Innovations across industries and geographies are driven by smart decisions derived from data, thanks to the proliferation of connected devices and the intelligent insights captured via cloud-enabled AI/ML and IoT ecosystem.
Today, companies are investing in Edge Computing to realize strategic business objectives, such as exponential growth, new market penetration and enhanced customer satisfaction.
Hybrid cloud computing now forms a vital element in the enterprise digitalization journey, along with being a key driver for edge-based computing models.
Today, companies are investing in edge computing to realize strategic business objectives, such as exponential growth, new market penetration and enhanced customer satisfaction. A smart edge-based computing model distributes and decentralizes cloud computing by taking it closer to where the data is collected, reducing latency issues, and improving business agility.
Edge computing – Key drivers and use cases
Advancements in new-age technologies like AI/ML and IoT are enabling enterprises to harness the potential of enormous volumes of raw data. As per IDC, “By 2025, around 25 billion devices will be connected to the internet, increasing IoT-generated data to 163 Zettabytes”. Analyzing data stored across centralized data centers can often be time-consuming. Moving to edge computing will help enterprises perform instantaneous action by enabling data to be analyzed closer to its source. This will also save cost, as the most crucial data can be selectively identified and moved to the cloud.
The telecom sector is seeing a tectonic shift, with virtualized network functions disintegrating from proprietary hardware supporting the open stack architecture. This is enabling the secure deployment of 5G network at an accelerated pace. Across the globe, governments are beginning to lease out radio spectrums for 5G, allowing its deployment in both public and private networks. This is seen as a great technology disruptor, and as it promotes advanced connectivity use cases, enterprises are leaning on cloud and edge networking and computing capabilities to harness the potential of superior connectivity with ultra-reliable low latency, device mobility, and network slicing.
5G can help accomplish technology-led innovations, such as advanced VR/AR, robotic surgeries, autonomous vehicles, real-time management of the distributed energy sources, and more a reality. Communication service providers, in the past, struggled to reshape their underlying architecture and were forced to stay with proprietary OEM vendor lock-in solutions. They can now enable cloud-to-edge networking to mitigate slow response time to sensitive data at remote and edge locations.
Apart from the smart sensors in the manufacturing industry, there is a plethora of edge computing use cases driving the next era of Industry 4.0. It could be the next smart car emitting performance data, a connected handheld device, an advanced digital camera in a retail store, or any smart application on your phone sending sporadic data and capturing the next level of user and mobile experience. Such possibilities are virtually limitless, and thus, it becomes imperative to think out of the box and shift towards a decentralized smart hybrid approach.
HCLTech built a smart edge-based image analytics platform for one of its largest rail freight services clients to help them improve on the manual, time-consuming, and error-prone railway track monitoring and maintenance system. Vehicle-mounted ruggedized edge and customized algorithms were used to detect and capture the defects and anomalies in the tracks in real-time. Such feed was then geotagged on each occasion, filtered, and sent to the cloud for deeper analytics and storage capabilities.
Enterprises are gradually and smartly embracing edge computing in order to capture, collect and convert raw information into meaningful business insights and deliver an enhanced customer service experience.
EdgeLITy - Filling the digital void
HCLTech understands the importance of cloud-driven cultural shift within organizations focused on leveraging the native services and functionalities of the hyperscaler ecosystem. A multi-cloud adoption strategy with platform agonistic solution promotes the sense of consuming the best from the available stack, both on-premises and cloud. With EdgeLITy, HCLTech has built an end-to-end, holistic framework to cater to the needs of fast and agile information processing at the edge and to leverage cloud-based services on demand.
EdgeLITy’s block-based architecture offers agility by absorbing the existing infra components of customers’ ecosystem in their brownfield deployments, ensuring a continuation of returns on existing infrastructure wherever possible. By providing widespread support for protocols and plugged-in, smart, industry-ready solutions, EdgeLITy offers a head start to organizations in their digital and edge-to-cloud transformations. Allowing flexibility and choice at the edge as per user demand and criticality of the desired output, HCLTech offers three smart variants of EdgeLITy – Lite, Smart and Power.
EdgeLITy Lite – This is a basic, lighter version of EdgeLITy that provides connectivity to the cloud for users with lesser demand for real-time inference of data sets and more focus on the extraction and building of data lakes.
EdgeLITy Smart and Power – These variants are designed to focus on generating real-time and near real-time value out of the captured data sets in the system. Both the variants hold powerful yet concise infra footprint to store, churn and send transformed and filtered inputs for final action.
EdgeLITy’s edge-as-a-service model makes it commercially feasible and competitive, assisting organizations reap the benefits of data modeling and data science, coupled with best practices around Infra and IoT. With years of experience in specialized verticals, HCLTech’s experts have crafted and developed 19+ patents across verticals to help its customers envisage their journey of edge transformation.
Due to its vendor-agnostic approach, HCLTech has developed an architecture built to support OS and containerize the platform on any GPP-based edge devices of an x86 platform. The onboarding process can be fast-tracked by leveraging features, such as single pane of glass to deploy and the option to manage and upgrade your edge devices with a few clicks. This engineered solution is compiled with validated designs, tested and built in our state-of-the-art IoT labs from IoT WoRKS™. A strategic partnership can enable enterprises to make a smart move to the edge and ensure a smooth ride on the new wave of edge-based transformation.
To know more about EdgeLITy, email us at firstname.lastname@example.org