Sylabs was launched in 2015 to create a container platform specifically designed for scientific and high performance computing use cases, two areas that founder and CEO Gregory Kurtzer, says were left behind in the containerization movement over the last several years. (For an explanation of containers, see this article.)
Docker emerged as the container of engine of choice for developers, but Kurtzer says the container solutions developed early on focused on microservices. He says there’s nothing inherently wrong with that, but it left out some types of computing that relied on processing jobs instead of services, specifically high performance computing.
Kurtzer, who didn’t exactly just fall off the open source turnip truck, had more than 20 years of experience as a high performance computing architect working at the US Department of Energy Lab, where he founded CentOS, an open source enterprise Linux project and Warewulf, which he says has become the most utilized stateless HPC cluster provisioner.
He decided to shift his attention to containers when founded Sylabs and launched the first open source version of Singularity in April, 2016. Even then, he had a vision of creating a commercial version of the product. He saw Singularity as a Docker for HPC environments, and would run his company in a similar fashion to Docker, leading with the open source project, then building a commercial business on top of it — just as Docker had done.
Kurtzer now wants to bring Singularity to the enterprise with a focus not just on the HPC commercial market, but other high performance computing workloads such as artificial intelligence, machine learning, deep learning and advanced analytics.
“These applications carry data-intensive workloads that demand HPC-like resources, and as more companies leverage data to support their businesses, the need to properly containerize and support those workflows has grown substantially,” Kurtzer wrote in a blog post announcing the enterprise product.
Even though Singularity is designed to handle different kinds of workloads, it still works with container orchestration tools, specifically Kubernetes and Mesos, and it is also compatible with Microsoft’s Azure Batch tool and other cloud tools.
Kurtzer indicated Sylabs currently has 12 employees, and is operating on an undisclosed amount of seed money. It was funded by RStor, a startup itself currently operating in stealth mode.