Method and system to monitor a diverse heterogeneous application environment
A method to detect potential problems within a heterogeneous and diverse application environment. Operations data is received from a plurality of application servers within the application environment. The operations data pertains to operations performed at the plurality of application servers over a predetermined time interval. The operations data is aggregated. The aggregated data is compared to reference data, and a potential problem within the application environment is detected if the aggregated data deviates from the reference data in a predetermined manner.
1. A method of detecting a problem within a server environment, the method comprising:
performing an aggregation phase in a pipelined processing environment, including
receiving operations data from a plurality of servers within the server environment;
aggregating the operations data over a first determinable time interval;
running the aggregation phase for a first set of operations data, the first set of operations data related to a first time period; and
performing an analysis phase in the pipelined processing environment, including
generating reference operations data from previously collected operations data over one or more second determinable time intervals;
comparing the aggregated operations data to the reference operations data;
running the analysis phase for the reference operations data, the reference operations data related to a time period prior to the first time period; and
detecting the problem within the server environment based on the comparing of the aggregated operations data to the reference operations data.
2. The method of claim 1 , further comprising detecting the problem within the server environment based on a comparison of the aggregated operations data deviating from the reference operations data in a determinable manner.
3. The method of claim 1 , further comprising continually updating the reference operations data.
4. The method of claim 1 , further comprising conforming the reference operations data to a common syntax, the common syntax being defined by at least one dimension variable and one analysis variable.
5. The method of claim 1 , wherein the aggregation of the operations data includes generating a multidimensional data structure into which the operations data, pertaining to the transactions performed at the plurality of servers over the first determinable time interval, is aggregated.
6. The method of claim 1 , including generating the reference operations data based on historical operations data pertaining to the application environment.
7. The method of claim 6 , wherein the generating of the reference operations data includes selecting the historical operations data based on the one or more second determinable time intervals.
8. The method of claim 6 , wherein the historical operations data is selected as pertaining to a past time interval corresponding to the one or more second determinable time intervals.
9. The method of claim 1 , wherein the comparing of the aggregated operations data to the reference operations data includes performing comparisons on multiple dimensions common to the aggregated operations data and the reference operations data.
10. The method of claim 1 , wherein detecting the problem includes generating at least one threshold based on the reference operations data, and determining whether the aggregated operations data transgresses the at least one threshold.
11. The method of claim 1 , wherein detecting the problem includes generating a range, based on the reference operations data, for at least one analysis variable of the aggregate operations data, and determining whether the at least one variable of the aggregate operations data falls outside of the range.
12. The method of claim 1 , further comprising generating an alert including information pertaining to the problem responsive to the problem being detected.
13. The method of claim 1 , including automatically initiating an action to correct the problem, responsive to the detection thereof.
14. The method of claim 1 , wherein the operations data is at least one of transaction, event, and heartbeat data.
15. A machine-readable storage medium storing an instruction that, when executed by one or more processors, causes at least one of the one or more processors to perform a method of detecting a problem within a server environment, the method comprising:
performing an aggregation phase in a pipelined processing environment, including
receiving operations data from a plurality of servers within the server environment;
aggregating the operations data over a first determinable time interval;
running the aggregation phase for a first set of operations data, the first set of operations data related to a first time period; and
performing an analysis phase in the pipelined processing environment, including
generating reference operations data from previously collected operations data over one or more second determinable time intervals;
comparing the aggregated operations data to the reference operations data;
running the analysis phase for the reference operations data, the reference operations data related to a time period prior to the first time period; and
detecting the problem within the server environment based on the comparing of the aggregated operations data to the reference operations data.
16. The machine-readable storage medium of claim 15 , wherein the method further comprises detecting the problem within the server environment based on the comparison of the aggregated operations data deviating from the reference operations data in a determinable manner.
17. A system to detect a problem within a server environment, the system comprising:
a summary module to receive and aggregate operations data from a plurality of servers, the summary module configured to operate in a pipelined processing environment, the operations data pertaining to operations performed by the plurality of servers with the aggregation being performed over a first determinable time interval, the summary module further to receive and aggregate the operations data related to a first time period;
an analysis module to generate reference operations data from previously collected operations data collected over one or more second determinable time intervals, the analysis module configured to operate in the pipelined processing environment and to generate the reference operations data related to a time period prior to the first time period; and
a comparison module to compare the aggregated operations data to the reference operations data and detect the problem within the server environment based on the comparison.
18. The system of claim 17 , wherein the comparison module is further configured to detect the problem within the server environment based on a comparison of the aggregated operations data deviating from the reference operations data in a determinable manner.
19. The system of claim 17 , wherein the analysis module is further configured to continually update the reference operations data.
20. The system of claim 17 , wherein the comparison module is further configured to compare the aggregated operations data to the reference operations data by performing comparisons on multiple dimensions common to the aggregated operations data and the reference operations data.
21. The system of claim 17 , wherein the comparison module is further configured to generate a range, based on the reference operations data, for at least one analysis variable of the aggregate operations data, and to determine whether the at least one variable of the aggregate operations data falls outside of the range.
22. The system of claim 17 , wherein the comparison module is configured to initiate an action automatically to correct the problem, responsive to the detection thereof.
23. A system for detecting a problem within a server environment, the system comprising:
a summary means for receiving and aggregating operations data from a plurality of servers, the summary means for operating in a pipelined processing environment, the aggregation being performed over a first determinable time interval, the summary means further for receiving and aggregating the operations data related to a first time period;
an analysis means for generating a reference operations data from previously collected operations data over one or more second determinable time intervals, the analysis means further for operating in the pipelined processing environment and for generating the reference operations data related to a time period prior to the first time period; and
a comparison means for comparing the aggregated operations data to the operations data and detecting the problem within the server environment based on the comparison of the aggregated operations data deviating from the reference operations data in a determinable manner.
24. A method of detecting a problem within a server environment, the method comprising:
receiving and aggregating, in a pipelined processing environment, operations data from a plurality of servers within the server environment, the aggregating to occur over a first time period;
generating, in the pipelined processing environment, reference operations data from previously collected operations data over one or more second determinable time intervals, the one or more second determinable time intervals being related to a time prior to the first time period;
comparing the aggregated operations data to the reference operations data; and
detecting the problem within the server environment based on the comparing of the aggregated operations data to the reference operations data.
25. The method of claim 24 , further comprising detecting the problem within the server environment based on a comparison of the aggregated operations data deviating from the reference operations data in a determinable manner.