Edge Computing is getting popular due to the massive explosion of data through the Internet of Things (IoT) and huge compute and storage demands of cloud users. No one expected AWS to have $13 billion business within such a short span of time. All the big players including IBM, Microsoft and Oracle to name a few, and the smaller ones wanted to have their own versions and offerings for public cloud.
Grey ‘Cloud’: The Challenge
Can public or private cloud provide a realistic and economic option considering the data volumes and the performance needs? A networking giant predicts that the worldwide cloud traffic will hit 14.1 ZB per year by 2020. Adding up the mobile computing needs to this mix, cloud may not be a good fit for all the Big Data processing scenarios.
The massive amount of raw, unprocessed data gathered through IoT devices or applications needs to be moved to the cloud for processing. This, of course, overloads the network, causing performance issues for application users. Also, there are compliance regulations that need to encrypt or mask sensitive data that’s being shipped to the cloud, which is then sent back. Depending on the volume of these results, there will be a network impact and latency in receiving the results. All this is accepted by businesses. Why? Because there are no better options.
Edge Computing can prove to be an option
What Is Edge Computing?
Edge Computing is defined as a distributed architecture in which user data is processed at the verge of the network, as close to the source as possible. Real-time data in Edge Computing architecture can be processed at the point of origin by an intelligent device or sent to an intermediary to be processed in real-time. This data can be aggregated or summarized to reduce the volume, before sending it to cloud for further processing. Less time sensitive or low volume data can be sent directly to the cloud for historical analysis, Big Data analytics and long-term storage. Mobile computing, the decreasing cost of computer components, and the sheer number of networked devices in IoT are driving the move towards Edge Computing.
Mobile-Edge Computing
Cloud computing capabilities within the Radio Access Network (RAN) that is in close proximity to mobile subscribers are provided by Mobile Edge Computing. The RAN availability provides an environment with the ultra-low latency and high bandwidth as well as direct access to real-time radio network information that can be used by applications and services to offer context-related services, enhancing the mobile broadband experience. This also allows content, services, and applications to be accelerated, increasing performance and responsiveness from the edge.
Relevance to HCLTech
So, how is this relevant to HCLTech? HCLTech has a really strong market presence in the on-premises infrastructure segment. It has a large number of worldwide customers, whose infrastructure is managed by HCLTech within their own datacentres or in some cases within a HCLTech-managed datacentre. HCLTech also has a growing cloud practice with public and private cloud computing offerings. There are expert HCLTech resources within HCLTech who manage all these environments.
What’s missing is an Edge Computing offering that can marry resources from both of these environments to provide a more effective usage of infrastructure. The resulting throughput will demonstrate the use of this concept to the clients and help them get the best ROI.
