WO2020147336A1 - 一种微服务全链路监控系统及方法 - Google Patents
一种微服务全链路监控系统及方法 Download PDFInfo
- Publication number
- WO2020147336A1 WO2020147336A1 PCT/CN2019/106865 CN2019106865W WO2020147336A1 WO 2020147336 A1 WO2020147336 A1 WO 2020147336A1 CN 2019106865 W CN2019106865 W CN 2019106865W WO 2020147336 A1 WO2020147336 A1 WO 2020147336A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- service
- link
- module
- monitoring
- node
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/50—Testing arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
- G06F11/324—Display of status information
- G06F11/327—Alarm or error message display
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/805—Real-time
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/865—Monitoring of software
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
Definitions
- the invention relates to the technical field of microservices, in particular to a microservice full-link monitoring system and method.
- microservice design model has been popularized in China.
- the microservice design model encourages service splitting and facilitates code decoupling, but it also brings new problems, which increase the dependency between services.
- a service often depends on multiple underlying layers. Services, the call link is deeper, and nested calls of more than three levels of services are becoming more and more common. Therefore, many problems need to be solved urgently: it is difficult to locate the problem and the performance bottleneck is difficult to find.
- the embodiments of the present invention provide a microservice full-link monitoring system and method, which solves the problem of link embedding of cross-thread calling services, no code intrusion, and greatly improved monitoring convenience and availability ; It solves the problem of cross-thread link transfer, without hard coding for cross-thread link transfer; provides distributed expansion capabilities, suitable for large-scale scenarios.
- the technical solution is as follows:
- a microservice full-link monitoring system includes:
- Collection framework module used to collect service call data and perform link serialization
- the message queue module is used to receive service invocation data from the collection framework module in real time;
- the computing center module is used to subscribe service call data to the message queue module, and aggregate and store it in real time;
- the monitoring center module is used to read the monitoring data stored in the computing center module and provide monitoring functions;
- the message queue module and the computing center module both adopt a distributed deployment mode.
- the collection framework module is used to collect service invocation data including link ID, node ID, service name, request parameters, server IP, and response time.
- the collection framework module is used to set the link ID and node ID for the current service or generate a new link according to the link ID and node ID passed by the caller ID, node ID.
- the link ID is TraceID
- the node ID is SpanID
- the message queue module adopts the Kafka architecture, and/or, the computing center module adopts the Druid architecture.
- the monitoring center module is used to read the monitoring data stored by the computing center module, and provide information including call link display, search, monitoring, and alarms. Monitoring function.
- a micro-service full-link monitoring method combined with the micro-service full-link monitoring system described in the first aspect is provided, the method includes a data collection step, and the data collection step specifically includes the following sub-steps:
- the collection framework module generates the link ID for this call, and the first node ID for the current request,
- the first service calls the second service
- the collection framework module obtains the currently called link ID and node ID, generates a second node ID for the second service, and passes the link ID and the second node ID to the second service through parameters;
- the collection framework module sets the current link ID and node ID according to the passed link ID and node ID;
- the second service starts the child thread to call the third service, and the parent thread automatically inherits the link ID and node ID information to the child thread;
- the collection framework module obtains the currently called link ID and node ID, generates a third node ID for the third service, and passes the link ID and the second node ID to the third service through parameters;
- the second service starts the child thread to call the fourth service, and the parent thread automatically inherits the link ID and node ID information to the child thread;
- the collection framework module obtains the currently called link ID and node ID, generates a fourth node ID for the third service, and transmits the link ID and the third node ID to the third service through parameters.
