Edge automation: Seven industry use cases and examples

Put simply, edge computing is computing that takes place at or near the physical location of either the user or the source of the data being processed, such as a device or sensor.

By placing computing services closer to these locations, users benefit from faster, more reliable services and organizations benefit from the flexibility and agility of the open hybrid cloud.

Edge computing challenges

With the proliferation of devices and services at edge sites, however, there is an increasing amount to manage outside the traditional operations sphere. Platforms are being extended well beyond the datacenter, devices are multiplying and spreading across vast areas, and on-demand applications and services are running in significantly different and distant locations.

This evolving IT landscape is posing new challenges for organizations, including:

• Ensuring they have the skills to address evolving edge infrastructure requirements.

• Building capabilities that can react with minimal human interaction in a more secure and trusted way.

• Effectively scaling at the edge with an ever increasing number of devices and endpoints to consider.

Of course, while there are difficult challenges to overcome, many of them can be mitigated with edge automation.

Edge automation benefits

Automating operations at the edge can reduce much of the complexity that comes from extending hybrid cloud infrastructure so you are better able to take advantage of the benefits edge computing provides.

Edge automation can help your organization:

• Increase scalability by applying configurations more consistently across your infrastructure and managing edge devices more efficiently.

• Boost agility by adapting to changing customer demands and using edge resources only as needed.

• Focus on remote operational security and safety by running updates, patches and required maintenance automatically without sending a technician to the site.

• Reduce downtime by simplifying network management and reducing the chance of human error.

• Improve efficiency by increasing performance with automated analysis, monitoring and alerting.

7 edge automation examples

Here are some industry-specific use cases and examples that demonstrate the value of edge automation.

1. Transportation industry

By automating complex manual device configuration processes, transportation companies can efficiently deploy software and application updates to trains, airplanes and other moving vehicles with significantly less human intervention. This can save time and help eliminate manual configuration errors, freeing teams to work on more strategic, innovative and valuable projects.

Compared to a manual approach, automating device installation and management is generally safer and more reliable.

2. Retail

Establishing a new retail store and getting its digital services online can be complex, involving configuration management of networked devices, configuration auditing and setting up computing resources across the retail facility. And once a store is set up and open to the public, the IT focus shifts from speed and scale to consistency and reliability.

Edge automation gives retail stores the ability to stand up and maintain new devices more quickly and consistently while reducing manual configuration and update errors.

3. Industry 4.0

From oil and gas refineries to smart factories to supply chains, Industry 4.0 is seeing the integration of technologies such as the internet of things (IoT), cloud computing, analytics and artificial intelligence/machine learning (AI/ML) into industrial production facilities and across operations.

One example of the value of edge automation in Industry 4.0 can be found on the manufacturing floor. There, supported by visualization algorithms, edge automation can help detect defects in manufactured components on the assembly line. It can also help improve the safety of factory operations by identifying and alerting hazardous conditions or unpermitted actions.

4. Telecommunications, media and entertainment

The advantages edge automation can provide to service providers are numerous, and include clear improvements to customer experience.

For example, edge automation can turn the data edge devices produce into valuable insights that can be used to improve customer experience, such as automatically resolving connectivity issues.

The delivery of new services can also be streamlined with edge automation. Service providers can send a device to a customer’s home or office that they can simply plug in and run, without the need for a technician on site. Automating service delivery not only improves the customer experience, it creates a more efficient network maintenance process, with the potential of reducing costs.

5. Financial services and insurance

Customers are demanding more personalized financial services and tools that can be accessed from virtually anywhere, including from customers' mobile devices.

For example, if a bank launches a self-service tool to help their customers find the right offering — such as a new insurance package, a mortgage, or a credit card — edge automation can help that bank scale the new service while also automatically meeting strict industry security standards without impacting the customer experience. 

Edge automation can help provide the speed and access that customers want, with the reliability and scalability that financial service providers need.

6. Smart cities

To improve services while increasing efficiency, many municipalities are incorporating edge technologies such as IoT and AI/ML to monitor and respond to issues affecting public safety, citizen satisfaction and environmental sustainability.

Early smart city projects were constrained by the technology of the time, but the roll out of 5G networks (and new communications technologies still to come) not only increase data speeds, but also makes it possible to connect more devices. To scale capabilities more effectively, smart cities need to automate edge operations, including data collection, processing, monitoring and alerting.

7. Healthcare

Healthcare has long since started to move away from hospitals toward remote care treatment options such as outpatient centers, clinics and freestanding emergency rooms, and technologies have evolved and proliferated to support these new environments. Clinical decision-making can also be improved and personalized based on patient data generated from wearables and a variety of other medical devices.

Using automation, edge computing and analytics, clinicians can efficiently convert this flood of new data into valuable insights to help improve patient outcomes while delivering both financial and operational value.

Red Hat Edge

Modern compute platforms powered by Red Hat Edge can help organizations extend their open hybrid cloud to the edge. Red Hat Edge represents Red Hat’s collective drive to integrate edge computing across the open hybrid cloud. Red Hat’s large and growing ecosystem of partners and open methodologies give organizations the flexibility they need to build platforms that can respond to rapidly changing market conditions and create differentiated offerings.

Red Hat Edge consists of a portfolio of trusted enterprise open source software — such as Red Hat Enterprise Linux, Red Hat Ansible Automation Platform and more — that can help you implement a layered-security approach for better risk management on-premise, in the cloud and at the edge. 

By adopting Red Hat Edge technologies, customers can use Red Hat’s portfolio of open source platforms and its extensive partner ecosystem to assemble flexible solutions for:

• Delivering a more security-focused and scalable modern infrastructure from edge to core to cloud.

• Solving edge computing challenges and supporting innovative use cases.

• Avoiding vendor lock-in and building a more sustainable platform.

• Building an agile edge platform capable of adapting to shifting market demands.

• Adjusting to market conditions and developing competitive differentiators.

Learn more

• Red Hat's vision for edge computing

• What's new in Red Hat Enterprise Linux 9 for edge computing

• How to explain edge computing in plain English

• Automation mesh explained: Scalability and reliability for the hybrid cloud and the edge