SixSq: Monetizing edge computing with Nuvla.io marketplace for app vendors

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SixSq: Monetizing edge computing with Nuvla.io marketplace for app vendors

SixSq, a software-as-a-service (SaaS) provider for edge computing, started out by building a solution for managing edge application deployments. The company has successfully helped customers ranging from the European Space Agency to non-profit organizations deploying a clinic management application for doctors in remote areas.

SixSq, which was acquired by Ekinops in late 2021, has also been helping to drive software revenues for its parent company, which saw revenue top the €100m mark for fiscal 2021.

Now the company is widening the reach of the edge to more customers with an app marketplace — one that is gaining traction where others have failed to take off.

The company’s Nuvla.io App Vendor Program is described as a B2B digital platform for the industrialization and automation of containerized edge applications and device management. Vendors can sell their edge apps to customers and update their software through the Nuvla.io platform.

Edge Industry Review recently spoke to Marc-Elian Bégin, co-founder and CEO of SixSq to talk about the role marketplaces will have in the growth of the edge computing market.

The following comments from the interview have been edited for length and clarity.

EdgeIR: Can you give us some background on the company, how and why it was started, and describe what you currently offer?

Marc-Elian Begin (MB): I was working at CERN, the European lab for particle physics. Amazon had just announced the cloud and I thought it was really interesting. People I worked with at CERN were more focused back then on grid computing. I did a research paper that predicted grid computing would be an application that could be deployed on the cloud, as a more generic form of computing. Now, CERN is one of the biggest users of cloud computing.

In the process, with my wife and a friend also working at CERN, I laid the foundation of what would become SixSq in 2007. The company is about facilitating application deployment and helping people take advantage of those types of new infrastructure that have loads of benefits, but are still quite complex to use, operate, scale and manage.

We operated the company as a healthy SME for a few years before pivoting in November 2018 to focus on edge computing with a platform that would be delivered as B2B SaaS.

Recently, we added the marketplace concept of business apps. Vendors can actually deploy and sell, and customers deploy business-ready applications at the edge and in the cloud.

EdgeIR: How is the edge computing market developing this year for you? What are some of the key market verticals that you’re interested in?

MB: The ones that we are closing on this year include transport and manufacturing. We’re helping public transport companies deliver better services around stops, communicating with drivers, and virtualizing a lot of the functions that are running now in the tram, bus and train, and at stops.

In terms of manufacturing, it is really about understanding the process of building things — the assembly lines, and so on — and it’s simplifying deploying machine learning applications on the factory floor, or inside of warehouses and so on. Another market we’re working on is energy, including smart grid, which gives the ability for customers, and even citizens, to trade on the public grid.

EdgeIR: Software marketplaces invariably get compared to those such as AWS Marketplace. What sets yours apart from what the cloud providers are doing?

MB: Most marketplaces out there are really placeholders, right? There’s still a big gap in the true automation capability of those platforms to deliver business-ready outcomes.

Because we’re edge first, as opposed to the hyperscalers that you’re describing, we’re able to let the vendor help their customer — through our platform — deploy to the edge, and that edge part will connect to a SaaS platform that the vendor manages. The customers really have a complete finished application deployment at the end of a few button clicks. The edge first focus is also what gives that space for those vendors to play the edge under terms that are more favorable for them. That’s much harder to do on hyperscaler marketplaces.

Still, even with an edge first focus, you’re always at the edge of something, right? You can’t be at the edge of nothing. That thing, 99% of the time, is the cloud.

Microsoft, for example, has an IoT Hub; it’s their way of gatekeeping data that comes from the edge to power all of the AI features that they need to provide to their customers. We can work very easily with this.

EdgeIR: What is the reaction to the Vendor Program? What kinds of companies and applications are getting traction?

MB: The feedback we’re getting is that it really answers a need and that the apps are simplifying and making [customers’] edge infrastructure future-proof. The marketplace is a compelling answer. It needs to have credible vendors and that’s what we started building.

The other thing that comes with this is that service providers have the ability to resell this; the structure is service provider and telco-friendly. They can organize their [sales and engineering] departments and structure that with pricing that makes sense for everybody. Their customers can connect to this and use it under the bill they are already receiving.

The applications that service providers are interested in right now are monitoring and cyber defense. It’s a big focus because at the edge so far, they’ve lost the pulse on that piece. Applications on the Nuvla.io marketplace give them the ability to recover that.

With enterprise business use cases like manufacturing, automotive, and retail, there are deployments taking place that are bespoke and stovepipe. When will those two (service provider and enterprise) connect, is difficult to predict.

EdgeIR: The most prevalent applications on edge platforms are tied to machine learning. Is that what you are seeing? Is data sovereignty and privacy a key driver, or is it latency and bandwidth that is pushing the need for machine learning at the edge?

MB: Convenience for developers to use ML to solve many problems [is important] and the tooling around that technology has improved a lot. For example, we’ve integrated with Edge Impulse recently, which is another cool SaaS-based platform to facilitate and accelerate ML deployment. And why running it at the edge? Any of those use cases only need one tick in that list of latency, privacy, and autonomy to be the key drivers for machine learning at the edge.

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