CN111475682A - Intelligent operation and maintenance platform based on super-large-scale data system - Google Patents
Intelligent operation and maintenance platform based on super-large-scale data system Download PDFInfo
- Publication number
- CN111475682A CN111475682A CN202010262281.3A CN202010262281A CN111475682A CN 111475682 A CN111475682 A CN 111475682A CN 202010262281 A CN202010262281 A CN 202010262281A CN 111475682 A CN111475682 A CN 111475682A
- Authority
- CN
- China
- Prior art keywords
- data
- module
- maintenance platform
- intelligent operation
- platform based
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9024—Graphs; Linked lists
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/904—Browsing; Visualisation therefor
Abstract
The invention provides an intelligent operation and maintenance platform based on a super-large-scale data system, which adopts an open and extensible data acquisition bottom layer framework to butt joint various data sources and reduce a big data acquisition threshold. And viewing all types of data in the system from a full view angle, tracking the whole life cycle of each data node, and sharing and displaying the link relation among the data nodes. For example, through system node log monitoring, multi-dimensional link monitoring and data blood relationship combing of users, data, job tasks, API, services and the like is realized, traceability of fine-grained data and operation is guaranteed, and full life cycle management of data is completed. The invention displays the corresponding node information, resource consumption and the like by self-defining the size and color setting function of the data type node, highlights the node and node link relation, and compares and verifies the data and the original data, thereby ensuring the integrity, the correctness, the real-time property and the auditability of the data.
Description
Technical Field
The invention relates to the field of internet, in particular to an intelligent operation and maintenance platform based on a super-large-scale data system.
Background
With the development of cloud storage, cloud computing and big data related technologies, big data acquisition and analysis are operated based on a cloud management platform, support for a large number of server operation data is achieved, logs are collected uniformly, relevant operation data of the servers are monitored, close association of a monitoring alarm system is achieved, performance and monitoring trend of a relevant data center are analyzed, and therefore health conditions of a host, a virtual machine, storage, an application system and the like are evaluated, optimized and predicted effectively, accurately and timely.
Apache Skywalking provides a solution for distributed tracking, service grid telemetry analysis, performance index analysis, application and service dependency analysis, metric aggregation, visualization integration, and the like. However, skywarkling does not support call tracing, cannot restore the whole life cycle of data, and does not trace user data in the system, so that full-view data link relation analysis related to a user is performed.
However, the existing ultra-large scale data system has the following defects in the intelligent operation and maintenance: the prior art focuses on the management and monitoring of system application performance data, and does not address all data within the system, including: unified management and intelligent monitoring of users, data, services and resources and calling and tracking of various large application services are realized, and systematic operation and maintenance are carried out on data. The existing technology provides data link collection, but cannot perform user-defined screening of data nodes and automatically generate corresponding data link relations. The prior art can not be compatible with batch processing and stream processing modes simultaneously according to business requirements, and can only carry out self-defined development according to data business requirements. In the prior art, a data link UI display interface has single color and graphic mode, and does not provide a user-defined display function according to the characteristics of data, such as a star chart, a tree chart, a scatter diagram and the like of a force-oriented graph and share a result interface. The prior art can visually display the accessed data and the data relation thereof, but does not automatically compare and verify the displayed data and the original data by using an artificial intelligence algorithm, thereby ensuring the integrity, the correctness, the instantaneity and the auditability of the data.
Disclosure of Invention
In order to solve the technical problems, the invention provides an intelligent operation and maintenance platform based on a super-large scale data system so as to realize real-time acquisition, combination and intelligent analysis of distributed heterogeneous data.
According to the embodiment of the invention, the invention provides an intelligent operation and maintenance platform based on a super-large-scale data system, which comprises an identity verification module, a data acquisition module, a data analysis processing module, a data sharing display module, a data monitoring module and a data verification module.
Wherein the content of the first and second substances,
the identity authentication module is used for authenticating the identities of multiple classes of users in the same or different clusters of the introduced multiple data source systems so as to realize that users with different authorities log in a platform and check data and data link relations with different granularities;
the data acquisition module is used for collecting data periodically based on an API (application program interface) provided by the target system, or providing the API for the target system to upload data actively;
the data analysis processing module is used for analyzing the global data blood margin and the application data blood margin of the acquired data, deeply analyzing the data and the application value and processing the acquired data, wherein the processing process comprises the steps of carrying out batch processing on main data and carrying out stream processing on fact data and log data so as to ensure the integrity, the accuracy and the real-time property of the data;
the data sharing display module is used for displaying all data and data link relations in a force-directed graph mode, judging the relations among the data nodes according to conditions and carrying out user-defined highlighting display and sharing display of a data link interface on the data node relation links;
the data monitoring module is used for performing similarity learning and clustering on data in the system by adopting a clustering algorithm of frequency and dependency or a hierarchical clustering algorithm according to different data scenes so as to continuously monitor the data quality;
and the data verification module is used for combing the data link relation by adopting machine learning and an artificial intelligence database algorithm, and comparing and verifying the data and the original data to ensure the integrity, the correctness, the instantaneity and the auditability of the data.