- the data collection step specifically includes the following sub-steps:
- the collection framework module generates TraceID for this call, and generates the first SpanID for the current request,
- the first service calls the second service
- the collection framework module obtains the currently called TraceID and SpanID, generates a second SpanID for the second service, and passes the TraceID and the second SpanID to the second service through parameters;
- the second service processing request the collection framework module sets the current TraceID and SpanID according to the passed TraceID and SpanID;
- the second service starts the child thread to call the third service, and the parent thread automatically inherits TraceID and SpanID information to the child thread;
- the collection framework module obtains the currently called TraceID and SpanID, generates a third SpanID for the third service, and passes the TraceID and the second SpanID to the third service through parameters;
- the second service starts the child thread to call the fourth service, and the parent thread automatically inherits TraceID and SpanID information to the child thread;
- the collection framework module obtains the currently called TraceID and SpanID, generates a fourth SpanID for the third service, and passes the TraceID and the third SpanID to the third service through parameters.
- the method further includes a data analysis processing step, and the data analysis processing step specifically includes the following sub-steps:
- the collection framework module collects service invocation data and sends it to the message queue module;
- the computing center module pulls the service invocation data from the message queue module for aggregate storage
- the monitoring center module reads monitoring data from the computing center module, and provides monitoring functions including call link display, search, monitoring, and alarm.
- the data analysis processing step specifically includes the following sub-steps:
- the collection framework module collects service invocation data and sends it to the message queue module of the Kafka architecture;
- the computing center module of the Druid architecture pulls the service call data from the message queue module of the Kafka architecture for aggregate storage;
- the monitoring center module reads monitoring data from the computing center module of the Druid architecture, and provides monitoring functions including call link display, search, monitoring, and alarm.
- monitoring content through the configuration method (link ID, node ID, system ID, caller system ID, server IP, service name, service type, processing start time, processing end time, request parameters, user ID, response time, etc. ), which makes the monitoring information configurable; monitoring data is sent to Kafka in real time, and then aggregated and stored in Druid in real time.
- the monitoring center can read druid data in real time for display and monitoring, with high real-time performance, plus excellent open source frameworks such as kafka and Druid , High throughput, strong computing power, provides distributed expansion capabilities, suitable for large-scale scenarios;
- the code starts the child thread to call the service, and it can automatically obtain the TraceId (link id) and spanId (node id) of the parent thread, thereby ensuring the integrity of the entire link and solving the problem of cross-thread link transfer without hard coding Perform cross-thread link delivery.
- Figure 1 is a schematic structural diagram of a microservice full link monitoring system provided by an embodiment of the present invention
- Figure 2 is a working demonstration diagram of the overall architecture of the microservice full link monitoring system provided by an embodiment of the present invention, taking the Http service based on the Spring Mvc framework as an example;
- FIG. 3 is a schematic flowchart of a microservice full link monitoring method of a microservice full link monitoring system provided by an embodiment of the present invention
- Figure 4 is a link page display diagram of the microservice full link monitoring system for full link monitoring provided by an embodiment of the present invention
- Fig. 5 is a link page display diagram of the microservice full link monitoring system for full link monitoring provided by an embodiment of the present invention.
- microservice full-link monitoring system and method provided by the embodiments of the present invention provide embedded plug-ins for mainstream frameworks such as Spring Mvc, Thrift, Dubbo, Hessian, Protobuf-RPC, Okttp, Rsf, and provide annotation AOP support for Java, Easy to use, you can perform full-link monitoring with simple configuration, which solves the problem of link burying in cross-thread calling services, without code intrusion, and greatly improves the convenience and availability of monitoring; select the monitoring content through the configuration method to make monitoring Information is configurable; monitoring data is sent to Kafka in real time, and then aggregated and stored in Druid in real time.
- mainstream frameworks such as Spring Mvc, Thrift, Dubbo, Hessian, Protobuf-RPC, Okttp, Rsf, and provide annotation AOP support for Java, Easy to use, you can perform full-link monitoring with simple configuration, which solves the problem of link burying in cross-thread calling services, without code intrusion, and greatly improves the
- the monitoring center can read druid data in real time, display and monitor, with high real-time performance, coupled with excellent open source frameworks such as kafka and Druid, and high throughput , Strong computing power, provides distributed scalability, suitable for large-scale scenarios; code starts the child thread to call the service, and can automatically obtain the TraceId (link id) and spanId (node id) of the parent thread to ensure the integrity of the entire link , Which solves the problem of cross-thread link transfer, without hard coding for cross-thread link transfer. Therefore, the micro-service full-link monitoring system and method provided by the embodiments of the present invention can be widely used for full-link monitoring in various micro-service scenarios.
