#edge-computing

#edge-computing

A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."

Edge computing is a type of IT infrastructure in which data is collected, stored, and processed near the "edge" or on the device itself instead of being transmitted to a centralized processor. Edge computing systems usually involve a network of devices, sensors, or machinery capable of data processing and interconnection. A main benefit of edge computing is its low latency. Since each endpoint processes information near the source, it can be easier to process data, respond to requests, and produce detailed analytics.

Dell Technologies is bringing innovations to its PowerProtect appliances. The solutions are designed to help companies respond more quickly to cyberattacks by improving protection, enabling intelligent automation, and providing greater flexibility. IT professionals are increasingly concerned about disruptive cyberattacks. Cyber resilience is central to the enhancements. PowerProtect now integrates with Dell NativeEdge for edge computing. The solution also supports Nutanix Hyper-Converged environments via Prism Central.

There are, however, a couple of reasons why data centers in space are being considered. There are plenty of reports about how the increased amount of AI processing is affecting power consumption within data centers; the World Economic Forum has estimated that the power required to handle AI is increasing at a rate of between 26% and 36% annually. Therefore, it is not surprising that organizations are looking at other options.

With advanced processing in the car, we can handle interference on board so that it works in low-data-connection areas,

A lot of cheap dev boards and Qualcomm-flavored software tools will certainly give the company access to entire sectors previously excluded. Qualcomm hitherto only talked to big old companies who'd sign big old contracts with big old secrets. Now Qualcomm silicon and software can get into the hands of individuals, educators and inventive start-ups. That's where the future comes from, especially where the better sort of AI fertilizes the better sort of robotics.

Cloudera describes itself as the company that brings "AI to data anywhere" today. It's a claim stems from its work that spans a multiplicity of data stacks in private datacentres, in public cloud and at the compute edge. As we now witness enterprises move quickly through what the company says are "new stages of AI maturity", Cloudera used its Evolve25 flagship practitioner & partner conference this month in New York to explain the mechanics of its mission to help enterprises navigate this transformation with an AI-powered data lakehouse.

To support HTTP client APIs, Cloudflare reimplemented the core node:http APIs by building on top of the standard fetch() API that Workers use natively, maintaining Node.js compatibility without significantly affecting performance. The wrapper approach supports standard HTTP methods, request and response headers, request and response bodies, streaming responses, and basic authentication. However, the managed approach makes it impossible to support a subset of Node.js APIs.

From stealth mode to center stage, Mach Industries is bringing AI into one of the world's most complex and controversial sectors: defense. At TechCrunch Disrupt 2025, Ethan Thornton, CEO and founder of Mach Industries, steps onto the AI Stage to share what it takes to build in high-stakes environments where speed and autonomy matter most - and why next-gen infrastructure starts with rethinking the fundamentals.

As the backbone of artificial intelligence (AI), machine learning, cloud computing and the internet of things (IoT), datacentres are at the centre of modern business infrastructure, but as businesses become more dispersed, the infrastructure surrounding datacentres has become more critical and complex, with network outages no longer isolated events and their cost to businesses never higher, a study from Opengear has found.

For OpenYurt, Kubernetes at the edge means running workloads outside centralised data centres at locations like branch offices or IoT sites. This helps reduce latency, improve reliability when connectivity is limited, and enable tasks such as analytics, machine learning, and device management, all while maintaining consistency with upstream Kubernetes. As the CNCF notes in its Cloud Strategies and Edge Computing blog, deploying compute resources closer to the network edge can deliver high-speed connectivity, lower latency, and enhanced security.

With HyperScale Edge, Commvault is specifically targeting remote locations and smaller businesses where space and IT resources are limited. Think of retail stores, branches, and distribution centers. These environments often have different needs than large data centers. The solution works with validated hardware from Dell, HPE, and Lenovo. Like the other HyperScale products, it is delivered as a software image that is easy to install. This makes implementation faster and more predictable.

The integration combines Scale Computing's Hypercore platform with Bitdefender's GravityZone to secure workloads, virtual desktops, and data in edge environments.

The Box isn't some magical compression algorithm. It's edge AI hardware that can run the models that needed Google's data centers two years ago. And it's shipping right now.