Graphical Representation Of Cluster Topology's Health And Information
Publication Date: 2014-May-01
The IP.com Prior Art Database
Disclosed is a method for representing a customer's software defined storage with a simple and effective visualization. The method graphically visualizes the topology, overall health, and information of a cluster comprised of node groups, nodes, and associated peripherals.
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Graphical Representation Of Cluster Topology '
The method disclosed herein addresses the pooling of storage into a single virtualized layer, which is useful for moving storage away from hardware-based systems to
software-based systems and for enabling storage administrators to quickly and efficiently view, manage, and resolve problems with private cloud storage systems.
For storage that is visualized in a graphical user interface (GUI), the disclosed method helps represent both as a generalized pool and a specialized pool associated with higher-end disks. This works in concert with existing storage management products.
Alerts from the managed hardware are surfaced in the GUI, with drill-down access to key information as directly as possible (i.e. one to three clicks or gestures in a multichannel medium).
The disclosed method graphically visualizes the topology, overall health, and information of a cluster comprising node groups, nodes, and associated peripherals (e.g., disks). Various visual cues (e.g., color, thickness, size, and text with a graphical element such as circle, disks, etc.) are used to denote the characteristics of the topology constructs (e.g., node group, state, number of errors, etc.). The method provides the users with visual cues to take prioritized action on the objects requiring immediate attention. This feature is important for accelerating turnaround time; the time between determining the problem and resolving it to restore availability is critical for the many applications of this method (e.g., Service Level Agreements (SLAs)).
The graphical and interactive elements of the disclosed method represent a complex cloud-scale cluster (e.g., a thousand nodes) in a single view that allows users to monitor its health and quickly identify and resolve problems in a prioritized manner. Embodiments of the disclosed method include:
• Progressive drill-down: represents the cloud-scale cluster, such as to facilitate problem determination. Users can drill-down on problems via direct interaction (e.g., touch, click) from the topmost aggregate topology level to the lowest element of the topology.
• Visual cues: allow users to take prioritized action on objects requiring immediate attention
- Text, lines, and fill: color- and thickness-coded
- Size: larger circles represent a greater business impact
- Placement: higher priority objects are centrally placed
• Business-based problem determination: the data/number displayed inside the circles (i.e. node groups) is customizable to the customer's need to reflect high-value data that impacts the business (e.g., number of volumes, number of objects, number of errors, number of users impacted, etc.)
• Positioning of the viewport: positioning directly over the localized problem area
when zooming-in focuses the user's attention to the high-priority area
• Dual purpose zooming mechanism: allows traditi...