Cloud Computing vs. Edge Computing

Cloud Computing vs. Edge Computing

Like IoT, machine learning, and 5G, cloud computing and edge computing are most discussed in the business and tech world these days. The cloud and edge computing both are technologies that supplement the traditional data center and help in resource utilization and management optimization.

Cloud computing has become a massive thing these days, and many companies, whether small or large, are using it. Edge computing on the other side provides a cloud-based mechanism, but it brings the cloud server to the end-user rather than taking the computing to the cloud server. But, it has to be kept in mind that both technologies are not ideal for every organization or scenario. Use cases play a major factor in which deployment model makes the most sense of certain workloads, and before deciding whether to use cloud or edge, one must understand the cons and pros of both technologies. Let’s look at the nuances of both the technologies and see who is more likely to replace the other, as some people expect. 

Cloud Computing 

Cloud computing means using remote data centers or servers for storing, processing, managing, computing, and analyzing a huge amount of data. It also includes the delivery of different services over the internet i.e. data storage, servers, databases, networking, and software. Due to remote data centers, there is a time lag between data collection and processing, which is unnoticeable in most use cases. But, in time-sensitive apps, this time-lag measured in even milliseconds, becomes essential. 


  • Highly dynamic flexible resource provisioning.
  • Highly virtualized.
  • Disaster recovery
  • Pay per user


  • There still remains a resource ceiling.
  • Difficulties in dealing with more physical aspects of an environment.
  • Public clouds aren’t generally connected to the more physical needs of an organization through high-bandwidth links.

Edge Computing

As compared to cloud computing, edge computing moves the networking, compute, and storage closer to the source of data. Hence, it significantly reduces the travel time and latency. Instead of continuously transferring data back and forth, the processes take place near the device, or at the edge of the network. This is how it allows faster response times. Applications working on edge computing reduce the volumes of data to be transferred, the distance that data travels, as well as the traffic that results from the transfers. 


  • It places data intelligence closer to where it’s needed.
  • Minimizes data transfers across the broader network.
  • Enables a more “onion skin” approach to data transfers to be enacted.


  • Defining the edge.
  • False positives and negatives.


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