Updated 18/06/2026
The way businesses manage data is changing, and quickly. With the rapid growth of technologies like IoT, AI, autonomous systems and real-time analytics, traditional IT infrastructure is struggling to keep up. As organisations demand faster processing, lower latency, and greater reliability, a new approach is emerging: edge computing. By moving data processing closer to where it’s generated, edge computing is transforming how businesses operate.
IT infrastructure requirements must now accommodate greater demands for:
Added to which, there are industry-specific requirements, such as the need for particularly high physical protection in harsh manufacturing environments.
For these reasons we are seeing local IT resources - placing computing resources at the perimeter of a given network - to become more widely deployed. This deployment has been dubbed edge computing, and it ensures that latency is low (packet round trips of less than 100ms, with 25ms being desirable), thus making data readily available to a growing number of applications.
Edge thereby flips the computing paradigm, pushing computing and data closer to end-users and, in response, IT vendors are developing some innovative solutions which are tailored to sector needs.
The rise of edge computing is accelerating rapidly. Recent industry forecasts suggest that up to 75% of enterprise-generated data will be created and processed outside traditional centralised data centres or cloud environments by 2025, highlighting a significant shift towards distributed IT architectures. This reinforces the view that cloud computing will not disappear, but rather evolve
The focus for edge is typically on the immediate processing capacity required at the source of data; making it as fast and secure as possible.
For example, in “smart” internet grocery distribution centres, robots sensors and actuators continuously relay information on the status of processes and infrastructure. This forms the basis for innovative services such as alerts, predictive maintenance, and machine self-optimisation, delivered by the company’s IT department in real time. For this to happen, and for rapid responses to events and anomalies, it’s critical to have low latency between production and the IT infrastructure. A cloud data centre could struggle to support these scenarios.
With all this in mind, many vendors are introducing edge data centre solutions: an end-to-end product with standardised, preconfigured IT infrastructure which can be implemented quickly and cost-effectively, easily paving the way for Industry 4.0 applications.
For clients, the main features of a universal edge solution are:
Depending on the scale of the application, an edge data centre could comprise:
Some vendors are now combining typical ‘as-a-service’ offerings providing complete, one-stop solutions for those enterprises (regardless of size) that don’t want to manage their own systems.
To streamline edge data centre planning, many vendors now offer specialised web-based configurators which means compact and small enclosures can now be quickly and easily configured online. Customers can choose the right accessories without reference to a catalogue, then position and prepare the enclosure for mechanical processing.
Data-centre-as-a-service (DCaaS) offerings are now a viable alternative for end users who would prefer not to operate the edge data centre themselves. They are then free to focus on their core tasks while harnessing the benefits of the IoT for their business.
Hand-in-hand with IT-as-a-service (ITaaS) platform providers, the IT industry also offers private-cloud data centres in shipping containers, plus ITaaS. These containers are fully equipped with all key active components, such as servers, network connectivity and storage for immediate and rapid deployment/use.
This whitepaper takes you through four key areas for consideration to reduce the risk of potential downtime whilst still meeting the IT world’s future demands:
1. Physical Protection
2. Efficient cooling
3. Reliable & Secure IT Power Supplies
4. Real-Time Monitoring