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公开(公告)号：US20210096977A1
公开(公告)日：2021-04-01
申请号：US16792914
申请日：2020-02-18
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: According to an aspect of the present disclosure, a correlation data correlating resource usage with workload signatures is maintained, each workload signature representing a cluster of block signatures, each block signature characterizing the transaction instances initiated in a corresponding block duration. For the transactions received in a current block duration, if a current block signature is not contained in the correlation data and if the current transaction arrival rate (TAR) is greater than an expected TAR, a resource requirement for the current block signature is computed. Actions to manage capacity to handle transaction instances are triggered if the resource requirement is greater than the resource allocation in the current block duration. As an unknown current block signature and a higher TAR may be indicative of a workload surge, triggering suitable actions for such block signatures facilitates such surges to be handled by the software application.
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公开(公告)号：US20210224102A1
公开(公告)日：2021-07-22
申请号：US17013876
申请日：2020-09-08
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates characterizing operation of software applications having large number of components. In one embodiment, a digital processing system receives a first data indicating invocation types and corresponding invocation counts at an entry component for multiple block durations, where the entry component causes execution of internal component of the software application. The system also receives a second data indicating values for a processing metric at the internal components for the same block durations. The system then constructs for each internal component, a corresponding component model correlating the values for the processing metrics at the internal component indicated in the second data to the invocation types and invocation counts of the entry component indicated in the first data. The component models can aid in the performance management of the software application.
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3.发明申请公开(公告)号：US20210096981A1
公开(公告)日：2021-04-01
申请号：US16787059
申请日：2020-02-11
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates identifying differences in resource usage across different versions of a software application. In one embodiment, a respective first usage of resources is quantified for each of a set of workload signatures during the processing of transaction instances using a first version of a software application in a first sequence of block durations. A respective second usage of resources is quantified for each of the set of workload signatures during the processing of transaction instances using a second version of the software application in a second sequence of block durations. For each workload signature, the respective first usage and the respective second usage are compared to identify differences in the resource usage across different versions of the software application.
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公开(公告)号：US20150199254A1
公开(公告)日：2015-07-16
申请号：US14599351
申请日：2015-01-16
Applicant: Appnomic Systems Private Limited
Inventor： Nageswara Rao Vesepogu , Sumanth Narasappa , Padmanabhan Desikachari
IPC: G06F11/34
CPC classification number: G06F11/3419 , G06F11/0709 , G06F11/079 , G06F11/3466 , G06F2201/865 , G06F2201/87
Abstract: Various techniques associated with application performance monitoring are disclosed. In some embodiments, a subset of application methods is configured to capture response time metrics, and response time metrics for a prescribed application transaction are computed by summing corresponding response time metrics of methods of the subset that are executed during each transaction invocation. Method and transaction response time metrics are collected for each of a plurality of observation intervals, and the collected response time metrics are analyzed to identify anomalous method and transaction states. Co-occurring anomalous transaction and method states are correlated to identify a set of hotspot methods for the transaction, wherein hotspot methods comprise expected root causes for anomalies of the transaction.
Abstract translation: 公开了与应用性能监视相关的各种技术。 在一些实施例中，应用方法的子集被配置为捕获响应时间度量，并且通过对在每次事务调用期间执行的子集的方法的相应响应时间度量相加来计算规定的应用事务的响应时间度量。 针对多个观察间隔中的每一个收集方法和事务响应时间度量，并且分析所收集的响应时间度量以识别异常方法和事务状态。 相关联的异常事务和方法状态被相关联以识别用于事务的一组热点方法，其中热点方法包括事务异常的预期根本原因。
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公开(公告)号：US12174722B2
公开(公告)日：2024-12-24
申请号：US17013876
申请日：2020-09-08
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates characterizing operation of software applications having large number of components. In one embodiment, a digital processing system receives a first data indicating invocation types and corresponding invocation counts at an entry component for multiple block durations, where the entry component causes execution of internal component of the software application. The system also receives a second data indicating values for a processing metric at the internal components for the same block durations. The system then constructs for each internal component, a corresponding component model correlating the values for the processing metrics at the internal component indicated in the second data to the invocation types and invocation counts of the entry component indicated in the first data. The component models can aid in the performance management of the software application.