- FIG. 1 is a schematic structural diagram of a microservice full-link monitoring system provided by an embodiment of the present invention.
- the microservice full-link monitoring system provided by the embodiment of the present invention includes a collection framework module 11, a message queue module 12, a computing center module 13, and a monitoring center module 41.
- the collection framework module 11 is used to collect service call data and perform link series connection.
- collecting service invocation data includes: collecting service invocation data including link ID, node ID, service name, request parameters, server IP, and response time.
- the collection framework module 11 collects link ID, node ID, system ID, caller system ID, server IP, service name, service type, processing start time, processing end time, request parameters, user ID, response time, etc. Service call data.
- the monitoring content is selected through the configuration mode, so as to collect various service invocation data, which is not particularly limited in the embodiment of the present invention.
- the process of link serialization may specifically include: setting the link ID and node ID for the current service or generating a new link ID and node ID according to the link ID and node ID passed by the caller.
- the link ID is set to TraceID
- the node ID is set to SpanID.
- the message queue module 12 is used to receive the service call data from the collection framework module 11 in real time; the computing center module 13 is used to subscribe the service call data to the message queue module 12 to aggregate and store in real time; the monitoring center module 41 is used to read Take the monitoring data stored in the computing center module 13 and provide monitoring functions.
- the message queue module 12 and the computing center module 13 both adopt a distributed deployment mode.
- the message queue module 12 adopts the Kafka architecture, and the computing center module 13 adopts the Druid architecture.
- the monitoring center module 41 is used to read the monitoring data stored by the computing center module 13 and provide monitoring functions including call link display, search, monitoring, and alarm.
- Figure 2 is a working demonstration diagram of the overall architecture of the microservice full-link monitoring system provided by an embodiment of the present invention, taking the Http service based on the Spring Mvc framework as an example.
- Fig. 3 is a schematic flow chart of a micro-service full-link monitoring method of a micro-service full-link monitoring system provided by an embodiment of the present invention, which also takes the Http service based on the Spring Mvc framework as an example.
- Figures 4 and 5 are diagrams showing the link pages of the microservice full-link monitoring system for full-link monitoring provided by an embodiment of the present invention.
- the micro-service full-link monitoring method of the micro-service full-link monitoring system provided by the embodiment of the present invention includes a data collection step and a data analysis processing step.
- the first service takes service A as an example
- the second service takes service B as an example
- the third service takes service C as an example
- the fourth service takes service D as an example
- the first node ID is 0 as an example
- the second node The ID is 0.1 as an example
- the third node ID is 0.1.1
- the fourth node is 0.1.2
- the first SpanID is SpanID:0 as an example
- the second SpanID is SpanID:0.1 as an example.
- the third SpanID takes SpanID: 0.1.1 as an example
- the fourth SpanID takes SpanID: 0.1.2 as an example.
- the data collection step specifically includes the following sub-steps:
- the page requests the first service (service A);
- the collection framework module generates the link ID for this call, and the first node ID (0) for the current request,
- the first service (service A) calls the second service (service B);
- the collection framework module obtains the currently called link ID and node ID, generates a second node ID (0.1) for the second service (service B), and passes the link ID and second node ID to the second service (service B) through parameters. );
- the second service processes the request, and the collection framework module sets the current link ID and node ID according to the passed link ID and node ID;
- the second service (service B) starts the child thread to call the third service (service C), and the parent thread automatically inherits the link ID and node ID information to the child thread;
- the collection framework module obtains the currently called link ID and node ID, generates the third node ID (0.1.1) for the third service (service C), and passes the link ID and second node ID (0.1) to the first Three services (service C);
- the second service (service B) starts the child thread to call the fourth service (service D), and the parent thread automatically inherits the link ID and node ID information to the child thread;
- the collection framework module obtains the currently called link ID and node ID, generates the fourth node ID (0.1.2) for the third service (service C), and passes the link ID and third node ID (0.1.1) through parameters Give the third service (service C).
