TECHNICAL FIELD

[0001] Embodiments of the present disclosure relates to the field of enterprise application performance monitoring and management. In particular, embodiments of the disclosure relate to a system and a method for managing the performance of an enterprise application.

BACKGROUND OF THE DISCLOSURE

[0002] Enterprise application performance management is a set of processes that enable the management of performance of an organization to achieve one or more pre-selected goals.

[0003] An exemplary embodiment of currently available performance monitoring and management systems is illustrated in Figure 1. Most of the current management systems collect various performance metrics from a server 100 in the system. Using the collected performance metrics, the system will generate time scaled system metrics 102. In addition, various thresholds 104 will be defined by the IT team 106. The system will then co-relate the time-scaled system metrics 102 with the thresholds 104. Based on the co-relation, a breach identifier 108 will identify a breach. Once a breach is identified, a reporting unit 110 generates an appropriate alarm and reports the breach.

[0004] In addition to these processes, some of the existing performance monitoring and management systems comprise an issue diagnostic unit 112 that has diagnostic capabilities to identify hotspot areas by co-relating and analyzing metrics. Further, some systems comprise predictive analysis unit 114 which has forecasting capabilities to predict performance based on the historic performance of the system. Also, some systems include system execution model 116 that have capabilities to define and monitor performance of business transactions and drill down to view individual systems performance metrics in the distributed transaction path.

[0005] The above described performance management systems identify performance issues on occurrence, but they cannot accurately pin point the components affecting business transaction performance due to the following reasons.

[0006] The current systems do not co-relate workload elements while identifying threshold breaches and while diagnosing performance issues. Further, while predicting future workload, the current systems do not consider the trends observed in the current workload, for example: increase in number of users, month-on-month growth in number of requests.

[0007] Factors like change in workload etc. must be considered while forecasting performance as these factors can change the performance characteristics. However, none of the present systems take into account these factors while calculating the performance.

[0008] Therefore, there exists a need to develop a system and a method for managing performance of an enterprise application to overcome the above-mentioned problems.

SUMMARY OF THE DISCLOSURE

[0009] According to an embodiment of the present disclosure, a system for managing the performance of an enterprise application, said system comprises a central server configured to collect workload and performance metrics in a standard message format from a plurality of servers. The system further comprises a workload modeler configured to create a current workload model using the workload metrics collected over a predefined period of time. The current workload model is then forwarded to a trend analyzer and a predictive analyzer to predict a future workload for managing the enterprise application performance.

[00010] According to an embodiment of the present disclosure, a method for managing the performance of an enterprise application, said method comprising the steps of collecting workload metrics in standard message format from a plurality of servers. Then, a current workload model is created using the workload metrics collected over a predefined period of time. Following, a forecast workload model is produced using the workload model created over a predefined period of time. Further, a plurality of inputs is received to predict a future workload for managing the enterprise application performance, wherein the plurality of inputs comprises the current workload model and the forecast workload model.

BRIEF DESCRIPTION OF THE DRAWINGS

[00011] The features of the present disclosure are set forth with particularity in the appended claims. The disclosure itself, together with further features and attended advantages, will become apparent from consideration of the following detailed description, taken in conjunction with the accompanying drawings. One or more embodiments of the present disclosure are now described, by way of example only, with reference to the accompanied drawings wherein like reference numerals represent like elements and in which:

[00012] Figure 1 illustrates a simplified diagram of conventional performance monitoring and management system.

[00013] Figure 2 illustrates a system for managing performance of an enterprise application in accordance with the present disclosure.

[00014] The figures depict embodiments of the disclosure for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.

DETAILED DESCRIPTION

[00015] The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. Additional features and advantages of the disclosure will be described hereinafter which form the subject of the claims of the disclosure. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the disclosure as set forth in the appended claims. The novel features which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure.

[00016] The present disclosure relates to the field of enterprise application performance monitoring and management. In particular, the present disclosure relates to a system and a method for managing the performance of an enterprise application.

[00017] In one embodiment, a system for managing the performance of an enterprise application, said system comprises a central server configured to collect workload and performance metrics in a standard message format from a plurality of servers 210. The system further comprises a workload modeler 202 configured to create a current workload model using the workload metrics collected over a predefined period of time. The current workload model is then forwarded to a trend analyzer and a predictive analyzer to predict a future workload for managing the enterprise application performance.

[00018] In another embodiment of the present invention, the system comprises a co-relation unit configured to compare the standardized metrics with a predetermined threshold value. A breach identifier is configured to detect a breach and output a signal based on the comparison. Further, an issue diagnostic unit is configured to identify reason for the breach.

[00019] In one embodiment of the present disclosure, a method for managing the performance of an enterprise application, said method comprising the steps of collecting workload metrics in standard message format from a plurality of servers. Then, a current workload model is created using the workload metrics collected over a predefined period of time. Following, a forecast workload model is produced using the workload model created over a predefined period of time. Further, a plurality of inputs is received to predict a future workload for managing the enterprise application performance, wherein the plurality of inputs comprises the current workload model and the forecast workload model.

