Reducing Operational Costs and Enhancing Data Security By Janifha Evangeline

Reducing Operational Costs and Enhancing Data Security

Janifha Evangeline | Saturday, 08 October 2022, 13:57 IST

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Amit Luthra, Managing Director - India, Lenovo ISG (Infrastructure Solutions Group) in interaction with CIOTechOutlook, shares his views on how businesses can optimize their IT expenses by processing data locally rather than in cloud.

The worldwide edge computing market is projected to reach USD 274 billion by 2025. How do you see this market evolving in India?

In today’s digital-first business era, organizations have realized the need to be agile and innovative to stay ahead of the curve - that means using data-driven intelligence to deliver better customer experience and value. With an increasing volume of data, businesses must have the right infrastructure to derive valuable insights and make real-time accurate decisions. This gets critical in sectors such as Retail, Supply Chain, Healthcare, Manufacturing, etc. where faster insights can significantly improve operations and value to the end customer.

Edge computing is eliminating these challenges by processing data at the edge of the network, instead of sending it all the way to the cloud for processing and storage. For example, retailers can use edge computing to tailor their advertising and marketing efforts to better address their customers’ preferences and recommend new products or offers based on their purchasing decisions because it helps evaluate data into customers’ purchasing histories that are either in-store or nearby.

Furthermore, increased usage of IoT technology and the deployment of 5G are expected to create massive amounts of data, creating an opportunity for edge computing to become more mainstream across businesses and industries in India. Therefore, we expect a steep growth in the adoption of edge computing in India.  

 

Enterprises today are rapidly moving towards digitalization by adopting emerging technologies to automate and accelerate their business processes efficiently. Please elaborate on how Edge computing will reduce data transmission and storage costs through localized processing.

IDC’s Global DataSphere indicates that data is expected to grow more than double in size till 2026. CIOs will have a more prominent role in managing this data expansion as IDC predicts that enterprise data will grow twice as fast as consumer data. Our ‘always-evolving’ IT requirements and the expected growth of data will create an uphill task in the management of CAPEX & OPEX - a priority for CIOs.

Processing data at the edge is more cost-effective than managing workloads in the cloud, since it offers local data storage & processing, and helps in avoiding the need for large volumes of data to travel from the source to the cloud or data centre. This will not only cut costs but also enable CIOs to better utilize cloud and data centre resources for other workloads. Furthermore, managing workloads at the edge of the network also means a reduced need to scale up cloud and data centre infrastructure, which offers another layer of cost savings in overall IT spending.  

 

With the increasing adoption of multi-cloud infrastructures within the organization, establishing a reliable edge network to handle the network traffic from multiple nodes will be a challenge. Also, most IT managers are facing challenges in finding a suitable solution and cloud vendors that can address the high bandwidth requirements, as well as redundant data reporting. What kind of solutions can help in addressing these challenges?

There are many solutions CIOs can implement to establish a reliable edge network to handle the network traffic from multiple nodes. The software-defined networking (SDN) approach helps to eliminate the underlying hardware and provides a more flexible method of configuring the network. Deploying more powerful and efficient routers and switches at the edge of the network and increasing the bandwidth of the network connections could also help to address this challenge. 

When it comes to high bandwidth requirements, businesses can use a content delivery network (CDN) to help improve remote data access by caching content on servers located around the world. This way data can be accessed from a nearby server, which can help improve performance.  

 

Please elaborate on how the rise of AI workloads and ongoing enterprise adoption of hybrid computing strategies is fueling demand for edge servers.

AI relies on data transmission and computation of complex ML algorithms. Edge computing establishes a modern computing paradigm that moves AI and ML to the network’s edge, where data collection and computation happen. AI at the edge allows faster computing, better data security, and control over continuous operations. That means, it can improve the performance of AI applications and save on operational costs. As businesses save on time and cost to insights, there will be growing trust in edge computing and its potential in reshaping the way we conduct business. Edge, coupled with IoT is also very critical in realizing and enabling smarter cities.

 

While edge computing hardware needs to be rugged; compact; and have sufficient storage, connectivity, and power range, it must also meet various other requirements as they are often deployed in tough environmental conditions. Therefore, what kind of solution will help in meeting these requirements?

Apart from the need for edge computing hardware to be rugged, compact, and have sufficient storage, connectivity, and power range, it must also be able to operate in tough environmental conditions. CIOs must consider the following solutions while implementing edge computing:

Rich I/O ports: A rugged edge computer must be equipped with rich I/O ports because they must often connect to both new and legacy factory machinery, devices, and equipment.  

Trusted Platform Module: To ensure security they must also be equipped with the Trusted Platform Module (TPM) 2.0.  

Versatile mounting options: As edge computers are deployed in space-constrained environments, they should have versatile mounting options such as wall mounting, ceiling mounting, bookshelf mounting, DIN rail mount, and VESA Mount. 

 

Gartner estimates that 75% of enterprise-generated data will be processed at the edge by 2025 and 80% of enterprise IoT projects will incorporate AI by 2022. How do you see the market for edge computing in the near future?

In today’s digital-first business era, leaders focus on improving customer experience, reducing operational costs, and enhancing overall efficiency. The technology must be agile, secure and flexible for IT infrastructure to help organizations grow. Services across industries empowered by IoT technology require high compute power to process large amounts of data in real time and help make decisions instantaneously. As the volume of data increases, businesses will need to deploy edge computing solutions to gain a competitive advantage. Three key factors that will power the adoption of edge computing in India:

Data optimization: Better analytics capabilities allow businesses to receive technical data optimized for better consumption and per the business requirements. 

Reduced OPEX: Edge will significantly improve delivery time; reduce the cost implications of additional bandwidth and latency-related investments  

Value to Data through AI at the Edge: Enhanced computing power will allow businesses to use AI capabilities to process data smartly, allowing intelligent data to flow into the system. 

 

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