Business leaders are in a juggling act with their IT infrastructure. They must balance latency, storage, and scalability requirements constantly.
Technologies like cloud computing provide the flexibility and capacity companies need, but the centralized architecture can lead to latency bottlenecks. On the other hand, Edge computing may provide required latency, but distributing dense storage at the edge can be expensive.
Businesses can’t choose one or the other when it comes to edge and cloud computing. Instead, they must employ strategies that allow them to harness the best of both. Fog computing is the middle layer that frees organizations from committing to a single computing paradigm. It helps companies solve the limitations of centralized computing and provides the following benefits through local computing:
- Fog computing reduces internet connectivity problems
- Fog computing increases data security
- Fog computing lowers network latency
Fog computing can boost your modern enterprise infrastructure. Perhaps, you’re curious about how it compares to edge computing. Let’s take a closer look.
What’s the Difference Between Edge and Fog Computing?
Edge computing is a subset of fog computing which can make telling them apart confusing. The easiest way to differentiate the two is to recognize edge computing’s restricted role. Edge computing is limited to processing where the data is being generated. A range of devices can perform this processing, including IoT devices on the factory floor and on-premise data centers. In contrast, fog computing includes edge computing infrastructure and the connections required to transfer data to the endpoint.
A major benefit of fog computing is that it doesn’t require devices to be on the same type of network. This characteristic allows organizations to filter processing by latency needs to boost efficiency. For example, processing that requires lower latency can be processed on local networks, while teams can push less time-sensitive processing to the cloud.
Another benefit of fog computing is that it makes your cloud experience more efficient by splitting processing loads. Local computing can do part of the processing, clean up data, and send what’s needed to the cloud. By sending partially processed data instead of raw data, you speed up data transfer and strategically use cloud resources.
To provide these benefits, fog computing uses a network of edge nodes that are distributed and interconnected. This structure allows data to flow smoothly from anywhere in the network but makes edge hardware indispensable — especially as applications grow in complexity and AI and deep learning usage increases.
Power Your Fog Computing With Adaptive Edge Hardware
Edge and fog computing are closely related. In fact, fog computing can’t exist without edge infrastructure. It’s essential to work with a partner who can advise on forward-thinking hardware choices, build it to your requirements, and help you support it throughout its lifecycle. Intequus can help ensure your fog computing is supported by the best hardware.
Our team advises on hardware choices that will extend the longevity of your infrastructure while providing cutting-edge performance. Our hardware capabilities are coupled with end-to-end management covering design, deployment, maintenance, support, and decommissioning. Learn how you can take control of your edge infrastructure while simplifying its management. Let’s talk.