CN-122019325-A - Health evaluation method and device for application, electronic equipment and storage medium

CN122019325ACN 122019325 ACN122019325 ACN 122019325ACN-122019325-A

Abstract

The application provides an application health assessment method, device, electronic equipment and storage medium, which comprise the steps of obtaining monitoring index data corresponding to a target application in a plurality of health dimensions, normalizing the monitoring index data corresponding to the health dimensions based on reference parameters corresponding to the health dimensions for each health dimension to obtain health sub-scores corresponding to the health dimensions, determining dynamic weights corresponding to each health dimension based on application figures of the target application, and determining the health degree of the target application based on the health sub-scores and the dynamic weights corresponding to each health dimension. By adopting the technical scheme provided by the application, the accuracy, practicality and intelligence level of application health evaluation are improved, and the dependence on manpower and operation risk are reduced.

Inventors

CHEN WEI
AN BAOZHU
GAO KEKE
FAN CHENGHAO
WEN BAODONG
CAO HENGZHI

Assignees

人保信息科技有限公司
中国人民人寿保险股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260129

Claims (10)

1. An applied health assessment method, characterized in that the health assessment method comprises: acquiring monitoring index data corresponding to a target application in a plurality of health dimensions; for each health dimension, based on a reference parameter corresponding to the health dimension, carrying out normalization processing on the monitoring index data corresponding to the health dimension to obtain a health sub-score corresponding to the health dimension; determining a dynamic weight corresponding to each health dimension based on the application portraits of the target application; and determining the health degree of the target application based on the health sub-score and the dynamic weight corresponding to each health dimension.
2. The method for evaluating the health of an application according to claim 1, wherein the application representation comprises static attributes of a target application and dynamic attributes of the target application, wherein the determining the dynamic weight corresponding to each health dimension based on the application representation of the target application comprises: based on the static attribute, matching a basic weight corresponding to each health dimension from a weight template library; determining an adjustment operator of the basic weight corresponding to each health dimension based on the priority of the dynamic attribute; and respectively correcting the basic weight corresponding to each health dimension according to the corresponding adjustment operator to obtain the dynamic weight corresponding to each health dimension.
3. The method for health assessment of an application according to claim 2, wherein said determining an adjustment operator for the basis weight corresponding to each health dimension based on the priority of the dynamic attribute comprises: determining a first adjustment value of the basic weight corresponding to each health dimension based on the priority of the dynamic attribute; The historical health data and the historical event record data of the target application in the first preset time period are associated according to a preset association rule, and an event diagnosis conclusion of the target application in the first preset time period is generated; determining whether an event abnormality instruction for indicating that the event diagnosis conclusion is abnormal is detected; If the event abnormal instruction is detected, determining key features from the event diagnosis conclusion in response to the event abnormal instruction; Determining a second adjustment value of the base weight corresponding to each health dimension based on the key features; Determining an adjustment operator of the basic weight corresponding to each health dimension according to the first adjustment value and the second adjustment value of the basic weight corresponding to each health dimension; and if the event abnormality instruction is not detected, respectively determining a first adjustment value of the basic weight corresponding to each health dimension as an adjustment operator of the basic weight corresponding to each health dimension.
4. The method for health assessment of an application according to claim 3, further comprising: Determining a change amplitude of historical monitoring index data corresponding to each health dimension in a second preset time period in response to a fraction anomaly instruction for indicating the health anomaly; determining a health dimension that anomalies the health score based on the magnitude of change; And determining a new reference parameter corresponding to the health dimension with abnormal health degree based on a preset adjustment step length, and replacing the original reference parameter corresponding to the health dimension with abnormal health degree with the new reference parameter.
5. The method for health assessment of an application according to claim 3, further comprising: and rendering the historical health data, the historical occurrence event and the event diagnosis conclusion to generate a first view in a visual interface corresponding to the target application.
6. The method for health assessment of an application according to claim 1, further comprising: And rendering the health data of the target application to generate a second view in the visual interface corresponding to the target application.
7. The method of claim 6, wherein the health data comprises a health of the target application, a health sub-score for each health dimension, and a dynamic weight for each health dimension.
8. An applied health assessment device, characterized in that the health assessment device comprises: the acquisition module is used for acquiring the monitoring index data corresponding to the target application in a plurality of health dimensions; The processing module is used for carrying out normalization processing on the monitoring index data corresponding to the health dimension based on the reference parameter corresponding to the health dimension to obtain the health sub-score corresponding to the health dimension; the dynamic weight determining module is used for determining the dynamic weight corresponding to each health dimension based on the application portrait of the target application; and the health degree determining module is used for determining the health degree of the target application based on the health sub-score and the dynamic weight corresponding to each health dimension.
9. An electronic device comprising a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is in operation, the machine-readable instructions being executable by the processor to perform the steps of the health assessment method of the application of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the health assessment method of an application according to any of claims 1 to 7.

