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How Distributed Cloud Computing Extends the Range of Cloud Use Cases

The use of cloud environments for safe and effective data management and deploying business-specific applications is no longer a new approach. Still, distributed computing attracts interest from companies that are eager to manage their data more intelligently, making data transfer as instant, safe, and seamless as possible.

Gartner predicts that by 2024 most cloud vendors will offer distributed cloud computing opportunities on an Infrastructure as a Service basis, so let’s find out what benefits a distributed cloud can offer right now and how it extends the range of cloud use cases.

What Is a Distributed Cloud?

Distributed cloud takes on a new approach to cloud computing definition. According to it, a distributed cloud means a public cloud infrastructure that uses a distributed approach to data sets storage and processing. To put it simply, a company that uses distributed cloud computing can store and process its data in different data centers that may be physically located in other locations.

To better understand cloud and distributed computing, let’s review the example of microservice app architecture. When an app is built on a microservice foundation, each part works separately, performing API calls in response to the user’s request. Here is how distributed cloud computing works – users access only a part of the cloud, the part which hosts the necessary data.

Users can receive the data almost instantly since the distributed cloud cluster is located in reasonable proximity to the location from which the request was made.

Advantages of Distributed Computing

Being a highly responsive, safe, and accessible data environment, distributed cloud computing can promise the following benefits for the business:

  • Instant data transfer. The speed of data transfer directly depends on the amount of computing power the system needs to process the user’s request and deliver the necessary information. In public clouds, the data has to travel a pretty long distance before being delivered to the users. The use of distributed cloud solves this problem and allows the data to move faster due to the closer physical proximity of the distributed data center.
  • Cost-effectiveness. This benefit of distributed cloud computing is directly connected to the one above. The less computing power you consume to make a request and get a response, the less you have to pay to the distributed cloud vendor.
  • Transparent cloud management from a single dashboard. In contrast to using hybrid cloud, when the user has to switch between public and private cloud environments to manage cloud data, distributed computing allows for managing and requesting it from a single dashboard. The company also has to partner with only one distributed cloud computing vendor instead of multiple ones. The latter feature shows the benefit of a distributed approach compared to the multi-cloud option.
  • Better disaster recovery and data protection opportunities. Another advantage of distributed computing is that cloud environments are independent, despite being owned by a single vendor. The company using them has a better option to protect its data by backing up crucial information and distributing it across several environments. This is also an opportunity for faster disaster recovery – if one of the cloud data storage fails, the other ones are still working.

How Distributed Cloud Empowers Edge Computing

Still, the most prominent advantage of distributed computing is that it gives a way for edge computing, which brings instant processing of huge amounts of data due to the physical proximity of the data source and the device making a request. As stated by The Verge, “It doesn’t mean the cloud will disappear. It means the cloud is coming to you.”

From the technical standpoint, edge computing can promise a better bandwidth essential for vast data sets processing and transfer. Global Internet users and smart devices generate and upload 24,000 gigabytes of data to the Internet each second.

In response to the necessity of developing, processing, analyzing, and delivering growing data amounts, edge computing is considered the future of cloud computing. According to Statista, the global edge computing market size will reach $10.9 billion by 2024 (compared to $1.9 billion in 2018).

Distributed Cloud Use Cases

According to the research, the amount of cloud-connected devices is expected to grow, and for some of them, instant data transfer, predictable latency, wider bandwidth, and high availability will be essential, for example, in such industries as automation and healthcare.

Still, the use cases of distributed cloud are not limited to the ones above. Below are some examples of cloud computing showing how companies leverage their power in conjunction with edge technologies.

Automotive industry

As for the usage of distributed clouds in the automotive industry, the development of semi-autonomous and self-driving cars is the most prominent example. The core idea behind such vehicles is an in-build opportunity to capture data in real-time, accessing the road situation, process this data, and make instant decisions.

Cars in the future are expected to be powered with AI, namely object recognition, data analysis, and decision intelligence features. They will also be able to capture real-time data using 5G. Leveraging distributed clouds, in this case, promises a better option for instant data transfer and subsequent decision-making.

For example, the projects created by Tesla are examples of edge computing and distributed cloud usage.

Healthcare

The opportunity to instantly process and deliver huge data amounts is also promising for healthcare. For this industry, the list of use-cases is almost endless. For example, healthcare providers can use hybrid clouds and edge computing for in-hospital and at-home patient monitoring. Plus, there are a lot of IoT-based apps and devices for tracking specific symptoms and conditions.

As for the prominent example of edge computing technology for healthcare, let’s consider the example on the verge of medical services and smart home solutions. Kwido is the next-generation set of software and hardware created for elderly patients monitoring at home. With the help of sensors, it catches behavior anomalies of elderly users (for example, staying in the bathroom for a long time), changes in habits, and reports it to the mobile app of the supervisor.

Content Delivery Networks

Content Delivery Networks (like the Internet itself) are also powered mainly by the edge and distributed cloud computing. For example, Netflix and YouTube use these approaches together with the microservice architecture to speed up vast amounts of data transfer, plus utilize AI for content recommendations.

Surveillance

The use of distributed cloud in conjunction with edge computing also makes a lot of sense for the surveillance industry. Smart surveillance cameras capture up to 400 GB of data per month but surely, using such devices for citizens’ safety makes more sense when there is a whole network of devices in a city.

It should also be able to instantly process and analyze data with the help of object recognition, and here is where a distributed cloud and edge computing can promise better bandwidth.

Conclusion

The usage of distributed cloud can promote better efficiency for data management and transfer. Edge computing, in turn, is the logical response to distributed cloud adoption and increased amount of data generation. It is ideal for businesses that need to process data in real-time and make instant decisions, for example, with the help of decision intelligence.

Infopulse experts can support you along the way to distributed cloud adoption, develop an intelligent cloud data migration strategy and power your IT ecosystem with additional technologies that will help you unlock even more business benefits. Contact us to embrace the cloud!

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