Edge Computing vs Cloud Computing

 In Technology

Small and giant companies are moving their applications continually toward the cloud. Only for the cloud, more than 28 percent of an organization’s total IT budget is now maintained aside for cloud computing.

Nowadays more than 75 percent of organizations have at least one application on a cloud, indicating that companies are recognizing the advantages of cloud computing and slowly adapting.

All the Industry experts and companies have now predicted the future growth of cloud computing. It is now believed by the experts, that cloud has reached at end of its run at the top and it is now, betting on the growing popularity and benefits of edge computing.

What is Edge Computing?

Edge computing is a distributed paradigm that gets computation and data storage closer to the source of data.

Edge computing is an architecture rather than a technology that is expected to grow response time and save bandwidth.

The source of edge computing lies in a content distribution network that was built in the late 1990s to serve web and video content from edge servers that were deployed close to users.

These all networks were developed to host applications and application components at the edge servers in the early 2000s. Which tends to result in the very first commercial edge computing services.

These edge computing services hosted applications such as dealer locators, shopping carts, and real-time data aggregators.

Organizations are now investing in edge technologies to reap the many following benefits.

Reduced cost:

As compared to cloud computing, using the local area network for data processing grants organizations higher bandwidth and storage comes at lower costs.

As the processing happens at the edge only, less data needs to be sent to the cloud or to the data centre for further processing which tends to be cost-cutting as well. As the amount of data, needs to be decreased.

Model Accuracy

Specifically for the edge use cases which require real-time response, AI relies on high-accuracy models.

When the bandwidth of the network is too low, it is typically cleared by reducing the size of data fed into a model. Which tends to reduce image sizes, skipped frames in a video and reduced simple rates in audio.

When deployed to the edge, data feedback loops can be used to enhance AI model accurateness and multiple models can be run simultaneously.

Lower latency:

At the edge data processing results in eliminated or reduced data travel. Which can give speed to insights for use cases with complex AI models, which require low latency, such as fully autonomous vehicles and increased reality.

What is Cloud Computing?

Cloud Computing is an on-demand availability of computer system aids, especially data storage/cloud storage and computing power.

It is an on-demand delivery of IT resources over the internet with “Pay-As-You-Go” pricing. We can access technology services like computing power, storage and a database, on a needed basis from any cloud provider.

Each location being a data centre, large clouds have often functions distributed over multiple locations. To achieve coherence and typically using a “Pay-As-You-Go” model Cloud computing relies on sharing of resources.

The “Pay-As-You-Go” model can help in reducing capital expenses but it can also lead to unexpected operating expenses for unknowing users.

There are many benefits of cloud computing and many organizations are adopting it and saying that it is extremely important to their organization’s future strategy and growth.

Let’s see why cloud computing adoption is now only growing and why enterprises have executed cloud infrastructure.

Lower upfront cost

Many expenses of the organizations come down or are eliminated easily, such as buying software, hardware, IT management, and round-clock electricity for power and cooling.

It allows an organization to launch an application as quickly as possible with low financial expenses.

Flexible Pricing

Allowing more control over costs and fewer surprises, Enterprises can only pay for the computing resources used.

Limitless compute on demand

By automatically provisioning and de-provisioning resources, Cloud services can react and adapt to changing demands instantly.

This will not only lower the cost but also increase the overall efficiency of organizations.

Simplified IT management

Allowing employees to focus on their business’s core needs, Cloud providers supply their customers with access to IT management experts.

Edge Computing Vs. Cloud Computing - Which One’s Better?

First, it needs to be understood that cloud computing and edge computing both are different and non-interchangeable technologies that can not be replaced by one another.

Edge computing is used to process time-sensitive data, while cloud computing is used to process data that is not time-driven. Besides latency, edge computing is preferred over cloud computing in remote locations, where there is limited or no connectivity to a centralized location.

Cloud computing is used to process the data which is not time-driven and edge computing is used to process the time-sensitive data.

In remote locations, where there is limited or no connectivity to a centralized location, edge computing is preferred over cloud computing in a remote location.

These all locations required local storage, similar to the mini data centre, with edge computing delivering the required solution for it.

For the specialised and intelligent devices Edge computing is also beneficial. While all these devices are likely to be PC, they are not traditional computing devices that are designed to perform numerous functions.

When to Use Edge Computing vs Cloud Computing?

Both edge and cloud computing have different features and most organizations will end up using both technologies. Below are some references when looking at where to deploy different workloads.

Edge Computing Cloud Computing
Non-time-sensitive data processing Real-time data processing
Reliable internet connection Remote locations with limited or no internet connectivity
Dynamic workloads Large datasets that are too costly to send to the cloud
Data in cloud storage Highly sensitive data and strict data laws

As an example, when surgeons need real-time data, edge computing is preferable to cloud computing in medical robotics.

Comparisons between Edge Computing and Cloud Computing

The one this to note here is that it is not advised to replace cloud computing totally with edge computing.

The difference between these two can be like a difference between an SUV and a racing car. As both vehicles have an individual purpose and use.

We have noted some point that gives you a better idea to understand the difference between both.

Points of Difference Edge Computing Cloud Computing
Suitable Companies Edge Computing is considered ideal for operations with extreme latency situations. Therefore, medium-scale companies that have budget restrictions can use edge computing to save financial resources. Cloud Computing is more appropriate for projects and organizations which deal with huge amounts of data storage.
Programming Several other platforms may be used for programming, all having various runtimes. Actual programming is nicely worked in clouds as they are typically made for one target platform and use one programing language
Security Edge Computing needs a strong security plan including progressive authentication methods and proactively tackling attacks. It requires less of a robust security plan.

Bottom Line

Most organizations are moving towards edge computing. Regardless, edge computing is not only the solution.

For the computing challenges faced by IT vendors and organizations, cloud computing remains a possible solution.

In some examples, they use it in pair with edge computing for a more wide solution. Empowering all data to the edge is also not an intelligent decision. It’s why public cloud providers have started integrating IoT strategies and technology accumulations with edge computing.

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