Getting Started With Edge Computing

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Edge Computing is an open distributed computing paradigm that ensures speedy computation, handles data activities, network operations and data storage. It brings the devices closer to the place as a result improving the post time and saving bandwidth. It features de-centralized processing power enabling mobile computing and Internet of Things.

Simply saying, Edge Computing brings the de-centralization of networks. Edge Computing is the upcoming enhancement and advancement in technology. The literal meaning of the word ‘Edge’ is the geographic location. On the planet to deliver services in a distributed manner.

The computing that occurs by placing workloads at the edge of corporate networks where the data is being created. It known as Edge Computing. The “edge” is defined as the position where the end devices can access the rest of the network devices like laptops, phones, desktop, machines, routers, and sensors. This technology is used to connect IoT devices so they can deliver data efficiently, receive instructions quickly, and download software updates from a cloud or a data centre without any hassle.

Benefits of Edge Computing

Edge Computing is a new type of technology that will not only save time but also save the cost of servicing and other charges too.


It is the most attractive and essential factor in any field and especially in the computer science field. Every company and industry demand high-speed technology aspects such as financial organisations because slow speed data processing can make a heavy financial loss to the company, healthcare industries because a fraction of second either can save the patient’s life or can take the life, and other service-providing industries need fast speed computing otherwise it can irritate the customers which will make a bad impact of the industry on its customers. Edge Computing will definitely benefit these sectors because of its extremely fast computing speed. Through edge computing, the latency of the networks will be decrease, and also IoT devices will process data at edge data centres. Thus, data need not be travelled back to the central server (i.e., centralize server).

Scalability of Data

Scaling becomes easy and simple with edge computing where one can buy edge devices with high computation power for increasing their edge network. There is no such requirement to make their own private and centralized data centres for fulfilling their data needs. Just combine the edge computing with colocation services in order to expand your edge network. Otherwise, companies need to purchase new equipment for expanding their IT infrastructure. Thus, it will save the companies for purchasing new devices. It is enough if the industries buy a few IoT devices to expand the network.


Edge Computing has gained popularity because it is the most cost-effective method as compared to the existing alternative technologies. It is because edge computing reduces the cost of data storage, network costs, data travelling costs, and data processing costs. Also, edge computing ensures interoperability among modern legacy and smart IoT devices, which are not compatible by concerting those communication protocols that are used by the legacy devices into a language that could be understood by the modern smart devices as well as the cloud. Thus, there is no need to invest money in purchasing new IoT devices because we can easily connect the existing or older IoT devices via edge computing.

Challenges in Edge Computing

Limited Capability

Part of the allure that cloud computing brings to edge — or fog — computing is the variety and scale of the resources and services. Deploying an infrastructure at the edge can be effective, but the scope and purpose of the edge deployment must be clearly define — even an extensive edge computing deployment serves a specific purpose at a predetermine scale using limited resources and few services

Colocation Cloud Data Centres

The method of private housing servers and networking devices in a third-party data centre is Colocation. To ensure smooth edge computing operations, the cloud provider would require setting up or collaborate with local data centres, which itself will bring a lot of challenges in terms of data virtualisation and replication.

Continuous Local hardware Maintenance

With edge computing, the number of edge devices also increases. Thus, it involves large investments and more maintenance costs.

Network Connectivity and Electrical Power Management

Edge computing requires uninterrupted network connectivity and electrical power management because different edge devices require different processing power and network connectivity.

Edge computing use cases and examples

Some of the potential areas where we can use edge computing and what are the uses of edge computing in these areas


Consider a business that grows crops indoors without sunlight, soil or pesticides. The process reduces growth times by more than 60%. Using sensors enables the business to track water use, nutrient density and determine optimal harvest. Data is collect and analysed to find the effects of environmental factors and continually improve the crop growing algorithms and ensure that crops are harvest in peak condition.


An industrial manufacturer deployed edge computing to monitor manufacturing. Enabling real-time analytics and machine learning at the edge to find production errors and improve product manufacturing quality. Edge computing supports the addition of environmental sensors throughout the manufacturing plant. Providing insight into how each product component is assembles and store — and how long the components remain in stock.

Improved Healthcare

The healthcare industry has dramatically expanded the amount of patient data collected from devices, sensors and other medical equipment. That enormous data volume requires edge computing to apply automation and machine learning to access the data, ignore “normal” data and identify problem data so that clinicians can take immediate action to help patients avoid health incidents in real time.


Hope after reading this blog you have got the basic idea of Edge Computing, its uses and challenges. If you want to deep-dive into Edge Computing, you can go through the reference section.


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Written by 

Shubham Gupta is a DevOps Consultant at knoldus. He is practising Devops - Docker, Jenkins, Ansible, Kubernetes. He is passionate about DevOps technology and cloud computing.