Scalable monitoring system supporting hybrid clusters

Abstract

The invention discloses a scalable monitoring system supporting hybrid clusters, comprising a monitoring agent program, a main monitoring program and a graphical interface; the monitoring agent program operates above a monitored node computer and broadcasts the performance monitoring data of the computer to all nodes in a group; the main monitoring program operates above a monitoring host computer, connects with all data resource nodes, periodically acquires the performance monitoring data of all the nodes of the group in which a data resource exists from the data resource nodes, and stores the acquired data into a database; a backend module of the graphical interface acquires relevant data from the database and sends the data to a frontend display module, and the frontend display module carries out visual presentation on the data and prompts alarm information. The invention can favorably adapts to the expansion of system function and scale, support isomerous and hybrid architectures and simultaneously adopt various monitoring strategies to monitor a plurality of nodes and equipment with different architectures and types, thereby having wide application prospect.

Description

(1) Technical field: [0001] The invention relates to a cluster monitoring system, in particular to an easily expandable monitoring system supporting heterogeneous clusters. Among them, the scalability includes two aspects: the expansion of the cluster scale and the expansion of the monitoring function. Supporting heterogeneity means that the monitoring system can simultaneously monitor node machines, network devices and other devices with different architectures in the cluster system. technology field. (two) background technology: [0002] At present, the cluster system has become the mainstream of today's high-performance computers due to its excellent performance-cost ratio, good scalability, and high availability. Among the latest TOP 500 in June 2009, 82% were cluster systems. Cluster systems are extremely expensive to manufacture and operate, so the performance indicators during cluster operation should be observable so that users can adjust and optimize the performan...

AI Technical Summary

Problems solved by technology

However, with the rapid growth of the number of nodes in the cluster system (up to thousands), new nodes and devices of heterogeneous types are continuously introduced into the cluster, so that these historical monitoring systems can no longer adapt to the growth of the new system scale. , and cannot meet the heterogeneous needs in today's cluster systems

[0007] Specifically, the main problem in the existing monitoring system is that it cannot well support ultra-large-scale cluster systems, that is, when the number of nodes in the cluster increases on a large scale, the load of the main monitoring node increases sharply, and the response time of the monitoring system decreases. It becomes very long and unacceptable; in addition, the cluster architecture begins to develop in a heterogeneous direction, and the existing monitoring system cannot meet the needs of various heterogeneous types of new nodes and dynamically increased equipment

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