Furthermore, the data acquisition module adopts an open and extensible data acquisition architecture, supports multiple types of data acquisition of multiple data sources, and supports seamless connection with an original big data platform of a target system. Wherein the multiple types of data comprise one or more of structured data, semi-structured data, unstructured data.
Further, the data analysis processing module comprises a data integration sub-module, a data analysis sub-module, a data exploration sub-module and a data query sub-module, wherein the data integration sub-module, the data analysis sub-module, the data exploration sub-module and the data query sub-module are arranged in the data analysis processing module
And the data integration submodule is used for converting, cleaning and integrating data from different sources, different types and different fields to form unified data and dimension data.
And the data analysis submodule is used for analyzing the data state of the current system, and comprises a data generation mode for acquiring the current data type and the corresponding type in real time and the occupation state of the data.
And the data exploration submodule is used for exploring services and data in the system through a query interface, sharing search results, finding low-value applications and low-value data and improving the data operation efficiency.
And the data query submodule is used for processing data based on the graph database and supporting quick query of mass data and link relations of the mass data and query result sharing.
Furthermore, the data analysis sub-module is also used for viewing specific information of a specific entity in the system and entity information related to the entities so as to perform early warning and detection and quickly locate problem data.
Further, the data query submodule is also used for generating a link relation between keywords according to one or more keyword queries, displaying the link relation in a graphical interface mode, periodically generating a report and a query interface according to different requirements, and sharing a result interface.
Further, the force guide graph mode comprises one or more of a star graph, a tree graph and a scatter graph.
Furthermore, the data monitoring module is also used for analyzing global data root cause and providing continuous monitoring and promotion suggestions of high-order operation and maintenance indexes.
Further, the artificial intelligence database algorithm comprises one or more of a path search algorithm, a community discovery algorithm and a centrality algorithm.
Further, the graph database includes one or more of MySQ L, ElasticSearch, Kafka, Hive, and Neo4 j.
Further, the data sharing display module is further configured to self-define and filter a data node range through CQ L, so as to generate a corresponding data node link relationship, and share the data link interface.
The invention has the beneficial effects that: firstly, the invention uniformly carries out digital management on all entities (users, data, services and resources) in a target system; secondly, the invention provides a unified entrance to check the running state, the use condition, the resource consumption condition and the like of the whole platform from various visual angles; thirdly, the interface UI of the invention is friendly to interaction, and displays and shares data nodes and the link relation among the nodes by a force-directed graph (comprising a star graph, a tree graph, a scatter graph and the like). Fourthly, the machine learning and artificial intelligence algorithm is adopted to carry out comparison verification and data quality monitoring on the data and the original data, and the integrity, the correctness, the real-time property and the auditability of the data are ensured.
Drawings
FIG. 1 is a frame diagram of an intelligent operation and maintenance platform based on a very large scale data system according to the present invention;
fig. 2 is a UI diagram of an intelligent operation and maintenance platform interface based on a very large scale data system according to the present invention.
Detailed Description
For the convenience of understanding, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, according to the embodiment of the present invention, the present invention provides an intelligent operation and maintenance platform based on a very large scale data system, which solves the technical problem of real-time acquisition, merging and intelligent analysis of distributed heterogeneous data, and fills the blank of uniformly performing digital full link management on all entities (users, data, services, and resources) in a cluster and a cluster system, according to the embodiment of the present invention, the platform of the present invention comprises an identity verification module, a data acquisition module, a data analysis processing module, a data sharing display module, a data monitoring module, and a data verification module, wherein,
and the identity authentication module is used for authenticating the identities of the multi-class users in the same or different clusters of the introduced multi-data source systems so as to realize that the users with different authorities log in the platform and check the data and data link relations with different granularities.
And the data acquisition module is used for collecting data periodically based on an API (application program interface) provided by the target system, or providing the API for the target system to upload data actively.
