Edge computing is transforming the way data is being handled, processed and delivered from millions of devices around the world. The explosive growth of internet-connected devices – the IoT – along with new applications that require real-time computing power, continues to drive edge-computing systems.
Faster networking technologies, such as 5G wireless, allows edge computing systems to accelerate the creation or support of real-time applications, such as video processing and analytics, self-driving cars, artificial intelligence and robotics, to name a few.
OpenGov Asia had a chance to speak exclusively to Brent Schroeder, Chief Technology Officer, SUSE to discuss how edge computing provides smart cities with real-time data to improve their efficiencies.
Brent has a strong track record of bringing products from conceptualisation through to commercialisation. He is responsible for shaping SUSE’s technology and portfolio strategy in support of emerging use cases in areas such as Hybrid Cloud, IoT and AI/ML. He also drives the technology relationship with numerous industry partners, participates in open source communities as well as evangelising the SUSE vision with customers, press and analysts.
Brent acknowledges that there are some challenges with regards to cloud computing. The high costs usually associated with edge computing is of concern to companies and the public sector. Configuration, deployment and maintenance of an edge computing framework are expensive. To ease the worry of the public and private sectors, adopters need to keep in mind two key aspects when managing concerns regarding costs of edge computing.
The first is to identify focused projects that have a clear return on investment. Starting with value to the business gets quicker alignment and buy-in from all stakeholders that benefit from the outcome. Rather than building an edge programme from the get-go, organisations must learn how to conduct a focus project first. The return could be financial in improved throughput or efficiency for the organisation; client retention through improved experience and satisfaction; or even societal returns by improved traffic management or safety/security.
The second aspect is to utilise a cost-effective solution. Brent does not recommend highly custom solutions built on proprietary software. This creates lock-in, does not leverage industry scale and ultimately can lead to higher costs. Implementers should look to leverage open source solutions as much as possible to help improve the overall costs and provide the greatest flexibility.
Organisations need to engage service providers that have direct experience in edge computing. Collaborating with experts helps architect the usage of edge solution to achieve the business goals. It is important to understand the technology’s capabilities and if the solution it provides fits the problem to ensure alignment.
For example, Brent elaborates, if the edge application is processing large volumes of image data looking for anomalies, they would choose a different technology than a system that is processing movement data from a robotics environment that is designed to optimise factory automation. Collaboration among the teams helps to bring together the business requirements with the right technical capabilities.
Businesses must be equipped to efficiently manage between data that is important in edge operations versus the long-term, Brent feels. The key value proposition of edge computing is how technology continues to change, as against trying to use a centralised solution whether in a company data centre or cloud.
Edge data management technologies can be used to build real-time analytics taking advantage of large volumes of data to drive smart city actions. There is a lot of data involved in edge computing, not all of which are used for operations of smart cities. Open-source technologies such as Apache Kafka and Spark are often used for processing at this point. Once real-time processing is complete, further analysis and filtering of the data can be done at the edge, discarding unnecessary data and forwarding essential data to a centralised, cloud-based data lake for further analytics.
In terms of security using edge computing, Brent conceded that for edge solutions to be effectively governed, companies must employ automation at all levels of the infrastructure and applications to ensure continuous compliance with policies, best practices, and the latest security updates. Automation helps on two fronts – it minimises the human element for managing change and provides continuous monitoring of critical infrastructure and application, something humans cannot do on a practical level.
Key concepts people may have heard of that are required to implement automation to this level are Infrastructure as Code and Policy as Code. SUSE’s portfolio utilises both these concepts to help companies implement automation at multiple levels.
First, within the compute infrastructure SUSE Manager protects businesses with an automated system that proactively manages against the standards they define – so they can easily meet security and compliance requirements while maintaining healthy, available services. For the application infrastructure, as companies take advantage of cloud-native computing at the edge, the SUSE Rancher product line lets companies automate processes and applies a consistent set of user access and security policies for all the Kubernetes clusters, no matter where they are running.
Brent added that there is a shift in skillset occurring with the adoption of cloud-native technology, which is the fuel that drives Edge to make it cost-effective. Companies will need to look for applicants that are well versed in not only the technologies but its techniques and processes. Specifically, skill in DevOps principles, microservices, and the new security requirements. Candidates skilled in these elements will adapt to a variety of technologies that can be used to implement secure cloud solutions.
Regarding specific technologies, Kubernetes experience is the most universal need. Organisations should begin hiring a core team of members who understand Kubernetes and related cloud-native computing technologies.
A shortage of these technically skilled people and the surge in technologies is a very real issue. The remedy is to combine hiring a core group of team members with these new skills, with an internal training and mentoring programme. Engineers appreciate the opportunity to learn new skills, and what better way to improve employee satisfaction than providing career refreshment and growth opportunities.
Brent concluded that organisations could reap the full benefits of Edge Computing by building teams with a combination of new, skilled talent and existing team members who are already familiar with the organisational requirements. In the end, both will benefit from each other’s skills and experience resulting in greater overall productivity and satisfaction.