[00020] In another embodiment of the present invention, the method further comprises comparing the standardized metrics with a predetermined threshold value, detecting a breach and outputting a signal based on the comparison and identifying reason for the breach.

[00021] Figure 2 illustrates a system for managing performance of an enterprise application according to an embodiment of the present disclosure.

[00022] The system for managing the performance of an enterprise application comprises different platforms and application environments and is distributed across multiple environments. In one embodiment, the system comprises of a central server 200, a workload modeler 202, a trend analyzer 204, a predictive analyzer 206 and a business analytics unit 208.

[00023] The central server 200 collects workload and performance metrics from a plurality of servers 210i, 2102, , 210n (hereinafter collectively referred to as 210) present in the system for a predefined period of time. Each of the servers 210 represent the metrics in a different format which interrupts in accurate tracking of transactions. The central server 200 therefore defines the collected metrics in a standard message format which helps to track and diagnose business transactions across multiple application platforms. The standard message format allows capturing data required for both business and system characteristics in a single message.

[00024] The central server 200 is connected to a co-relation unit 212 which takes the standard message format metrics 214 as input and compares the metrics with a predefined threshold value 216. This comparison result is then used by a breach identifier 218 for identifying threshold breaches. Upon detection of a breach, the breach identifier 218 outputs a signal for reporting the breach to the IT team 220. The system further comprises an issue diagnostic unit 222 which identifies reason for the breach and provides an accurate performance diagnosis.

[00025] The central server 200 is further connected to the workload modeler which creates a current workload model using the standard message format metrics collected over the predefined period of time. Based on the current workload model created for a predefined period of time by the workload modeler 202, the trend analyzer 204 produces a forecast workload model. The forecast workload model is generated by analyzing the current and historic workload models and identifying the trend there from. This forecast workload model is then provided as input to the predictive analyzer 206.
[00026] Along with receiving input from the trend analyzer 204, the predictive analyzer 206 receives a plurality of other inputs including but not limited to the current workload model collected over a predefined period of time. These inputs are significant for determining the future performance characteristics of the system. Based on these inputs, the predictive analyzer 206 accurately predicts a future workload which in turn determines the future performance of the enterprise application.

[00027] Further, the output from the predictive analyzer 206 is fed to the business analytics unit 208 connected therewith for associating the future performance characteristics with actual impact on business. The business analytics unit 208 co-relates the performance improvement/ degradation with corresponding impact on business by associating a cost to each business transaction and determining cost variance based on the business performance. For example: performance degradation in the enterprise application would result in loss to enterprise and vice-versa. Similarly, impact of reduction in throughput on business revenue, impact of underutilized system resources on system operation and maintenance is predicted by associating a cost with each transaction and software/hardware component. This is done through a business performance dashboard 224 and system performance dashboard 226 connected with the business analytics unit 208. The business performance dashboard 226 and system performance dashboard 226 is monitored by the business team 228 and the IT team 220 respectively. The business analytics unit 208 also predicts the degradation service levels and cost impact on the enterprise due to performance degradation.

[00028] The methodology disclosed in the present disclosure quantifies the impact of system performance on the business and shares this information with the business stakeholders to enable better risk mitigation. Further, the standard message format of the present disclosure helps in standardizing metrics collected across disparate platforms which provide an easy way to track and analyze business transaction. Also, the method and system as disclosed in the disclosure improves the predictability of application performance by taking into account all the factors that may affect the performance characteristics. The present disclosure provides for enhanced performance issue diagnostics and threshold breach detection.

[00029] The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and devices within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[00030] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

We claim:

1. A system for managing the performance of an enterprise application, said
system comprises.

a central server 200 configured to collect workload and performance metrics in a standard message format from a plurality of servers 210;

a workload modeler 202 configured to create a current workload model using the workload metrics collected over a predefined period of time, and to forward the current workload model to a trend analyzer 204 and a predictive analyzer 206 to predict a future workload for managing the enterprise application performance.

2. The system as claimed in claim 1, further comprising:

a co-relation unit 212 configured to compare the standardized metrics 214 with a predetermined threshold value 216;

a breach identifier 218 configured to detect a breach and output a signal based on the comparison; and

an issue diagnostic unit 222 configured to identify reason for the breach.

3. A method for managing the performance of an enterprise application, said
method comprising the steps of:

collecting workload metrics in standard message format from a plurality of servers;
creating a current workload model using the workload metrics collected over a predefined
period of time;

producing a forecast workload model using the workload model created over a predefined period of time;

receiving a plurality of inputs to predict a future workload for managing the enterprise application performance,

wherein the plurality of inputs comprises the current workload model and the forecast workload model.

4. The method as claimed in claim 3, further comprising.
comparing the standardized metrics with a predetermined threshold
value;

detecting a breach and outputting a signal based on the comparison; and identifying reason for the breach.