- the above-mentioned data collection step is implemented in the following manner, specifically including the following sub-steps:
- the page requests the first service (service A);
- the collection framework module generates TraceID for this call, and generates the first SpanID (SpanID:0) for the current request,
- the first service (service A) calls the second service (service B);
- the acquisition framework module obtains the currently called TraceID and SpanID, generates a second SpanID (SpanID: 0.1) for the second service (service B), and passes the TraceID and the second SpanID to the second service (service B) through parameters;
- the second service processes the request, and the collection framework module sets the current TraceID and SpanID according to the passed TraceID and SpanID;
- the second service (service B) starts the child thread to call the third service (service C), and the parent thread automatically inherits TraceID and SpanID information to the child thread;
- the collection framework module obtains the currently called TraceID and SpanID, generates a third SpanID (SpanID: 0.1.1) for the third service (service C), and passes the TraceID and second SpanID to the third service (service C) through parameters;
- the second service (service B) starts the child thread to call the fourth service (service D), and the parent thread automatically inherits TraceID and SpanID information to the child thread;
- the collection framework module obtains the currently called TraceID and SpanID, generates a fourth SpanID (SpanID: 0.1.1) for the third service (service C), and passes the TraceID and third SpanID to the third service (service C) through parameters.
- the data analysis processing steps specifically include the following sub-steps:
- the collection framework module collects service call data and sends it to the message queue module;
- the computing center module pulls the service call data from the message queue module for aggregate storage
- the monitoring center module reads monitoring data from the computing center module, and provides monitoring functions including call link display, search, monitoring, and alarms.
- the collection framework module collects service call data and sends it to the message queue module of the Kafka architecture
- the computing center module of the Druid architecture pulls the service call data from the message queue module of the Kafka architecture for aggregate storage;
- the monitoring center module reads monitoring data from the computing center module of the Druid architecture, and provides monitoring functions including call link display, search, monitoring, and alarms.
- micro-service full-link monitoring system when the micro-service full-link monitoring system provided in the above embodiment triggers the micro-service full-link monitoring service, it only uses the division of the above-mentioned functional modules for illustration. In actual applications, the above-mentioned Function allocation is completed by different functional modules, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above.
- the micro-service full-link monitoring system provided by the foregoing embodiment belongs to the same concept as the micro-service full-link monitoring method of the embodiment. For the specific implementation process, please refer to the method embodiment, which will not be repeated here.
- microservice full-link monitoring system and method provided by the embodiments of the present invention have the following beneficial effects compared with the prior art:
- the monitoring content through the configuration method (link ID, node ID, system ID, caller system ID, server IP, service name, service type, processing start time, processing end time, request parameters, user ID, response time, etc. ), which makes the monitoring information configurable; the monitoring data is sent to Kafka in real time, and then aggregated and stored in Druid in real time.
- the monitoring center can read druid data in real time, display and monitor, with high real-time performance, plus excellent open source frameworks such as kafka and Druid , High throughput, strong computing power, provides distributed expansion capabilities, suitable for large-scale scenarios;
- the code starts the child thread to call the service, and it can automatically obtain the TraceId (link id) and spanId (node id) of the parent thread, thereby ensuring the integrity of the entire link and solving the problem of cross-thread link transfer without hard coding Perform cross-thread link delivery.
- the program can be stored in a computer-readable storage medium.
- the storage medium mentioned can be a read-only memory, a magnetic disk or an optical disk, etc.
- each flow and/or block in the flowchart and/or block diagram and a combination of the flow and/or block in the flowchart and/or block diagram may be implemented by computer program instructions.