In the embodiment of the invention, a data acquisition module is used for data acquisition, distributed acquisition of data such as users, data, services, resources and the like in a system is supported under the condition that the existing system is not changed, an API interface or a query function provided by a target system can be used for regularly collecting data (pull) in the acquisition process, or the API interface is provided for the target system to carry out active data uploading (push), meanwhile, seamless docking is carried out on a large data platform of the existing docking system, wherein the large data platform comprises KeyCloak, Spark, Yarn, Git, CI/CD, Marathon, tasks, Artifact, HDFS, Hive, Kafka, MySQ L, Redis and the like, the underlying architecture is flexible and extensible.
According to the embodiment of the invention, the intelligent operation and maintenance platform further comprises a data analysis processing module for analyzing and processing the acquired data to obtain effective data so as to realize intelligent management of the big data, the invention supports the processing of batch data and stream data, the batch processing mode is carried out on the main data, the stream processing mode is carried out on the fact data and log data, the integrity of the data is ensured, and the accuracy and the real-time performance of the data are ensured.
According to the embodiment of the invention, the data analysis of the invention provides analysis of the blood margin of the global data and the blood margin of the application data, and deep analysis of the data and the application value. The data analysis processing module of the invention comprises:
and the data integration submodule is used for converting, cleaning and integrating data from different sources, different types (structured, semi-structured and unstructured data) and different fields to form unified data and dimension data.
And the data analysis submodule is used for analyzing the data state of the current system, and comprises a data generation mode for acquiring the current data type and the corresponding type in real time and the occupation state of the data. In the present invention, the data analysis submodule carries the role of data panorama, specifically, it includes the situation of viewing all entity data in the system, including: what data is in the system, how the data is generated, what data is used by who (user, service), what applications are in the system, who uses the applications, how much resources are consumed, current/historical state of data and applications, etc. And personnel in the system can reasonably schedule and allocate resources according to the data information panoramic image.
In an embodiment of the present invention, the data analysis sub-module of the present invention is further configured to view specific information of a specific entity (user, data, service) in the system and entity information related to the entities, such as: the upstream of this entity depends on the data, which data, applications are consumed downstream, the running state of the entity, how it is affected by the upstream and downstream services, etc. Therefore, the system operation and maintenance personnel can perform early warning and detection and quickly locate problems.
According to the embodiment of the invention, the data analysis processing module further comprises a data exploration sub-module and a data query sub-module.
According to the embodiment of the invention, the data exploration submodule is used for exploring services, data and the like in a system and sharing search results through a query interface, finding low-value applications and low-value data, improving the data operation efficiency, and further data mining can be carried out by a data scientist or a data engineer on the basis.
According to an embodiment of the present invention, the intelligent operation and maintenance platform of the present invention further includes a data sharing display module, as shown in fig. 2. The front-end interface of the data sharing display module carries out friendly interaction and display in a force-directed graph mode (including a star graph, a tree graph, a scatter graph and the like), and can carry out self-defined highlight display on nodes and link relations thereof. The invention tracks, displays and shares the application relationship, including the data blood relationship and the link applying the blood relationship. The data sharing display module of the invention displays all data and data link relations in a force-directed graph mode, judges the relations among data nodes according to conditions, displays the relation links of the data nodes in a user-defined highlight mode, and displays the data link interfaces in a sharing mode.
According to the embodiment of the invention, the intelligent operation and maintenance platform also provides a data monitoring module, and the data in the system is subjected to similarity learning and clustering by adopting a clustering algorithm, a hierarchical clustering algorithm and the like of frequency and dependency according to different data scenes, so that the data quality is continuously monitored, and global data root cause analysis is used for providing continuous monitoring and promotion suggestions of high-order operation and maintenance indexes.
According to the embodiment of the invention, the intelligent operation and maintenance platform also provides a data verification module, and adopts machine learning and artificial intelligence database algorithm: the path search algorithm (including the shortest path), the community discovery algorithm, the centrality algorithm and the like are used for combing the data link relation in charge, and comparing and verifying the data and the original data, so that the integrity, the correctness, the real-time property and the auditability of the data are ensured.
The invention provides an intelligent operation and maintenance platform based on a super-large scale data system, which adopts an open and extensible data acquisition bottom layer framework, is butted with various types of data sources, and can also be seamlessly butted with a large data platform in the existing system, so that the large data acquisition threshold is reduced, the full-view viewing of all types of data in the system is realized, the whole life cycle of each data node is tracked, and the link relationship among the data nodes is displayed.
