Scale Computing CEO: Making Edge Computing An ‘App Store’ For Business IT

‘When the cloud came along, there were so many apps. One of the benefits was, you need a database, you just click a button and magically have a database. That’s where we’re taking Scale. It’s not that you can’t deploy a database on Scale today. Of course you can. The difference is that we’ll actually be building in the tools so that from within Scale, if you need an SQL server, click a button and you have it,’ says Jeff Ready, CEO and co-founder, Scale Computing.

The recently concluded Scale Computing Platform//2025 conference was a very busy time for Scale Computing. The Indianapolis-based company used the event to not only showcase its hyperconverged infrastructure technology for small and midsized businesses, but also to highlight its moves to take the lead in bringing IT to the edge.

Scale Computing CEO Jeff Ready told CRN in an exclusive meeting that edge computing remains a confusing subject, particularly for the SMBs and smaller enterprises and their channel partners who would most benefit from a move to the edge.

The edge can be defined in lots of ways, Ready said, but is essentially the last place where servers sit to let people or machines touch their applications.

[Related: Scale Computing CEO: Broadcom-VMware Backlash Has Powered 400 Percent Enterprise Growth]

It’s also where businesses are increasingly moving their applications, including AI applications, which unfortunately can quickly lead to increased costs of managing those applications, he said.

“To run infrastructure at the edge is expensive,” he said. “If I’m a retailer and I have 1,000 stores, that means deploying a server 1,000 times, installing the software 1,000 times, et cetera. It creates a very high bar to cross. For an application to be worth deploying, the value has to exceed the cost of getting it there in the first place.”

To mitigate those costs and turn the edge into a competitive advantage, Scale Computing introduced new capabilities aimed at making it easier to deploy and manage applications at the edge.

This includes new built-in autonomous infrastructure management technology to allow AI applications to continuously operate, adapt, scale, and recover from failures without human intervention, the ability to do complex application management at scale across thousands of distributed locations, and centralized fleet management and API-driven automation for distributed environments.

The idea, Ready said, is to think of edge computing more like the cloud. Running applications on the edge that add incremental value to a business has not been easy, he said.

“But if you can change the game, and you can make deploying an application in that retail store just as easy as clicking a button in the cloud, that application with an incremental value actually is worth deploying,” he said. “And so what we expect to see is that the number of applications running at the edge increases exponentially moving forward.”

There’s a lot going on at Scale Computing and its move to make the edge a key part of how SMBs and small enterprises run their businesses. To learn more, read what Ready had to say in this Q&A which was lightly edited for clarity.

How do you define Scale Computing?

Scale primarily has been an IT infrastructure company. It’s a platform for running applications. But the secret sauce of Scale has been using technology to make the administration of infrastructure extremely easy as a primary hypervisor and container platform, hence the competitive nature with VMware. What we announced at the Scale Computing Platform//25 conference was that, with the new version 10 of our software, we are now expanding into actual application management. So rather than just using Scale to deploy systems, scale the operating system that exists on them, and manage all that infrastructure, now you actually can deploy and manage and even ultimately create applications from within the Scale environment itself.

The best analogy is how the cloud works. You can use the cloud in a couple ways. You can take an application that exists in a data center and move it to the cloud. That’s more like infrastructure. Or you can use tools that exist in the cloud and create applications. What we have previously done is move the applications, but now we’re unveiling the first of a series of features and functions that will enable the creation and management of the applications themselves. So basically, you create a private cloud through Scale.

What kind of applications are you talking about?

Historically, when migrating applications from somewhere else to Scale, we’ve always been very horizontal, including back-office stuff and IT infrastructure stuff. Every organization has a handful of applications that are semi-unique to them. [And] everybody has seen in the last two years a dramatic increase in AI-based applications, particularly in computer vision-based AI, lots of that in manufacturing and transportation and so forth. We saw that even before ChatGPT got all that AI talk going. So lots of very interesting applications, from retail where businesses are using computer vision to do things like detecting shoplifting, to manufacturing where companies are checking parts on an assembly line or checking safety, such as somebody walking where they aren’t supposed to on the factory floor. Now, with large language models, I’m seeing models in areas such as fast food where customers are deploying LLMs to do drive through order taking to augment the staff so one person could take multiple orders at one time, and that kind of thing.

Why would somebody want to run those applications on Scale Computing infrastructure, rather than in the cloud or on standard servers?

First, you are going to run some applications in the cloud. There are other applications, though, where the cloud may not make sense. AI tends to be one of those applications. If we associate GPUs with AI, the cost of owning a GPU is probably two orders of magnitude less expensive than renting a GPU in AWS. So on the inference side of AI, which is the fancy way of saying running an AI application, it might run on a $1,000 piece of hardware. If you run that application 24/7 in the cloud, it might cost $3,000 or $4,000 a month. That’s $40,000 a year versus a $1,000 one-time cost. So there’s a pricing reason. And there’s often a technical latency reason. In some applications, not all, milliseconds matter. And so for, say, an assembly line or a factory and parts are coming down the line and you’re looking doing this computer vision thing, you may need an answer from the system as to whether the part is correct or not in 20 milliseconds. But the cloud is 80 milliseconds away. So technically it just doesn’t work. And then there’s privacy considerations sometimes, and sometimes it’s a question of what is practical. Can a retail store run the point-of-sale system in the cloud? Yes, and some do. But most large retailers don’t because the flakiest part of the infrastructure might be the internet connection. So they’re going to run something local.

How about versus a standard server?