Description

Health evaluation method and device for application, electronic equipment and storage medium Technical Field The present application relates to the field of application operation and maintenance, and in particular, to a method and apparatus for health assessment of an application, an electronic device, and a storage medium. Background The traditional IT service management system mainly carries out operation and maintenance treatment on the application around a predefined standardized flow. Under this system, application monitoring data is usually derived from a plurality of heterogeneous and independent tool platforms such as Zabbix, ELK, APM. The common operation and maintenance technical scheme focuses on passive alarming and manual investigation afterwards, and the implementation mode of the operation and maintenance technical scheme essentially belongs to simple stacking of various monitoring tools and data. However, due to the lack of effective data linkage and information fusion between different tool platforms, operation and maintenance personnel often need to perform data association analysis across multiple systems, which is low in efficiency and difficult to form comprehensive and timely application health state evaluation. Meanwhile, the existing operation and maintenance technical scheme not only shows unilateral performance, but also shows obvious passive response and result hysteresis, so that an operation and maintenance team cannot judge the real-time and comprehensive health degree of the system. In addition, health assessment mainly depends on judgment of each technical index by manual experience, and is difficult to comprehensively cover and objectively reflect the real health state with user experience as a core. Disclosure of Invention In view of the above, the embodiments of the present application provide a method, an apparatus, an electronic device, and a storage medium for health evaluation of an application, which improve the accuracy, practicality, and intelligence level of application health evaluation, and reduce the dependency on manpower and operational risk. The application mainly comprises the following aspects: in a first aspect, an embodiment of the present application provides a health assessment method for an application, where the health assessment method includes: acquiring monitoring index data corresponding to a target application in a plurality of health dimensions; for each health dimension, based on a reference parameter corresponding to the health dimension, carrying out normalization processing on the monitoring index data corresponding to the health dimension to obtain a health sub-score corresponding to the health dimension; determining a dynamic weight corresponding to each health dimension based on the application portraits of the target application; and determining the health degree of the target application based on the health sub-score and the dynamic weight corresponding to each health dimension. The application portrayal comprises a static attribute of a target application and a dynamic attribute of the target application, and the dynamic weight corresponding to each health dimension is determined based on the application portrayal of the target application, and the method comprises the following steps: based on the static attribute, matching a basic weight corresponding to each health dimension from a weight template library; determining an adjustment operator of the basic weight corresponding to each health dimension based on the priority of the dynamic attribute; and respectively correcting the basic weight corresponding to each health dimension according to the corresponding adjustment operator to obtain the dynamic weight corresponding to each health dimension. Further, the determining an adjustment operator of the basic weight corresponding to each health dimension based on the priority of the dynamic attribute includes: determining a first adjustment value of the basic weight corresponding to each health dimension based on the priority of the dynamic attribute; The historical health data and the historical event record data of the target application in the first preset time period are associated according to a preset association rule, and an event diagnosis conclusion of the target application in the first preset time period is generated; determining whether an event abnormality instruction for indicating that the event diagnosis conclusion is abnormal is detected; If the event abnormal instruction is detected, determining key features from the event diagnosis conclusion in response to the event abnormal instruction; Determining a second adjustment value of the base weight corresponding to each health dimension based on the key features; Determining an adjustment operator of the basic weight corresponding to each health dimension according to the first adjustment value and the second adjustment value of the basic weight corresponding to each heal