Enterprises migrate to the cloud seeking scalability, cost-effectiveness and resilience. But the centralised cloud computing model is inadequate for today’s data-intensive workloads.

Edge computing has become a popular alternative. This distributed form of cloud computing overcomes the limitations of centralised cloud.

Edge nodes process data locally and deliver instant results. The processing occurs in a network of servers and gateways close to the users or devices that generate the data. Any device with a CPU and the ability to process data outside the central cloud server can become an edge node. Edge gateways communicate with the central cloud only for additional processing or long-term storage.  

Of late there is a surge in data generation at the edge. By 2025, the processing of 75% of enterprise-generated data will take place outside traditional centralised data centres or cloud.

Here are the reasons why the cloud edge is soaring in popularity.

Improved Resilience

Network resilience has become critical for businesses in today’s digital age. Customer expectations have increased, and they expect uninterrupted service and rapid problem resolution. A resilient network can recover fast from any disruption.  

One of the main reasons enterprises migrate to the cloud is for resilience. But the traditional centralised cloud models can no longer meet expectations.

The huge data loads can overwhelm the centralised infrastructure, especially during peak hours or heavy use. Hardware failures, software bugs, cyberattacks, and natural disasters can cause outrages or downtime.

The cloud edge decreases such risks and makes the network more resilient.

Edge computing offloads traffic from central servers and distributes it to nearby micro-servers. Such a move reduces the load on central servers and eases network congestion. 

The decentralised edge cloud can leverage the computing resources of all smart devices in the vicinity. Often, the combined processing power of these smart devices is even greater than what the central cloud delivers. Dynamic adjustment of edge resources to meet fluctuating demands optimises resource utilisation. 

The cloud edge improves network agility, redundancy, fault tolerance and performance. Any risk of a single point of failure also gets eliminated..

Overcoming Latency

Latency is inherent in the centralised cloud model. Processing data at distant servers and databases leads to delays in transmission. 

Latency was not an issue when the data quantity remained manageable. And not noticeable when a few seconds hardly mattered. But the huge increase in data loads and critical workloads that depend on instant results makes latency intolerable today.

Data volumes now double every two years. In many places, the Internet speeds and network infrastructure do not support the seamless transfer of huge data volumes.  The responses slow down to an extent that degrades the user experience.  

Devices such as IoT sensors, wearables, industrial control systems and more generate tons of data. These data also need ultra-fast processing. 

Consider an autonomous vehicle. The embedded sensors collect data on road conditions, traffic, pedestrians, and obstacles. For the vehicle to not crash, the processing of such data must take place with zero latency.

Online gaming and stock trading likewise need instant responses to maintain their integrity. Even a few milliseconds of latency can make a huge difference to such applications. Delayed responses in stock trading, where prices fluctuate every second, can cause huge losses.

Cloud edge deployments execute real-time analytics near the data source. It relies on centralised cloud resources only for heavy lifting. The result transmits instantly, overcoming latency. Edge servers also cache frequent content and deliver it to users without relying on the central cloud.

Continuing with the example of autonomous vehicles, the processing takes place at the edge nodes closest to the vehicle. These servers identify potential hazards, calculate braking distances, and make steering adjustments. Even a few milliseconds of delays in transmitting such analysis can cause accidents. 

Better Integrations and Improved Flexibility

The edge allows enterprises to manage their devices locally, reducing the dependency on centralised servers. Devices become more autonomous, and enterprises can control and manage their data better.

A big impact area is the integration of legacy systems and silos. 

Silos have always stood in the way of seamless workflows, transparency and analytics. Silos are often associated with legacy systems or exist for security reasons. It is not realistic to eradicate all silos, despite concentrated attempts towards the same.

Edge cloud platforms offer APIs to facilitate seamless data exchange with legacy systems and silos. The edge also supports various connectivity options, such as VPNs and SD-WAN. Such flexibility makes it feasible to collect data from disparate legacy sources.

Innovation and New Revenue Streams

Edge computing allows businesses to unlock value from their data and create new revenue streams. The ultra-low latency and real-time insights catalyse new and innovative business models.

Local data processing improves the performance of virtual and augmented reality applications. For instance, it renders complex visual and auditory effects in real time, allowing for realistic and engaging experiences such as physics simulations and dynamic lighting. Such options unlock opportunities in VR gaming, equipment maintenance, and several other areas. 

Ultra-low latency enables designers in different locations to work simultaneously on a project. Design changes and updates reflect immediately as if everyone is in the same room.

Retail stores leverage edge computing for instant personalisation. A high-definition camera sends the feed to a GPU-enabled edge computing device. The edge-based server analyses customer demographics and behaviours in real-time. The business can deliver dynamic, personalised offers and promotions to visiting customers. Since the data does not get stored in the central databases, privacy issues are reduced.

Improved Security and Compliance

Cloud vendors offer robust security, but cyber attacks are commonplace. The vast attack surface of the cloud makes it vulnerable to attacks. The edge reduces the risks of cyber attacks. Spreading data over many edge locations makes it difficult for attackers to compromise the entire system. The system becomes more resilient to failures and attacks.

Processing and storing data closer to the source minimises data exposure over the network. The attack surface reduces. Also, local threat detection and analysis make responses faster.

Edge locations double up as backups, ensuring business continuity in case of cloud disruptions.

Edge cloud makes it easier to create isolated network environments. Such an environment allows secure connection of legacy systems, without compromising security.

The edge improves compliance as well. Many existing and upcoming legislations mandate localisation and stringent privacy requirements. Cases in point are China’s Personal Information Protection Law and India’s Personal Data Protection Act. Established legislations such as the EU GDPR and California’s CCPA also carry similar provisions. Edge processing keeps the data within the same legal and geographical jurisdiction. Compliance with data privacy and data sovereignty laws becomes easier.

Cost Reduction

Most enterprises embrace the cloud to save costs. The cloud edge allows users to save more than the traditional centralised cloud.

The edge servers, being closer to users, consume less energy than large, centralised data centres.Since data has to move only a short distance, bandwidth costs also reduce.

Harnessing the power of cloud edge gives businesses a competitive edge. Real-time data from the edge helps businesses work smarter and keep customers happier. This deliver indirect cost savings such as reduced waste and lesser load on support agents.

Optimal resource allocation improve asset use ratios.

Cloud edge computing has already found its way into many industries. Healthcare companies use it to monitor patient vitals, make health analyses, and respond to emergencies. Manufacturing industries use the cloud edge for supply chain optimisation and predictive maintenance. Retailers use it for inventory management and personalised marketing. More and more industries and businesses join the bandwagon by the day. The future belongs to enterprises who prioritise a distributed edge-based solution as default.