves the cost of tools and improves productivity.
It’s easy to see how this vital part of maintenance can translate to other industries. Whether it concerns controlling robots in a warehouse, monitoring trucks or reading the analytics of medical devices. The pursuit of omnichannel strategies and walkout technology are two edge-enabled innovations driving change in the retail sector.
Accessing real-time analytics and leveraging previously lost data will provide further analytical value to a business, especially the ability to identify and remove supply chain inefficiencies. Edge will be able to bring applications closer to the end user for a vastly improved experience. The opportunities of edge computing are clear for both enterprises and customers, but so are the risks if security fails to keep up with the pace of digital transformation.
Addressing the challenges of scale and carefully implementing solutions that weave both security and resilience into core infrastructure are inevitable if enterprises are to succeed in what is quickly becoming an inevitable journey to the edge.
