METHODS AND SYSTEMS TO MANAGE BIG DATA IN CLOUD-COMPUTING INFRASTRUCTURES

摘要

Methods and systems that manage large volumes of metric data generation by cloud-computing infrastructures are described. The cloud-computing infrastructure generates sets of metric data, each set of metric data may represent usage or performance of an application or application module run by the cloud-computing infrastructure or may represent use or performance of cloud-computing resources used by the applications. The metric data management methods and systems are composed of separate modules that perform sequential application of metric data reduction techniques on different levels of data abstraction in order to reduce volume of metric data collected. In particular, the modules determine normalcy bounds, delete highly correlated metric data, and delete metric data with highly correlated normalcy bound violations.

主权项

1. A method stored in one or more data-storage devices and executed using one or more processors of a computing environment to manage sets of metric data stored in the one or more data-storage devices, the method comprising:
deleting sets of metric data from the one or more data storage device that are correlated with other sets of metric data; calculating normalcy bounds for each set of metric data stored in the one or more data-storage devices; determining which normalcy bounds of the sets of metric data should be re-calculated based on comparisons with historical characteristics of the sets of metric data; determining which normalcy bound violations of the sets of metric data are events worthy an alert based on a degree of abnormality determined for each normalcy bound violation; and deleting sets of metric data from the one or more data storage devices with events that are correlated with events of other sets of metric data.