Univa recently announced the release of Navops Launch 1.0, the latest iteration of the most robust hybrid HPC cloud management product, thus marking a substantial advancement in the migration of HPC workloads to the cloud. Navops Launch brings together public cloud services with on-premise clusters to cost-effectively fulfil growing workload demand.

The Navops Launch platform enables HPC organizations to manage cloud spending as well as audit usage. This new product makes use of an automation engine that combines cluster and cloud management systems with end-user defined metrics to completely inform intelligent cloud workload placement actions. Navops Launch also enables organizations to benefit from the lightning-fast cluster creation, practically unlimited scalability, and the pay-per-use economics of hybrid HPC cloud computing along with the completely automated control of spending as well as policies.

Gary Tyreman, President and CEO, Univa, said, “Navops Launch 1.0 is a breakthrough release for our enterprise customers who are shifting workloads to the cloud. It addresses the major concerns about cloud migration we hear most often from clients, including ease-of-use, security, cost and concerns about data locality and synchronization. Most importantly, it preserves customer investments in existing applications and operations, and it can be deployed quickly with minimal impact to existing environments.”

The company added that Navops Launch automation closely integrates with Univa Grid Engine as well as its workload status and metrics collection to react to changes in cluster utilization and workload demand by growing or contracting the cloud footprint in a dynamic way. After the offering is configured, administrators gain complete control over tying cloud resource usage to a commensurate budget without needing to intercede manually. Furthermore, built-in monitors report the spend, use, efficiency, and status of workloads placed in the cloud.

Univa added that Navops Launch is used in various application environments, such as enterprise analytics, scale-out machine learning/deep learning, and HPC. It also gets built-in data collection and reporting to allow customers to effortlessly account for resource usage and workload on-premise and across various cloud platforms.