Performance metrics and business metrics correlated in real-time

Performance Metrics and Business Metrics Correlated In Real-Time Introduction:

Performance metrics and business metrics correlated in real-time Application Performance Management  tools have been a subject of  a some debate within the IT industry. With the application landscape shifting to an cloud & the enterprise infrastructures now dramatically different than the traditional.All has repositories &  agents follow an  few well-defined procedures to communicate with each other.

Overview of Performance Metrics and Business Metrics Correlated In real-time Job Support:

Performance metrics &  business metrics correlated in the  real-time An enterprise executes various  types of business processes in its every day operations. This  processes often span in  the several functional units sometimes even to extend to link with its partners’ of  processes. They usually involve in many different roles, assets, &  resources; they may be supported by the IT systems, or to  be executed in ad hoc manner manually.

To  monitor enterprise-wide range of   business performance, one has to continuously collect the  metric data from these processes, aggregate the lower-level operational metrics to a build higher level Key Performance Indicators. Each metric instance within  the metric data stream of a contains three fields Value, Time & Attributes. These Value field contains the measurement of value of this instance, the Time field contains an time stamp of this instance, usually used to be  temporally correlate multiple metric instances &  the Attributes field contains the values of a user-defined attributes in a context slots.

These attributes are used to be capture correlation in information between the metric instances. The values of all three fields in an  metric instance will be assigned by an aggregation agent when generating of this instance. In an metric network, metric repositories get metric instances generated by an  aggregation agents & store them; agents get metric instances from an  repositories to generate instances of a high-level metrics or build metric relationship models (knowledge agents). 

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