We know by now that to extract optimal value from data intelligence, it needs to be highly accessible, captured in real time and at its freshest state and quality if it is to drive immediate operational decisions and responses.

It’s why we have seen the decentralisation of the cloud as the sole vacuum of system intelligence and the migration of data capture and processing to the most remote part of the network edge. Not only does this provide for enhanced agility in terms of data access and handling, but also for improved security. The time data spends travelling across the network bandwidth and potential for corruption is much reduced, while the regular bottle necks that ensue as multiple devices communicate back to a centralised core network are fully consigned to the past.

Unsurprisingly, traction has been buoyant in the data-heavy environs of the IoT space, where more and more imaginative applications have demanded greater efficiency in the processing and transmitting the volumes of data generated. Specifically, the digital edge has flourished in industrial IoT settings, where increased data usage in remote devices becomes a norm, rather than exception.

Here, data must be transmitted across some of the most remote and challenging environments. This means sensors require sufficient processing power to make the kind of mission critical decisions that can’t wait for data to be sent to the cloud. Collecting data fast and flexibly in a gateway solution is a major bonus, not only lowering operational costs, but localising certain kinds of analysis and decision-making in a move that empowers the end user.

Yet the complexity of IoT ecosystems dictate that it is not just about getting data to the brink and job done. First, there’s the question of which approach is best to facilitate it, which can see many caught short by an over reliance on the deployment of dumb devices such as the low-cost routers in the field, while saving investment for more sophisticated hardware further up the food chain.

Where IoT devices are deliberately designed with simplicity in mind, and to reduce power consumption, the upshot can be endpoints exposed and vulnerable from a security standpoint. This should remind us of the importance of the stability and processing power that the cloud can bring and the benefit of architectural solutions that facilitate both.

Indeed, while the credentials of edge were once entirely framed in a debate that pitted it against the cloud as an either/or option, in reality this simply hasn’t panned out. Amid the complexities and choice that define the IoT space, a more nuanced hybrid approach was always going to prove a preferred option to deliver the best of both worlds. This capitalises on the more robust capabilities of the cloud, and the contextual awareness and locality of the edge. Such flexibility is increasingly imperative to thrive in the digital enterprise.

Delivering this duality, demands an underlying infrastructure that provides a consistent platform for both entities, one that is based on open architecture with flexibility and modularity that can drive real time integration for endpoints.

Simple and seamless integration is the foundation of this approach. It ensures the transcendence of boundaries that modern app development now encompasses and the accommodation of connected devices that use an increasingly wide variety of data formats and operating systems – or in some cases, no operating system at all. It is why open source development must play a role, having evolved from being seen as simply a cheaper alternative to proprietary software to becoming the primary source of innovation. Innovation that enables the creation of smarter, event-driven microservices and IoT edge applications.

Furthermore, using an intuitive drag-and-drop and API-led design approach, across cloud, edge, and hybrid environments delivers the speed and agility needed for making changes on the hop. With less overall cost and impact on the existing infrastructure, apps can be connected without the need to write code, a move that plays into the hands of multiple users with varying levels of expertise.