AiThority Interview with Brent Schroeder, Global CTO, SUSE

Hello Brent. Tell us about your journey into technology and how you started at SUSE.

In my 30 years of working in technology innovation and development, I’ve always been drawn to applying emerging technology to solving customer problems.

Prior to joining SUSE, I worked at numerous system vendors in various management and engineering roles, including most recently, in Dell’s Office of the CTO. I was responsible for software technology strategy covering hybrid cloud, systems management, virtualization and operating systems.

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Seeing the trends in cloud and cloud-native computing, I wanted to get in the middle of the action. SUSE provided a great opportunity in the CTO role to work with both customers and the vast open source communities to help build future solutions.

Now as SUSE CTO, I am responsible for shaping SUSE’s technology and portfolio strategy in support of emerging use cases in areas such as Hybrid Cloud, Edge Computing, and AI/ML.

This includes identifying opportunities to collaborate on emerging solutions with our partners, such as NVIDIA, to mutually innovate on areas important to our customers.

There has been a seismic shift in the way IoT, Cloud and AI capabilities have disrupted the IaaS marketplace. How does SUSE keep up with the changing trend and stay relevant to the industry needs?

It all starts with the customer relationship. Meeting with customers at all levels is an integral aspect of working at SUSE. These relationships help us understand how today’s solutions are working, and more importantly, what we need to develop to prepare them for future business challenges.

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As the world’s largest independent open source company, we take this knowledge into our engagement with the broad ecosystem of open source communities. Within these communities, we participate in the development of next generation technologies and how to deploy and manage them in the context of customer needs. So, whether it’s next generation GPU-enabled container infrastructure or helping data scientists more easily develop and deploy solutions for IoT use cases, we can stay tightly in the mix.

Could you tell us a little bit about SUSE’s role in NVIDIA’s GPU Virtualization platform?

The relationships we have with our partners is critical to our ongoing success, and we’re proud to have this partnership with NVIDIA.

Together, we focus on what we can do to help our mutual customers modernize their IT infrastructure and ultimately accelerate delivery of AI and ML applications.

Specifically, our recent update to SUSE Linux Enterprise 15 SP2 saw greater operational efficiency, providing anytime and anywhere access to data through workflow automation and expanded hypervisor support from NVIDIA for enterprises and cloud service providers that are seeing an increased need to support GPUs.

This puts more tools into the hands of data scientists and IT for managing AI and edge workloads.

How do you see the Internet-connected world scaling with Desktop VMs and multimodal OS?

There is a great interrelationship happening with the explosive growth in the number of devices, form-factors, and personas all interconnected on the internet. As a result, workloads and experiences are evolving to the point where the boundaries of applications are no longer defined or constrained by infrastructure. Instead elements can be run based on a best fit for the applications requirements. The Multimodal OS, SUSE Linux Enterprise (SLE) in our case, along with its VMs and containers, is the key enabler – essentially providing a consistent application platform on any device in any location, edge to core to cloud, including the workstation.

Applied to AI/ML, being able to virtualize CPU & GPU resources across any environment is key to developing scalable and portable AI/ML, data-intensive and compute-intensive workloads.  By example below, the new expanded hypervisor support with SLES enables that transparency and allows that scale across multiple environments.

A data scientist using vGPU-enabled, workstation VMs can develop AI/ML prototypes without the need for expensive data center or cloud resources.  Once developed, the data scientist then taps into resources in the cloud with a cloud-aware workflow – being able to scale on-demand across resource environments. This is possible using a single multimodal OS that provides transparent use of the underlying infrastructure.

A COVID-19 business continuity advice —

The biggest advice I can provide is for IT and business leaders to review their systems and see where they may have an opportunity to take advantage of new technologies that can help ensure mission critical systems can operate from anywhere, including from a home office. As business models are being adjusted to account for impact from COVID-19, this is an opportunity to accelerate digital transformation. Through the rise of cloud and hybrid cloud solutions, companies can be better equipped with modern technology to ensure business can stay resilient, while also preparing for any future unknowns that may occur.

This is also advice we’ve taken ourselves. Prior to the COVID-19, roughly 38% of our teams were remote workers, and we had close to 100% of our team working from home throughout the pandemic. We know we need to work quickly to deliver our products and services to our customers as they further their own digital transformation journeys. For example, we released a new workplace solution, SUSE Home Office Workplace that enables our customers to work from home securely and productively.

Thank you, Brent! That was fun and we hope to see you back on AiThority.com soon.