The intelligent operation and maintenance platform self-defines and screens a data node range through CQ L and generates a corresponding data node link relation, monitors user links, application links, metadata links and full link management topology, realizes root cause analysis by using panoramic data and provides continuous monitoring and promotion suggestions of high-order operation and maintenance indexes, adopts corresponding algorithms including frequency and dependency clustering algorithm and hierarchical clustering algorithm to learn and cluster the similarity of data in the system according to different data scenes, thereby continuously monitoring the data quality, and adopts an artificial intelligent database algorithm, namely a path search algorithm (including shortest path), a community discovery algorithm, a centrality algorithm and the like to comb complex data links and compare and verify the data and the original data to ensure the integrity, correctness, instantaneity and auditability of the data.
It will be evident to those skilled in the art that the embodiments of the present invention are not limited to the details of the foregoing illustrative embodiments, and that the embodiments of the present invention are capable of being embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the embodiments being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units, modules or means recited in the system, apparatus or terminal claims may also be implemented by one and the same unit, module or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention and not for limiting, and although the embodiments of the present invention are described in detail with reference to the above preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the embodiments of the present invention without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An intelligent operation and maintenance platform based on a super-large scale data system is characterized by comprising an identity verification module, a data acquisition module, a data analysis and processing module, a data sharing and display module, a data monitoring module and a data verification module,
wherein the content of the first and second substances,
the identity authentication module is used for authenticating the identities of multiple classes of users in the same or different clusters of the introduced multiple data source systems so as to realize that users with different authorities log in a platform and check data and data link relations with different granularities;
the data acquisition module is used for collecting data periodically based on an API (application program interface) provided by the target system, or providing the API for the target system to upload data actively;
the data analysis processing module is used for analyzing the global data blood margin and the application data blood margin of the acquired data, deeply analyzing the data and the application value and processing the acquired data, wherein the processing process comprises the steps of carrying out batch processing on main data and carrying out stream processing on fact data and log data so as to ensure the integrity, the accuracy and the real-time property of the data;
the data sharing display module is used for displaying all data and data link relations in a force-directed graph mode, judging the relations among the data nodes according to conditions and carrying out user-defined highlighting display and sharing display of a data link interface on the data node relation links;
the data monitoring module is used for performing similarity learning and clustering on data in the system by adopting a clustering algorithm of frequency and dependency or a hierarchical clustering algorithm according to different data scenes so as to continuously monitor the data quality;
and the data verification module is used for combing the data link relation by adopting machine learning and an artificial intelligence database algorithm, and comparing and verifying the data and the original data to ensure the integrity, the correctness, the instantaneity and the auditability of the data.
2. The intelligent operation and maintenance platform based on the very large scale data system according to claim 1, wherein the data acquisition module adopts an open and extensible data acquisition architecture, supports multiple types of data acquisition of multiple data sources, and supports seamless docking with an original large data platform of a target system, wherein the multiple types of data include one or more of structured data, semi-structured data and unstructured data.
3. The intelligent operation and maintenance platform based on the very large scale data system according to claim 1, wherein the data analysis processing module comprises a data integration sub-module, a data analysis sub-module, a data exploration sub-module and a data query sub-module, wherein
The data integration submodule is used for converting, cleaning and integrating data from different sources, different types and different fields to form unified data and dimension data;
the data analysis submodule is used for analyzing the data state of the current system, and comprises a data generation mode for acquiring the current data type, the corresponding type and the occupation state of the data in real time;
the data exploration submodule is used for discovering low-value application and low-value data and improving the data operation efficiency by inquiring the service and the data in the interface exploration system and sharing the search result;
and the data query submodule is used for processing data based on the graph database and supporting quick query of mass data and link relations of the mass data and query result sharing.
4. The intelligent operation and maintenance platform based on the very large scale data system according to claim 3, wherein the data analysis sub-module is further configured to view specific information of a specific entity in the system and information of entities related to the entities, so as to perform early warning and detection to quickly locate problem data.
5. The intelligent operation and maintenance platform based on the very large scale data system according to claim 3, wherein the data query submodule is further configured to generate a link relationship between keywords according to one or more keyword queries, display the link relationship in a graphical interface form, and periodically generate reports and a shared query result interface according to different requirements.
6. The intelligent operation and maintenance platform based on the very large scale data system according to claim 1, wherein the force directed graph mode comprises one or more of a star graph, a tree graph and a scatter graph.