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Patent Agency Ranking
6.发明授权公开(公告)号：US11036608B2
公开(公告)日：2021-06-15
申请号：US16787059
申请日：2020-02-11
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates identifying differences in resource usage across different versions of a software application. In one embodiment, a respective first usage of resources is quantified for each of a set of workload signatures during the processing of transaction instances using a first version of a software application in a first sequence of block durations. A respective second usage of resources is quantified for each of the set of workload signatures during the processing of transaction instances using a second version of the software application in a second sequence of block durations. For each workload signature, the respective first usage and the respective second usage are compared to identify differences in the resource usage across different versions of the software application.
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公开(公告)号：US10437696B2
公开(公告)日：2019-10-08
申请号：US14517582
申请日：2014-10-17
Applicant: Appnomic Systems Private Limited
Inventor： Padmanabhan Desikachari
Abstract: Disclosed herein is a computer implemented method and system for analyzing load responsive behavior of infrastructure components in an electronic environment for proactive management of the infrastructure components. Transaction data on multiple application transactions is collected. Load patterns are identified from the collected transaction data for generating load profiles. Data on infrastructure behavior in response to the application transactions is collected. Infrastructure behavior patterns are identified from the infrastructure behavior data for generating behavior profiles. The generated load profiles and the generated behavior profiles are correlated to create a load responsive behavior model. The created load responsive behavior model predicts behavior of the infrastructure components for different load patterns. A live data stream from current application transactions is analyzed using the load responsive behavior model to determine current load responsive behavior. Deviations of the current load responsive behavior from the predicted behavior are detected using the load responsive behavior model.
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公开(公告)号：US11567800B2
公开(公告)日：2023-01-31
申请号：US16949176
申请日：2020-10-19
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates early identification of problems in execution of background processes. In one embodiment, a digital processing system characterizes the consumption of multiple resources during normal prior executions of a background process and determines a baseline pattern of consumption of resources for the background process. The system then monitors a current pattern of consumption of the resources during a current execution of the background process, and checks whether the current pattern of consumption has a deviation from the baseline pattern of consumption. The system notifies a potential problem with the current execution of the background process if a deviation is determined to exist. The notifications enable a user to get an early indication of potential problems during the execution of the background process itself.
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公开(公告)号：US20220027199A1
公开(公告)日：2022-01-27
申请号：US16949176
申请日：2020-10-19
Applicant: APPNOMIC SYSTEMS PRIVATE LIMITED
Inventor： Padmanabhan Desikachari , Pranav Kumar Jha
Abstract: An aspect of the present disclosure facilitates early identification of problems in execution of background processes. In one embodiment, a digital processing system characterizes the consumption of multiple resources during normal prior executions of a background process and determines a baseline pattern of consumption of resources for the background process. The system then monitors a current pattern of consumption of the resources during a current execution of the background process, and checks whether the current pattern of consumption has a deviation from the baseline pattern of consumption. The system notifies a potential problem with the current execution of the background process if a deviation is determined to exist. The notifications enable a user to get an early indication of potential problems during the execution of the background process itself.
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公开(公告)号：US10803397B2
公开(公告)日：2020-10-13
申请号：US14304760
申请日：2014-06-13
Applicant: Appnomic Systems Private Limited
Inventor： Padmanabhan Desikachari , Sumanth Narasappa
Abstract: Various techniques employed by an application performance management service to generate an application behavior learning based capacity forecast model are disclosed. In some embodiments, such a capacity forecast model is at least in part generated by clustering collected transaction data into one or more usage patterns, analyzing collected usage pattern data, and solving a mathematical model generated from the usage pattern data to determine a sensitivity of a resource to each type of transaction associated with an application.
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