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Edge Computing

Is The Cloud On ‘Edge’? Dissecting Edge Computing’s Long-Term Impact On Cloud Strategy

Nastel Technologies®
June 1, 2020

The buzz around new technologies is inescapable, and edge computing is the latest buzzword. The pundits make it sounds fantastic, describing it in multiple ways and touting its numerous use cases. One notion exists that edge computing could even replace all traditional, more centralized cloud computing models. Let me stop you right there: Not going to happen.

Edge computing is a natural complement to cloud computing and vice versa, not a replacement. Edge computing solves network latency limitations, while cloud computing offers faster and cheaper centralized compute and storage for significant workloads. These workloads include AI, data analysis and machine learning – all which have proven to be vital in our current COVID-19 environment as discussed in my previous article “How To Leverage Artificial Intelligence And Machine Learning During A Pandemic.”

The technology environment of the future will likely have features of both traditional cloud computing and edge computing in a hybridized construct. It is truly yin and yang, as each approach overcomes the weaknesses of the other.

Everyone Wants an Edge

As we look at the industry, technology trends are lining up to embrace the power of edge cloud and the cloud itself in a continually evolving world of multi-cloud hybrid enablement. The examples abound in the emergence of the Internet of Things (IoT), self-driving vehicles, streaming media and other industries where network latency is a deal-killer, and sometimes a real killer in the case of self-driving vehicles.

The demand for modern cloud-native, consumption-based, hybrid-friendly cloud platforms will only increase as legacy IT workloads continually transition to agile cloud systems. Gartner reports that 61% of enterprises are showing IoT maturity. Below are some examples of how edge cloud is working today to help reduce latency and improve the user experience across the retail, medical and manufacturing industries. 


In the retail market, systems that track sales, strategy, and information are distributed in non-traditional methods, perfect for an edge deployment strategy. According to Grandview Research, IoT in retail will be a $95 billion market by 2025. Retailers will use IoT and edge computing for faster and better customer experiences, reducing lines, and increasing revenue. Leveraging edge-ready situations such as autonomous checkout, product tracking, sensor tracking, and supply chain reporting will be highly used in a post-COVID world.


IoT in the medical field is expected to be a $534 billion market by 2025. Pharmaceutical operations can answer challenges such as inventory management, increased complexities due to regulations and visibility through proximally placed systems that collect and process data near instantly.


In manufacturing, productivity and safety are being improved by minimizing downtimes, introducing sensors, and monitoring changing process conditions through a localized edge computing strategy. That IoT market is forecasted to be higher than retail and healthcare combined at $950 billion in 2024.

More Capacity for Innovation and Adoption

The amount of consumption and expectations of experience means that the scale and capabilities of edge computing will be even more critical than ever before. Latency-sensitive information is increasing, and technology providers are loading up with solutions such as Microsoft’s Azure Stack Edge, which comes prepared for artificial intelligence tasks and can act as a storage gateway. To call out another example, AWS adds services such as Snowball Edge into the equation, striving to make the world of IoT and edge computing much smaller through the capabilities of rapid data transport.

In many ways, computing has always existed at the ‘edge.” Branch offices and remote locations held data and storage for decades on small servers and networks. The difficulties came in the management, latency, and cost of protecting and implementing that data into IT systems. Now, cloud systems provide infrastructure and service capabilities that are reliable, agile, and ready for use.

When considering edge cloud computing, we need to consider it as part of an overall hybrid cloud strategy. Edge computing is an enhancement as part of a comprehensive cloud strategy, that can sustain the rapid, explosive growth of IoT device deployments.

This article originally appeared on To read the full article and see the images, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • zAdvanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering tools for Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT, IBM Cloud Pak for Integration and many more.


The Nastel i2M Platform provides:


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