Advanced Clustering Technologies Announces  ClusterVisor 1.0 HPC Management System

KANSAS CITY, Mo., May 11, 2023 — Advanced Clustering Technologies has announced the release of ClusterVisor 1.0, an update the company said enhances the features and benefits of this high performance computing (HPC) cluster management system.

ClusterVisor offers an easy-to-use web interface to deploy, provision, manage, monitor, and maintain the HPC cluster for its lifetime. With this update, ClusterVisor becomes a powerful disaster recovery tool that is delivered via an appliance that de-couples the cluster management aspect from the role of a head node so that its primary role is just running the job scheduler.

The new ClusterVisor system stores a cluster’s entire configuration, making it possible to manage every part of the cluster from the ClusterVisor interface or from the command line.

Among the key features of this latest edition of ClusterVisor:
• a statistics and monitoring engine
• a fully customizable UI
• integration with SLURM job data
• ability to create monitoring rules and alerts
• a rack diagramming tool to visualize the entire cluster
• customize dashboards to highlight the most important data
• built-in node and image cloner
• user management, account creation and password recovery tools

ClusterVisor helps organizations manage the cluster and its users while boosting application performance and improving cluster utilization. Any statistic that is collected by ClusterVisor can be used to create monitoring rules and alerts, thus enhancing cluster health and performance. Users are able to create their own custom dashboards to monitor the cluster activity that is most meaningful to that user.

With this latest edition of ClusterVisor, Advanced Clustering Technologies is giving organizations the tools needed to meet business and research objectives through effective management of the entire cluster. Updates made within ClusterVisor can be implemented cluster-wide quite easily, which helps organizations manage the cluster efficiently while increasing system utilization.