- These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated
- a device that implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.
- These computer program instructions may also be stored in a computer readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, the instructions
- the device implements the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and/or block diagrams.
- These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operating steps are performed on the computer or other programmable device to generate computer-implemented processing, which is executed on the computer or other programmable device
- the instructions provide steps for implementing the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and/or block diagrams.
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Telephonic Communication Services (AREA)
- Debugging And Monitoring (AREA)
Abstract
Description
Claims (10)
- 一种微服务全链路监控系统,其特征在于,所述系统包括:采集框架模块,用于采集服务调用数据和进行链路串联;消息队列模块,用于实时接收来自所述采集框架模块的服务调用数据;计算中心模块,用于向所述消息队列模块订阅服务调用数据,实时聚合存储;监控中心模块,用于读取所述计算中心模块存储的监控数据,并提供监控功能;其中,所述消息队列模块和所述计算中心模块均采用分布式部署方式。
- 根据权利要求1所述的系统,其特征在于,所述采集框架模块用于采集包括链路ID、节点ID、服务名称、请求参数、服务器IP、响应时间在内的服务调用数据。
- 根据权利要求1所述的系统,其特征在于,所述采集框架模块用于根据调用方传递过来的链路ID、节点ID为当前服务设置链路ID、节点ID或生成新的链路ID、节点ID。
- 根据权利要求2或3所述的系统,其特征在于,所述链路ID为TraceID,所述节点ID为SpanID。
- 根据权利要求1所述的系统,其特征在于,所述消息队列模块采用Kafka架构,和/或,所述计算中心模块采用Druid架构。
- 根据权利要求1所述的系统,其特征在于,所述监控中心模块用于读取所述计算中心模块存储的监控数据,并提供包括调用链路展示、搜索、监控、告警在内的监控功能。
- 一种应用于如权利要求1至3任一项所述的微服务全链路监控系统的微服务全链路监控方法,其特征在于,所述方法包括数据采集步骤,所述数据采集步骤具体包括以下子步骤:请求第一服务;所述采集框架模块为本次调用生成链路ID,为当前请求生成第一节点ID,所述第一服务调用第二服务;所述采集框架模块获取当前调用的链路ID、节点ID,为第二服务生成第二节点ID,将链路ID、第二节点ID通过参数传递给第二服务;第二服务处理请求,所述采集框架模块根据传递过来的链路ID、节点ID设置为当前的链路ID、节点ID;第二服务启动子线程调用第三服务,父线程将链路ID、节点ID信息自动继承给子线程;所述采集框架模块获取当前调用的链路ID、节点ID,为第三服务生成第三节点ID,将链路ID、第二节点ID通过参数传递给第三服务;第二服务启动子线程调用第四服务,父线程将链路ID、节点ID信息自动继承给子线程;所述采集框架模块获取当前调用的链路ID、节点ID,为第三服务生成第四节点ID,将链路ID、第三节点ID通过参数传递给第三服务。
- 根据权利要求7所述的微服务全链路监控方法,其特征在于,所述数据采集步骤具体包括以下子步骤:请求第一服务;所述采集框架模块为本次调用生成TraceID,为当前请求生成第一SpanID,所述第一服务调用第二服务;所述采集框架模块获取当前调用的TraceID、SpanID,为第二服务生成第二SpanID,将TraceID、第二SpanID通过参数传递给第二服务;第二服务处理请求,所述采集框架模块根据传递过来的TraceID、SpanID设置为当前的TraceID、SpanID;第二服务启动子线程调用第三服务,父线程将TraceID、SpanID信息自动继承给子线程;所述采集框架模块获取当前调用的TraceID、SpanID,为第三服务生成第三SpanID,将TraceID、第二SpanID通过参数传递给第三服务;第二服务启动子线程调用第四服务,父线程将TraceID、SpanID信息自动继承给子线程;所述采集框架模块获取当前调用的TraceID、SpanID,为第三服务生成第四SpanID,将TraceID、第三SpanID通过参数传递给第三服务。
