Sylabs Brings Singularity Container Platform to Enterprises

Sylabs is bringing to market a new option for enterprises to integrate a container architecture into their cloud operations. Those efforts are based on the Linux-based Singularity container platform, which was developed in late 2015 by Sylabs CEO Gregory Kurtzer for use in high-performance computing (HPC) and scientific use cases.

Sylabs is packaging that Singularity development, which is currently in its 13th release since rolling out in late 2015, with support for enterprise customers. Sylabs officially launched today with funding from RStor, which is still in stealth mode.

Kurtzer explained that container technology itself was a “fantastic” solution designed to solve real problems. But it was too focused on microservices, which are often lightweight applications that can take advantage of the agility provided by a container architecture. Sylabs, using Singularity, is focused on offering enterprises a container platform dedicated to more robust workloads.

“In speaking with the HPC community, I discovered they were looking for a solution that could handle more than just microservices,” Kurtzer said. “As it turns out, those needs are also similar to what enterprises are looking for when it comes to more advanced workloads.”

Kurtzer explained that Singularity offers several advantages compared to traditional Docker-based containers. These include better security due to the ability to run a container without granting users control of a root-owned daemon process or kernel feature; easier mobility of content within a container through the use of a single-file format that includes the runtime environment; and support for high-performance hardware commonly used by research labs.

Kurtzer said these advances make Singularity a good option for enterprises focused on workloads like artificial intelligence (AI), machine learning, deep learning, and data science. He tagged these workloads as “enterprise performance computing.”

“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 noted.

While different from a Docker container, Kurtzer said Singularity containers are compatible with Docker Hub and seamlessly integrate with resource managers. Sylabs is “actively” working on adding support for Kubernetes, with Kurtzer stating that Kubernetes and Open Container Initiative (OCI) compliance and support are part of its road map.

Singularity is currently being used by more than 25,000 users, with a vast majority at universities and government institutions. Kurtzer said those users are running more than 1 million containers per day from just a few sites.

Singularity has also begun to receive more mainstream support, including Microsoft late last year announcing support with the Azure Batch Shipyard release.