The Challenge: A key limitation of traditional management systems is the use of a centralized database for processing of performance data. Even if the collection of data is managed by distributed components, the solutions invariably require centralization of the data for processing and alert generation. For large infrastructures, this introduces a significant performance bottleneck. The multiplier effect of the amount of data that needs to be processed as new devices are added is enormous. Capturing and processing these metrics in a single centralized database creates a significant performance bottleneck.
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Traverse on the other hand is built on a powerful, fully-distributed, patented architecture that has no centralized data warehouse for performance data. Traverse has distributed collection capability AND a distributed database architecture, which allows the system to scale to extremely large environments with standard hardware. Traverse utilizes small local databases in each distributed data gathering component. A data gathering component can process tens of thousands of metrics every few minutes, and store the data for up to three years (aggregated performance data, non-aggregated alerts and threshold violation). All the different types of data in the local database is stored in separate database tables, and Traverse databases do not require maintenance by DBAs.
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