7. The intelligent operation and maintenance platform based on the very large scale data system according to claim 1, wherein the data monitoring module is further configured to provide continuous monitoring and promotion suggestions for high-order operation and maintenance indexes for global data root cause analysis.
8. The intelligent operation and maintenance platform based on very large scale data system according to claim 1, wherein the artificial intelligence database algorithm comprises one or more of a path search algorithm, a community discovery algorithm, and a centrality algorithm.
9. The intelligent operation and maintenance platform based on very large scale data system according to claim 1, wherein the graph database comprises one or more of MySQ L, ElasticSearch, Kafka, Hive, and Neo4 j.
10. The intelligent operation and maintenance platform based on very large scale data system of claim 5, wherein the data sharing and displaying module is further configured to custom screen a data node range through CQ L, so as to generate a corresponding data node link relationship and share the data link interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010262281.3A CN111475682A (en) | 2020-04-06 | 2020-04-06 | Intelligent operation and maintenance platform based on super-large-scale data system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010262281.3A CN111475682A (en) | 2020-04-06 | 2020-04-06 | Intelligent operation and maintenance platform based on super-large-scale data system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111475682A true CN111475682A (en) | 2020-07-31 |
Family
ID=71749744
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010262281.3A Pending CN111475682A (en) | 2020-04-06 | 2020-04-06 | Intelligent operation and maintenance platform based on super-large-scale data system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111475682A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112446031A (en) * | 2020-10-26 | 2021-03-05 | 国网安徽省电力有限公司信息通信分公司 | Operation and maintenance data display platform based on artificial intelligence |
| CN112989150A (en) * | 2021-02-08 | 2021-06-18 | 中国农业银行股份有限公司 | Operation and maintenance diagram acquisition method, device, equipment and readable storage medium |
| CN113067716A (en) * | 2020-08-03 | 2021-07-02 | 安徽高颐科技有限公司 | Intelligent big data billboard sharing method based on operation and maintenance system |
| CN113468159A (en) * | 2021-07-19 | 2021-10-01 | 广东电网有限责任公司 | Data application full-link management and control method and system |
| CN113742017A (en) * | 2021-08-30 | 2021-12-03 | 广东电网有限责任公司 | Display method and device of power data, storage medium and electronic equipment |
| CN114143177A (en) * | 2021-12-01 | 2022-03-04 | 云赛智联股份有限公司 | Business service monitoring system and monitoring method based on data blood margin |
| WO2022142012A1 (en) * | 2020-12-29 | 2022-07-07 | 平安科技（深圳）有限公司 | Script configuration adjustment method and apparatus, electronic device, and storage medium |
| CN115220624A (en) * | 2022-06-13 | 2022-10-21 | 北京元年科技股份有限公司 | Link highlight display method, device, equipment and computer readable storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8285656B1 (en) * | 2007-03-30 | 2012-10-09 | Consumerinfo.Com, Inc. | Systems and methods for data verification |
| CN103888287A (en) * | 2013-12-18 | 2014-06-25 | 北京首都国际机场股份有限公司 | Information system integrated operation and maintenance monitoring service early warning platform and realization method thereof |
| CN105119750A (en) * | 2015-09-08 | 2015-12-02 | 南京联成科技发展有限公司 | Distributed information security operation and maintenance management platform based on massive data |
| CN105825314A (en) * | 2015-01-08 | 2016-08-03 | 国家电网公司 | Monitoring information analysis method and system based on centralized operation and maintenance mode |
| CN109299044A (en) * | 2018-07-20 | 2019-02-01 | 浙江工业大学 | A kind of secure visual analysis system based on intra-company's log |
| CN109343995A (en) * | 2018-10-25 | 2019-02-15 | 金税信息技术服务股份有限公司 | Intelligent O&M analysis system based on multi-source heterogeneous data fusion, machine learning and customer service robot |
| CN110245270A (en) * | 2019-05-09 | 2019-09-17 | 重庆天蓬网络有限公司 | Data genetic connection storage method, system, medium and equipment based on graph model |
-
2020
- 2020-04-06 CN CN202010262281.3A patent/CN111475682A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8285656B1 (en) * | 2007-03-30 | 2012-10-09 | Consumerinfo.Com, Inc. | Systems and methods for data verification |