- 根据权利要求7所述的全链路监控方法,其特征在于,所述方法还包括数据分析处理步骤,所述数据分析处理步骤具体包括以下子步骤:所述采集框架模块采集服务调用数据,发送至所述消息队列模块;所述计算中心模块从所述消息队列模块拉取服务调用数据,进行聚合存储;所述监控中心模块从所述计算中心模块读取监控数据,提供包括调用链路展示、搜索、监控、告警在内的监控功能。
- 根据权利要求9所述的全链路监控方法,其特征在于,所述数据分析处理步骤具体包括以下子步骤:所述采集框架模块采集服务调用数据,发送至Kafka架构的所述消息队列模块;Druid架构的所述计算中心模块从Kafka架构的所述消息队列模块拉取服务调用数据,进行聚合存储;所述监控中心模块从Druid架构的所述计算中心模块读取监控数据,提供包括调用链路展示、搜索、监控、告警在内的监控功能。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CA3168303A CA3168303A1 (en) | 2019-01-18 | 2019-09-20 | Microservice full-link monitoring system and method |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910048998.5A CN111464373A (zh) | 2019-01-18 | 2019-01-18 | 一种微服务全链路监控系统及方法 |
CN201910048998.5 | 2019-01-18 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2020147336A1 true WO2020147336A1 (zh) | 2020-07-23 |
Family
ID=71614006
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2019/106865 WO2020147336A1 (zh) | 2019-01-18 | 2019-09-20 | 一种微服务全链路监控系统及方法 |
Country Status (3)
Country | Link |
---|---|
CN (1) | CN111464373A (zh) |
CA (2) | CA3235906A1 (zh) |
WO (1) | WO2020147336A1 (zh) |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112486786A (zh) * | 2020-11-12 | 2021-03-12 | 贝壳技术有限公司 | 一种调用链路追踪方法及装置 |
CN112770137A (zh) * | 2020-12-31 | 2021-05-07 | 重庆空间视创科技有限公司 | 基于微服务数据采集方法 |
CN113157478A (zh) * | 2021-04-21 | 2021-07-23 | 多点(深圳)数字科技有限公司 | 一种分布式系统配置化数据采集和业务报警系统 |
CN114629944A (zh) * | 2020-12-11 | 2022-06-14 | 来未来科技(浙江)有限公司 | 一种静态分析微服务系统全链路调用情况的方法 |
CN115314542A (zh) * | 2021-04-21 | 2022-11-08 | 深圳联友科技有限公司 | 基于Socket通信协议的链路追踪方法及系统 |
CN116737514A (zh) * | 2023-08-15 | 2023-09-12 | 南京国睿信维软件有限公司 | 一种基于日志与探针解析自动化运维方法 |
Families Citing this family (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111934793B (zh) * | 2020-07-31 | 2022-08-02 | 中国工商银行股份有限公司 | 一种互联网架构全链路监控方法及装置 |
CN112330147A (zh) * | 2020-11-04 | 2021-02-05 | 北京思特奇信息技术股份有限公司 | 一种业务受理信息监控方法、装置及存储介质 |
CN112311894A (zh) * | 2020-11-12 | 2021-02-02 | 北京沃东天骏信息技术有限公司 | 用于生成信息的方法、装置、电子设备和计算机可读介质 |
CN112527537B (zh) * | 2020-11-30 | 2023-10-27 | 北京百度网讯科技有限公司 | 在线服务系统的质量监控方法、装置、设备和介质 |
CN113114533B (zh) * | 2021-04-08 | 2023-04-07 | 中国工商银行股份有限公司 | 分布式服务调用的网络耗时展示方法及装置 |
CN113111374B (zh) * | 2021-05-13 | 2022-09-23 | 上海交通大学 | 一种端边云的工业微服务系统、数据交互方法及介质 |
CN115473839B (zh) * | 2021-06-11 | 2024-03-05 | 北京字跳网络技术有限公司 | 基于埋点的数据处理方法、装置、设备及存储介质 |
