Sylabs pushed out an update to its enterprise-focused SingularityPRO container platform that is the first to take advantage of its extensive 3.x launch from last October. The platform is designed to provide enhanced security and performance for container platforms and still be compatible with the current Kubernetes-focused ecosystem.
Gregory Kurtzer, founder and CEO of Sylabs, explained that the updated platform has been in the works since the 3.x launch and described it as a thorough upgrade from the previous version.
“We had made the transition to 3.x and were just waiting for it to stabilize before moving it into our enterprise offering,” Kurtzer said. “We are now to the point with 3.1 that it’s been stable and has been used in production. Basically, we decided it was a good opportunity to move our supported enterprise version to 3.1.”
That 3.x launch included a number of updates, including support with the Open Container Initiative (OCI) and the Container Networking Initiative (CNI), which required the move to base the platform on the Go programming language. “This allowed us to provide more features, but it was costly, especially for such a small company,” Kurtzer said.
“Singularity remains compatible with all of the container formats, we have just lowered the barrier for compute-based workloads by increasing the performance and security posture of that container runtime,” Kurtzer said.
The 3.1 release is also compatible with all workload managers and is integrated with orchestration systems such as Kubernetes and HashiCorp Nomad.
Sylabs’ platform uses the Linux-based Singularity container platform, which Kurtzer developed in late 2015. It was initially designed for use in high-performance computing (HPC) and scientific use cases. The company launched its enterprise push in early 2018.
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.
These features make Singularity a good option for enterprises focused on workloads like artificial intelligence (AI), machine learning, deep learning, and data science. Kurtzer noted that these workloads are often referred to 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.
Sylabs claims approximately 40,000 users are running millions of applications per day within the Singularity platform.
Kurtzer said that Sylabs is currently working on the 3.2 release, which could come online at some point in May. He said that version will include “the cool ability to take plugins to inject code features into the Singularity runtime and not have to fork it.”
Microsoft, Google Deals
Sylabs recently struck deals with cloud powerhouses Microsoft and Google.
The Microsoft agreement allows Sylabs and Azure users to pull Singularity container images from common OCI Distribution Specification image libraries. This supports an integrated path toward adopting Singularity Image Format (SIF) containers into workflows.
“This is a pretty strategic relationship as it’s not just having us in the marketplace, but also working together on the technology side to better enable the uptake and utilization of compute-based workloads in Azure,” Kurtzer said.
With Google, Sylabs is working as a technology partner to initially offer the SingularityPRO platform through the Google Cloud Platform (GCP) Marketplace.