The rise of cloud computing has opened up a world of opportunities. However, it isn’t the only form of remote computing. Cloud computing has a lesser-known cousin called edge computing. While there are similarities between the two concepts, there are distinct differences in how they work and the purposes they serve.
However, together these two forms of remote computing are transforming how we work, communicate, play, and the landscape of society in general. Let’s dive into the world of remote computing as we compare and contrast cloud and edge computing.
Key Differences Between Edge and Cloud Computing
These are both forms of remote computing. So, a useful starting point is to set out a simple definition of the concept of remote computing. Remote computing, at its core, refers to the practice of using computing resources that are not physically present at the user’s location.
The simplicity of this definition hides the complexity of the topic. For instance, remote workers who require access to business systems will require completely different resources from an Internet of Things (IoT) device that needs to process data in real-time. This is where the key differences between cloud and edge computing come into play.
Cloud computing is more suited to scenarios that process large amounts of data. By contrast,edge computing is more suited to processing less data, but in real-time.
This is a simplified description of the difference between the two remote computing models. Let’s break it down a bit by examining some of the metrics that help define cloud and edge computing:
Type of Difference
Edge Computing
Cloud Computing
Data Distribution/Storage
Distributes data across multiple locations.
Stores data in a single centralized location.
Data Processing
Processes data closer to the source, minimizing latency.
Processes data in the cloud, allowing for scalable and centralized processing.
Requires managing security across multiple locations, increasing complexity.
Simplifies security by having a centralized storage location, although it creates a single point of failure.
Reduces the need for bandwidth by processing data locally, minimizing data transfer requirements.
Requires significant bandwidth for data transfer to and from the cloud, which can be challenging in areas with limited connectivity.
May require more initial investment in infrastructure, but ongoing costs can be lower compared to cloud computing.
Offers cost-effectiveness that scales with usage. It also involves fewer upfront costs, making it suitable for different budget considerations.
These differences define the benefits of each model and dictate their use cases.
Edge and Cloud Computing in Action
The unique characteristics of each model are what make them suitable for different use cases. Understanding the scenarios in which each model excels, is the simplest way to understand the difference between the two approaches to remote computing.
There are gray areas where the two methodologies collide. But, in general, they provide distinctly different services.
Cloud Computing Use Cases
There are many benefits to cloud computing. It is primarily used in situations where vast amounts of data are stored, accessed, and managed from a centralized location. Among the scenarios that these attributes make this the correct choice are:
The common thread that runs through these uses is the requirement to manage and process large amounts of data. While this can occur in real time, this isn’t a core characteristic of cloud computing.
Edge Computing Use Cases
Edge computing is more suited to the real-time processing of smaller amounts of data. It is aimed at scenarios where latency needs to be minimized and immediate actions are required.
Among common uses for edge computing are:
Edge computing is the preferred solution where low-latency access to data is required.
The Future of Cloud and Edge Computing
Predicting the precise future of these is difficult. The rapid uptake of remote working practices, IoT, and AI, are all going to play a key role in dictating the future of these forms of remote computing.
However, these do offer some clues as to how we can expect these to evolve. There are three main aspects to consider when discussing the future:
Depicting the future is always a hit-and-miss affair. However, there is little doubt that both these technologies will continue to develop rapidly.
The rise of remote computing in all its forms means these technologies are here for the long run. Both cloud and edge computing have strengths and weaknesses that largely dictate the scenarios that employ them.
However, the future likely lies in hybrid models that combine the strengths of both models. These networks will combine the scalability and data processing capabilities of cloud computing with the low-latency and real-time processing capabilities of edge computing.