CN113986955B (zh) * | 2021-11-01 | 2024-03-19 | 华青融天(北京)软件股份有限公司 | 业务链的确定方法、装置、电子设备及介质 |
CN114172949A (zh) * | 2021-12-10 | 2022-03-11 | 航天信息股份有限公司 | 一种微服务链路监控追踪方法和系统 |
CN114710430A (zh) * | 2022-04-06 | 2022-07-05 | 深圳依时货拉拉科技有限公司 | 双向通信的管控方法、计算机可读存储介质和计算机设备 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150063102A1 (en) * | 2013-08-30 | 2015-03-05 | Cisco Technology, Inc. | Flow Based Network Service Insertion |
CN106790718A (zh) * | 2017-03-16 | 2017-05-31 | 北京搜狐新媒体信息技术有限公司 | 服务调用链路分析方法及系统 |
CN108173915A (zh) * | 2017-12-21 | 2018-06-15 | 中国联合网络通信集团有限公司 | 调用链处理方法及装置 |
CN108183927A (zh) * | 2017-11-22 | 2018-06-19 | 链家网(北京)科技有限公司 | 一种分布式系统中链路调用的监控方法及系统 |
Family Cites Families (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10069891B2 (en) * | 2015-09-30 | 2018-09-04 | Bank Of America Corporation | Channel accessible single function micro service data collection process for light analytics |
CN105608188A (zh) * | 2015-12-23 | 2016-05-25 | 北京奇虎科技有限公司 | 数据处理方法和数据处理装置 |
CN107038162B (zh) * | 2016-02-03 | 2021-03-02 | 北京嘀嘀无限科技发展有限公司 | 基于数据库日志的实时数据查询方法和系统 |
US20180026856A1 (en) * | 2016-07-21 | 2018-01-25 | Cisco Technology, Inc. | Orchestrating micro-service deployment based on network policy health |
CN106487596B (zh) * | 2016-10-26 | 2019-12-13 | 宜人恒业科技发展(北京)有限公司 | 分布式服务跟踪实现方法 |
CN106656604A (zh) * | 2016-12-23 | 2017-05-10 | 郑州云海信息技术有限公司 | 微服务请求管理方法、微服务控制器及高并发微服务架构 |
US10841181B2 (en) * | 2017-02-24 | 2020-11-17 | Ciena Corporation | Monitoring and auto-correction systems and methods for microservices |
CN108696400A (zh) * | 2017-04-12 | 2018-10-23 | 北京京东尚科信息技术有限公司 | 网络监测方法和装置 |
CN108153850A (zh) * | 2017-06-01 | 2018-06-12 | 广州舜飞信息科技有限公司 | 一种用户行为统计分析方法及系统 |
CN107135276A (zh) * | 2017-06-28 | 2017-09-05 | 北京中电普华信息技术有限公司 | 一种微服务架构下的全链路监控方法、装置和系统 |
CN107766205B (zh) * | 2017-10-10 | 2019-11-22 | 武汉大学 | 一种面向微服务调用过程跟踪的监控系统及方法 |
CN107979508B (zh) * | 2017-11-24 | 2020-08-04 | 深圳乐信软件技术有限公司 | 微服务测试方法及装置 |
-
2019
- 2019-01-18 CN CN201910048998.5A patent/CN111464373A/zh active Pending
- 2019-09-20 CA CA3235906A patent/CA3235906A1/en active Pending
- 2019-09-20 CA CA3168303A patent/CA3168303A1/en active Pending
- 2019-09-20 WO PCT/CN2019/106865 patent/WO2020147336A1/zh active Application Filing
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150063102A1 (en) * | 2013-08-30 | 2015-03-05 | Cisco Technology, Inc. | Flow Based Network Service Insertion |