Versus standard servers, there’s a couple of things. Built into Scale is high availability, so if a piece of hardware fails, it fails over. But more broadly, this gets into where we’re actually taking the company with the application management side. Today, think about running an application out at what we’ll call the edge. The edge can be defined in lots of ways, but basically it’s the last place you’re going to have servers before people or machines touch the application. To run infrastructure at the edge is expensive. If I’m a retailer and I have 1,000 stores, that means deploying a server 1,000 times, installing the software 1,000 times, et cetera. It creates a very high bar to cross. For an application to be worth deploying, the value has to exceed the cost of getting it there in the first place. Scale’s technology compresses that cost. It’s cheaper to get the infrastructure out there, it’s cheaper to deploy applications there, and that now opens up a lot of applications to run at the edge. Go back to that retail example. A retailer may think, well, the only application that’s worth running in the store is the point of sale application, right? Everything runs through that. But a little application which might make the staff slightly more efficient, or let them sell slightly more product, was never worth the effort of getting it out there. But if you can change the game, and you can make deploying an application in that retail store just as easy as clicking a button in the cloud, that application with an incremental value actually is worth deploying. And so what we expect to see is that the number of applications running at the edge increases exponentially moving forward. This happened with the cloud. Originally, the analysts of the world thought customers would move applications to the cloud because clouds are really big data centers, and big data centers have better economies of scale than small data centers, so it’ll be cheaper, right? And there was some of that. But as you know, 90 percent of the stuff running in the cloud today wasn’t moved there. It was just written there, and that’s what’s going to happen at the edge. There’s some migration of applications to the edge, but ultimately, if we can lower the barrier to deploying infrastructure and applications now, you’re going to get this massive increase in the number of apps that can run there.

But isn’t everything you just said already possible with Scale Computing? You already have compute and storage designed for running applications on the edge.

Can we create a spot to run and manage applications? Yes, that’s what we’ve done. The difference is we’re now moving towards is the introduction of software and tools and integrations to accelerate application development. Here’s a simple example. Before the cloud, if I wanted to spin up a database application, first I had to spin up a server, deploy SQL Server, get that thing going. It might take a couple days. When the cloud came along, there were so many apps. One of the benefits was, you need a database, you just click a button and magically have a database. That’s where we’re taking Scale. It’s not that you can’t deploy a database on Scale today. Of course you can. The difference is that we’ll actually be building in the tools so that from within Scale, if you need an SQL server, click a button and you have it. Think of it in some ways like an app store. The reason you have 1,000 applications on your phone is because there’s an app store. … How do you do software-as-a service at the edge when somebody has to deal with the infrastructure? How do you roll it out? Well, if Scale becomes the conduit, then software vendors can push their applications out to all of these customers who can easily get them through an app store-like experience.

Does Scale Computing have the ‘scale’ to be attractive for software vendors to want to develop applications to run on it? There’s a lot of companies with larger scale.

This is where the market dynamic has changed with Broadcom and VMware. A lot of software vendors are looking for other options. This is one of the elements of our Veeam partnership. On the one hand, yes, Scale wanted Veeam to support Scale because it’s a very popular backup product among our target market, and so having that integration is great. Also, we’re helping Veeam. Veeam is looking to protect its customer base. They have customers who are looking to make an exodus from VMware. That puts the backup vendor at risk. If a customer leaves VMware and goes to something else and that something else doesn’t support Veeam, Veeam may lose that customer. So we’re in it together with the changing dynamic. We’ve reached a point now where we have a lot of software vendors coming to us, partly because of the Broadcom VMware thing, and partly because there’s a lot of software vendors just trying to figure out how to do the edge. There aren’t a lot of options there.

Is Scale Computing profitable?

Yes, we are.

Any plans for an IPO?

We are watching the market. It seems to change on a daily basis these days. If you had asked me this around December, I would have thought that by this summer we’d start seeing tech IPOs happen. And I’d have thought we’d be seriously looking at our timing. Then tariffs and all that stuff happened, and that got delayed, and maybe we’ll see relief again. We have to see the IPO window open up and so we’re not going to fight the timing of the market. We’re also looking at what’s the right timing for an IPO in the edge space, because that is our strong suit and edge is fairly new. The next 12 to 24 months, I think there’s a good chance we’ll get to that point, but it’s almost impossible to say because there are circumstances beyond our control. But we’re of a size and scope where that’s a real possibility.

Is government a big part of your business.

Federal government is a small part of our business. We do a lot of state and local government business, so we haven’t seen any specific deals impacted by DOGE or any of the restructuring and stuff that’s happened, but everybody’s cognizant of it. But no impact with DOGE that we’ve seen directly.

What are your strategic priorities for the rest of the year?

We have three strategic priorities. Number one is to continue to provide customers an off-ramp from VMware. Where you’ve seen Broadcom raise prices, we’ve aggressively lowered prices to make it easier to make that transition. One of the benefits of our partnership with Veeam is it makes migrating to Scale from VMware as simple as just restoring your backup. If you back it up on VMware, you just restore it to Scale and you’re done. The second is closely related. In recruiting and enabling more partners, both domestically and internationally, we’ve seen a big increase in our business as a result of all the Broadcom activity, so that’s a priority. And the third is around our long-term vision to maintain our leadership position around edge computing, and that includes this application management technology that we talked about.

Anything else we need to know about Scale Computing?

In summary, we’re seeing with edge computing what we saw happen in 2009 and 2010 with the cloud. The cloud was a location, and then it evolved into an application platform. We’re now in the ‘2010’ of edge. A lot of people think edge is just a destination, just another name for ROBO (remote office or branch office), or another name for on-prem, but it’s much more than that. And because of AI, we’re really starting to see turn in that corner.