| CN103888287A (en) * | 2013-12-18 | 2014-06-25 | 北京首都国际机场股份有限公司 | Information system integrated operation and maintenance monitoring service early warning platform and realization method thereof |
| CN105825314A (en) * | 2015-01-08 | 2016-08-03 | 国家电网公司 | Monitoring information analysis method and system based on centralized operation and maintenance mode |
| CN105119750A (en) * | 2015-09-08 | 2015-12-02 | 南京联成科技发展有限公司 | Distributed information security operation and maintenance management platform based on massive data |
| CN109299044A (en) * | 2018-07-20 | 2019-02-01 | 浙江工业大学 | A kind of secure visual analysis system based on intra-company's log |
| CN109343995A (en) * | 2018-10-25 | 2019-02-15 | 金税信息技术服务股份有限公司 | Intelligent O&M analysis system based on multi-source heterogeneous data fusion, machine learning and customer service robot |
| CN110245270A (en) * | 2019-05-09 | 2019-09-17 | 重庆天蓬网络有限公司 | Data genetic connection storage method, system, medium and equipment based on graph model |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113067716A (en) * | 2020-08-03 | 2021-07-02 | 安徽高颐科技有限公司 | Intelligent big data billboard sharing method based on operation and maintenance system |
| CN112446031A (en) * | 2020-10-26 | 2021-03-05 | 国网安徽省电力有限公司信息通信分公司 | Operation and maintenance data display platform based on artificial intelligence |
| WO2022142012A1 (en) * | 2020-12-29 | 2022-07-07 | 平安科技（深圳）有限公司 | Script configuration adjustment method and apparatus, electronic device, and storage medium |
| CN112989150A (en) * | 2021-02-08 | 2021-06-18 | 中国农业银行股份有限公司 | Operation and maintenance diagram acquisition method, device, equipment and readable storage medium |
| CN113468159A (en) * | 2021-07-19 | 2021-10-01 | 广东电网有限责任公司 | Data application full-link management and control method and system |
| CN113742017A (en) * | 2021-08-30 | 2021-12-03 | 广东电网有限责任公司 | Display method and device of power data, storage medium and electronic equipment |
| CN114143177A (en) * | 2021-12-01 | 2022-03-04 | 云赛智联股份有限公司 | Business service monitoring system and monitoring method based on data blood margin |
| CN115220624A (en) * | 2022-06-13 | 2022-10-21 | 北京元年科技股份有限公司 | Link highlight display method, device, equipment and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111475682A (en) | Intelligent operation and maintenance platform based on super-large-scale data system | |
| Jacob et al. | Exathlon: A benchmark for explainable anomaly detection over time series | |
| US9590880B2 (en) | Dynamic collection analysis and reporting of telemetry data | |
| US8547379B2 (en) | Systems, methods, and media for generating multidimensional heat maps | |
| CN108039959B (en) | Data situation perception method, system and related device | |
| US11321327B2 (en) | Intelligence situational awareness | |
| WO2019182750A1 (en) | Multi-variant anomaly detection from application telemetry | |
| El‐Hasnony et al. | Leveraging mist and fog for big data analytics in IoT environment | |
| US11528207B1 (en) | Computing system monitor auditing | |
| Fu et al. | Real-time data infrastructure at uber | |
| CN109639791A (en) | Cloud workflow schedule method and system under a kind of container environment | |
| CN112395333B (en) | Method, device, electronic equipment and storage medium for checking data abnormality | |
| CN114265680A (en) | Mass data processing method and device, electronic equipment and storage medium | |
| Shilpika et al. | MELA: A visual analytics tool for studying multifidelity hpc system logs | |
| CN114090378A (en) | Custom monitoring and alarming method based on Kapacitor | |
| Romero et al. | Integration of DevOps practices on a noise monitor system with CircleCI and Terraform | |
| Xu et al. | Cloud computing boosts business intelligence of telecommunication industry | |
| US11392375B1 (en) | Optimizing software codebases using advanced code complexity metrics | |
| Calderon et al. | Monitoring Framework for the Performance Evaluation of an IoT Platform with Elasticsearch and Apache Kafka | |
| Daki et al. | Towards adopting Big Data technologies by mobile networks operators: A Moroccan case study | |
| Sanila et al. | Real-time mining techniques: a big data perspective for a smart future | |
| Bosch et al. | Towards automated detection of data pipeline faults | |
| CN112148347A (en) | Method and device for full-process traceability management | |
| Scheinert et al. | Perona: Robust infrastructure fingerprinting for resource-efficient big data analytics | |
| Li et al. | A sensor-based approach to symptom recognition for autonomic systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |