Edge Computing vs. Cloud Computing_ A Concluding Debate
Engineering 6 min read

Edge Computing vs. Cloud Computing: A Concluding Debate

What is edge computing? Is edge better than the cloud? What will happen to the cloud? There is an ongoing debate about the usefulness of cloud computing in a much more demanding market scenario. In a fast-paced market where growth and scalability are taking center stage, businesses want a service that extends the cloud’s capability across multiple sites and networks without compromising on time. 

Modern application architecture demands unique architecture that can handle the increasing workload while supporting a distributed infrastructure. Services like retail data analytics, network services, and AR/VR-based applications require continuous cloud capability at remote sites. 

Bridging the peripherals of the system on the edge 

Many businesses are already applying simplified administration and flexibility of cloud computing architectures on distributed infrastructures, spanning multiple sites and networks. Today, many companies demand expansion of cloud capabilities across WAN networks and into smaller portions on the network edge. 

Although edge computing is still in its early days, it is becoming more apparent that emerging use cases will significantly benefit from edge computing’s distributed architecture. So, where is this need coming from, and why is there a debate on edge computing vs. cloud computing? For that, we will need to understand what edge computing is. 

The buzz: What is edge computing? 

Edge computing is a decentralized, distributed computing infrastructure. This infrastructure evolved with the growth in implementing the Internet of Things. IoT devices generate data in bulk, which requires faster processing and real-time analysis.  

While cloud computing addresses this using a centralized, cloud-based location, edge computing brings data computation, analysis, and storage closer to the devices. With data collection happening on the devices, edge computing removes the requirement of transmitting data back to the cloud and waiting for it to get relayed back.  

The reason edge computing is now a buzzword lies in the fact that companies now realize that growth prospect in the cloud space is decreasing. Whatever that needed centralization is centralized. The upcoming opportunities for developing the “cloud” are currently on the “edge.” 

Edge computing brings faster response time and increased reliability 

Faster processing of data is vital for performing core business functions. Many modern applications work on a cloud infrastructure where a vital piece of information is easily managed, accessed, and calculated in a virtual space. 

Cloud computing does the crunching and processing of data away from the device in clusters of cyberspaces. This creates a longer time for processing crucial datasets, resulting in higher latency. Edge computing’s most significant benefit is its ability to reduce latency by increasing network performance. 

We want to add something interesting here; edge computing differs from cloud computing in two significant areas: 

1. Faster decision-making prowess 

For an organization that needs faster decision-making capabilities, the lag observed in cloud computing is unacceptable. Edge computing collects the data at the edge and runs the workloads on edge devices, making the decision-making process faster.  

2. Smoother handling of data bandwidth 

If you consider running an IoT or other sensor-based infrastructure that needs faster processing, then the sheer amount of data these devices collect will be overwhelming for cloud computing. 

Edge computing use case: Where can it come in handy for businesses? 

If we go by facts and figures, the global cloud computing market will grow to USD 947.3 billion by 2026. Even though edge computing commands a lesser market size in the current market, it is also growing at a good pace. The expected growth of the edge computing market is USD 87.3 billion by 2026

edge computing flow

Edge computing is one of the critical components of the industrial internet of things (IIoT); it plays a crucial role in accelerating the adoption of industry 4.0 adoption. How?  

First use case: An IIoT Environment 

Let’s say that you deploy an intelligent device in an IIoT environment. You will need to integrate an edge computing platform with a cloud data center. The IIoT combines real-time data processing, hardware optimization, and connectivity of IoT systems for better efficiency of the entire process. 

The adoption of smart robotics, remote diagnosis, asset optimization, connected product integration, and smart construction applications will boost edge computing implementation in various industries. 

Related Article: Industrial IoT trends that businesses must watch out for in 2021 and beyond

With the infusion of edge computing in IIoT processes, enterprises can achieve improved network communication and cooperative coordination with the cloud. 

Data security concerns can be mitigated using a professionally designed architecture that uses leading hardware and software components at the edge. 

IoT edge computing devices process data locally or at near-the-edge data centers. This means that the information collected by these devices doesn’t travel the same distance as in a cloud architecture. 

Second use case: A Smart Manufacturing Unit 

A data-driven, high-tech manufacturing machine’s functionality is crucial for the business as any type of delay in decision-making will result in huge losses. The said delay will only occur if the computation is being done on a cloud architecture.

For the machine to take decisions at a much faster rate without compromising the quality of output, the manufacturers need to opt for edge computing architecture. Creating high-capacity data storage, processing, and analysis centers is crucial to manufacturers that implemented IoT devices in and around their plants.

Related Article: Smart factory: A new frontier for the manufacturing industry

Smart devices with edge computation power will function with pre-defined metrics of tolerance levels and manufacturers can implement edge computing for faster localized processing. Once the device senses the metrics rising above the pre-defined tolerance, a warning signal will shut down the machine within microseconds, avoiding any loss. 

Four significant edge computing benefits for businesses 

Why should any company give edge computing a thought? Where does its application matter? What problems can edge computing solve for businesses? Let’s dive into its benefits. 

1. Faster response time 

In edge computing, data storage and computation are distributed over local servers. There is no to-and-fro between the cloud, which reduces latency and leads to faster responses. Edge computing helps companies mitigate critical machine operations break down. 

2. Reliable operations 

Monitoring remote installations such as oil rigs, solar farms, or windmills on remote locations with unreliable internet connectivity is often complex. Edge devices’ ability to locally store and process data ensures zero operational failure even with limited internet connectivity. 

3. Security and compliance 

Due to edge computing’s technology, massive data transfer takes place between devices and the cloud, and this scenario is easily avoidable. Companies can filter sensitive information locally and only upload important model-building details on the cloud allowing the users to have a security and compliance framework. 

4. Cost-effectiveness 

As mentioned previously, edge computing is one of the core components of IoT. There are concerns about IoT adoption as it involves the upfront cost of managing heavy network bandwidth, data storage, and computational power. Edge computing performs data computations locally, giving businesses the choice of running services locally and sending selective data to the cloud. This process helps them reduce the final costs of IoT solution installation. 

Concluding thoughts: The “versus” doesn’t matter; edge and cloud need to co-exist 

The edge must not replace cloud computing as there’s still a need for centralized processing, and we think there is no versus between these two technologies. Edge computing helps businesses optimize internet devices, sensors, and web applications by bringing computing platforms closer to the data source. 

Doing so reduces long-distance communication between client and server, further decreasing the latency and bandwidth usage. Businesses must find a way of combining the data-gathering potential of edge computing with the cloud’s storage capacity and processing power. 

This will also help them efficiently manage their applications and IoT devices without sacrificing valuable analytical data that can help them further improve their services in the future. 

Enterprises must look for digital transformation experts like Rapidops, helping businesses of all sizes and shapes reimagine their strategy and growth plan by leading the digital revolution.

Saptarshi Das

Content Marketing Strategist -- A seasoned marketing professional who develops content for leaderships and learners by covering the subject matter in a detailed, well-laid and understandable manner after in-depth SERP analysis. An empath who likes to keep his thought process aligned with others to generate consumable content.

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