What Is a Distributed Cloud?

Distributed cloud basically uses a fresh approach in cloud computing wherein a public cloud infrastructure can make use of distributed cloud computing architecture that enables it to store and process data in various data centres that may be located far off physically. This means that even though the processing workload and all relevant data are distributed across data centres, it continues to work as one for the users. In a distributed cloud architecture, users can only access a part of the cloud that contains all the relevant data. This data can be delivered almost in real-time as the distributed cloud cluster is generally located in fairly close proximity to the location where the request was generated. If you are looking for help to manage your Distributed Cloud Network more effectively, please reach out to Managed Cloud Services Fresno.

Advantages of Distributed Computing

Scalability and Modular Growth

Distributed systems have the advantage of being able to scale horizontally as the work is spread across multiple systems. This allows users to add or remove a machine to handle the workload efficiently as per demand. And there is no limit to this kind of horizontal scaling. Even the capacity allocation can be automated. When the system faces high workload pressure, it can utilize all the machines connected to the architecture at their full capacities but also wind down when the demands are low and even take machines offline to save on resource usage.

Fault Tolerance and Redundancy

Since the workload is distributed across multiple machines, distributed systems turn out to be more resilient and tolerant of faults compared to single machines. If a service makes use of multiple machines across multiple data centres, it can continue providing the service without disruptions when one system or even a data centre goes out of action. While this does result in increased strain on the rest of the machines, it does not affect performance.

Low Latency

The distributed system containing nodes in disparate physical locations provides users with the added advantage of low latency as the traffic is generally directed to a node that's closest to the user. This also results in a higher quality of performance. However, if the user requires multiple nodes to run at the same time, this can lead to higher costs and more complexity.


Distributed systems often turn out to be more cost-effective when compared to humungous centralized systems. Even though they may require a higher input cost initially than deploying standalone systems, it also provides users with the added advantage of economies of scale. Since the distributed system uses several smaller computers, they often prove cheaper to operate and maintain in the long run than a large mainframe machine.


Distributed systems can potentially allow users to reduce time spent on solving or computing complex problems or data as the workload is broken into smaller chunks with multiple computers working on them in parallel.

Distributed Cloud Use Cases

Automotive industry

The Automotive industry makes use of distributed clouds as it needs to make decisions in real-time that require faster processing of information with zero latency. Semi-autonomous and self-driving cars assess their environment and current road conditions by capturing data through their sensors in real-time and processing this data to make split-second decisions. As 5G and AI comes into play more prominently in the future of self-driving cars, the computing will involve more complex machinations such as object recognition, data analysis, and decision intelligence features that are deployed in real-time. In such use cases, making use of distributed clouds for instant processing and inputs just makes more sense than waiting for decision-making on traditional systems. IT Support Sacramento offers extensive distributed cloud services for local businesses.


As the healthcare industry makes more and more use of IoT medical devices and sensors, the huge volume of data generated and the complex nature of the data will make it necessary for healthcare companies to use distributed cloud computing. Healthcare is another sector where the ability to instantly make decisions can save lives and prevent harm. The use cases are particularly encouraging when it comes to the use of hybrid clouds and edge computing in delivering in-hospital and at-home patient monitoring. The same can also be leveraged for IoT-based apps and devices that can be deployed to monitor specific symptoms and conditions in patients.


This is another industry where distributed clouds can be deployed along with edge computing for more efficient monitoring of environments. Although smart surveillance cameras are already in use prominently, for effective monitoring of vast spaces such as entire cities and towns, we need more complex networks of such devices that are capable of instant image and video processing for better object recognition and creating system alerts. Distributed cloud workloads can make processing vast amounts of data captured by surveillance cameras much easier while also facilitating real-time image processing and decision-making. For a more in-depth understanding of Distributed And Cloud Computing, please consult IT Support Fresno.

About George:

George Passidakis is the Director of Sales and Marketing at Apex Technology Management, providing IT Consulting Sacramento, Redding & Sacramento. George has 30+ years of experience as an Information Technology professional. He also has extensive knowledge of Microsoft technology and other SMB IT products and solutions. Stay connected via LinkedIn.