10 Reasons Edge Computing is the Next Big Thing for Businesses

Edge computing is emerging as a powerful technology that is poised to change the way businesses operate. By processing data where it is generated—at the edge of the network—edge computing provides a host of benefits over traditional cloud and on-premise IT infrastructure models. 

 

As more companies adopt Internet of Things (IoT) technologies and recognize the usefulness of real-time data insights, edge computing will increasingly become the platform of choice.

 

Let’s examine 10 reasons edge computing is the next big thing for business. 

1. Lower latency

• Edge computing allows data to be processed extremely close to where it is generated and needed, such as factory equipment, sensors, point-of-sale devices and more. Instead of transmitting all of this information over networks and waiting for a response from a remote data center or cloud platform, edge deployments put compute and storage capabilities within the local environment. 

• Insightful workflows, predictive forecasting, automated decision making and other latency-sensitive applications can process inputs and react to changing conditions nearly instantaneously.

• The ability to instantaneously gather, compute and respond to information occurring right where value is being created makes edge-based computing a necessity for next-generation low-latency applications and impossible without its localized processing capabilities. Edge allows for an interactive, responsive and frictionless experience across key industries poised for IoT-driven transformation.

2. Improved connectivity

When devices are communicating and being controlled locally instead of routing traffic through a centralized cloud, connectivity issues have much less impact. Even if the cloud connection goes down temporarily due to an outage or congestion, edge devices can continue operating autonomously by using local processing and storage capabilities. This level of resiliency is invaluable for operations that require continuous uptime, such as transportation systems, utilities, and public safety networks.

3. Increased privacy and security

Keeping data localized to edge nodes means less of it needs to be transmitted over public networks, where it would be more vulnerable to cyber threats or unauthorized access. Edge computing architectures simplify compliance with various data privacy regulations by making it easier to keep sensitive user or customer information from leaving intended geographical boundaries. The distributed nature of the edge also provides redundancy against network failures or attacks.

4. Reduced bandwidth costs

When insights are gleaned from data where it is generated rather than needing to upload massive volumes to the cloud, bandwidth demand and associated service fees are lowered significantly. This is a huge incentive for organizations with widely distributed networks of IoT endpoints, such as at retail stores, university campuses, airports and more. Edge also relieves pressure on backhaul networks that would otherwise struggle to transport all the generated data upstream.

5. New location-based services

By bringing more intelligence down to the network edge, innovative location-based applications and contextual services become feasible. Imagine if public spaces like transportation hubs could use on-premise sensors and edge computing to offer customized wayfinding, shopping deals, emergency notifications and more, targeted precisely to each user’s context and location. The promise of these types of spatially aware experiences will drive many new edge use cases.

6. Powerful analytics at the source

While cloud analytics certainly have value, edge computing truly unlocks new potential by bringing intelligence directly to where it matters most—the situation on the ground. With real-time insights available at the source, teams are empowered with a level of insight that would otherwise remain hidden until data is reviewed after the fact in a centralized location.

 

Across industries, edge propels a shift to condition-based and outcome-based models where processes improve continuously rather than reactively. Issues are found and addressed during production rather than after the fact. Resources are optimally allocated based on the real needs revealed by real-time analytics. Overall equipment effectiveness increases, along with customer satisfaction and safety, when intelligence resides at the point of impact. Edge makes proactive operation excellence the new standard.

7. Cloud offload capabilities

Edge computing can be programmed to automatically offload less time-sensitive data, uploads, backups and queries to cloud platforms for longer-term storage and analytics. This hybrid model eases the burden on both edge nodes and centralized cloud resources. Compute tasks too intensive for local devices can also leverage cloud acceleration, while less demanding workloads remain distributed to the edge layer.

8. Lower upfront infrastructure costs

Edge deployments are more modular and distributed by design versus attempting to consolidate all compute in centralized data centers. This disaggregated approach lends itself to a more gradual, pay-as-you-grow rollout aligned with demand patterns. It avoids large upfront investments and lowers risks, while the costs of edge nodes themselves are declining as the technology matures.

9. Faster implementation and scaling

Edge computing has a major advantage in that it can be provisioned in a flexible, modular way to align precisely with business needs and growth patterns over time. Whereas cloud migrations typically require enterprises to predict maximum future utilization upfront and scale their entire environment all at once accordingly, edge infrastructure lends itself to a more phased, incremental approach.

• Companies deploying edge are able to start small at initial locations where data insights are most time-critical or network density is highest. 

• They can then monitor usage trends and expand out to new areas in strategic stages, activating edge capacity only where analytics have validated clear return on investment potential. 

• This allows optimization of spending at each phase based on validated ROI. Additionally, edge infrastructure already installed at location X can easily be upgraded with more powerful processors or expanded storage as analytics workloads intensify over time.

10. Future-proof architectures

Built with decentralized intelligence in mind from the ground up, edge networks are well positioned to take advantage of coming technological disruptions like 5G networks, advancements in distributed ledgers, and the proliferation of AI and ML capabilities out to the last mile. Businesses leveraging edge as their platform of choice today will be ahead of the curve as these upcoming innovations reshape digital possibilities.

 

Conclusion

As more sensors, devices and systems produce data for integration into digital workflows and decision-making processes, the limitations of moving it all to centralized cloud infrastructures will become apparent. Edge computing offers an optimized model accounting for the realities of exponential data growth, the strict performance needs of modern applications, and regulatory and privacy concerns driving localization requirements. For these reasons, edge will undoubtedly become a foundational technology, enabling tomorrow’s businesses to harness valuable insights from their own distributed operations.

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