CN106790718A (zh) * | 2017-03-16 | 2017-05-31 | 北京搜狐新媒体信息技术有限公司 | 服务调用链路分析方法及系统 |
CN108183927A (zh) * | 2017-11-22 | 2018-06-19 | 链家网(北京)科技有限公司 | 一种分布式系统中链路调用的监控方法及系统 |
CN108173915A (zh) * | 2017-12-21 | 2018-06-15 | 中国联合网络通信集团有限公司 | 调用链处理方法及装置 |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112486786A (zh) * | 2020-11-12 | 2021-03-12 | 贝壳技术有限公司 | 一种调用链路追踪方法及装置 |
CN114629944A (zh) * | 2020-12-11 | 2022-06-14 | 来未来科技(浙江)有限公司 | 一种静态分析微服务系统全链路调用情况的方法 |
CN114629944B (zh) * | 2020-12-11 | 2024-05-14 | 来未来科技(浙江)有限公司 | 一种静态分析微服务系统全链路调用情况的方法 |
CN112770137A (zh) * | 2020-12-31 | 2021-05-07 | 重庆空间视创科技有限公司 | 基于微服务数据采集方法 |
CN112770137B (zh) * | 2020-12-31 | 2022-06-17 | 重庆空间视创科技有限公司 | 基于微服务数据采集方法 |
CN113157478A (zh) * | 2021-04-21 | 2021-07-23 | 多点(深圳)数字科技有限公司 | 一种分布式系统配置化数据采集和业务报警系统 |
CN115314542A (zh) * | 2021-04-21 | 2022-11-08 | 深圳联友科技有限公司 | 基于Socket通信协议的链路追踪方法及系统 |
CN113157478B (zh) * | 2021-04-21 | 2024-05-10 | 多点(深圳)数字科技有限公司 | 一种分布式系统配置化数据采集和业务报警系统 |
CN116737514A (zh) * | 2023-08-15 | 2023-09-12 | 南京国睿信维软件有限公司 | 一种基于日志与探针解析自动化运维方法 |
CN116737514B (zh) * | 2023-08-15 | 2023-12-22 | 南京国睿信维软件有限公司 | 一种基于日志与探针解析自动化运维方法 |
Also Published As
Publication number | Publication date |
---|---|
CA3235906A1 (en) | 2020-07-23 |
CN111464373A (zh) | 2020-07-28 |
CA3168303A1 (en) | 2020-07-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2020147336A1 (zh) | 一种微服务全链路监控系统及方法 | |
CN111049705B (zh) | 一种监控分布式存储系统的方法及装置 | |
US20200366564A1 (en) | Continuous data sensing of functional states of networked computing devices to determine efficiency metrics for servicing electronic messages asynchronously | |
US20130080502A1 (en) | User interface responsiveness monitor | |
CN111752799A (zh) | 一种业务链路跟踪方法、装置、设备及储存介质 | |
CN111124830B (zh) | 一种微服务的监控方法及装置 | |
WO2020087830A1 (zh) | 数据分析方法、装置、服务器及存储介质 | |
KR20210005043A (ko) | 입력 및 출력 스키마 매핑 | |
CN104657497A (zh) | 一种基于分布式计算的海量用电信息并行计算系统及方法 | |
CN111966289A (zh) | 基于Kafka集群的分区优化方法和系统 | |
CN112905323B (zh) | 数据处理方法、装置、电子设备及存储介质 | |
CN113037722B (zh) | 一种边缘计算场景的入侵检测方法及设备 | |
CN108549592A (zh) | 一种数据库连接池的监控方法及监控设备、应用服务器 | |
CN110557291A (zh) | 一种网络服务监控系统 | |
CN114745295A (zh) | 数据采集方法、装置、设备和可读存储介质 | |
CN111124609A (zh) | 数据采集方法、装置、数据采集设备及存储介质 | |
CN114090378A (zh) | 一种基于Kapacitor的自定义监控告警方法 | |
CN111177237B (zh) | 一种数据处理系统、方法及装置 | |
CN110781180A (zh) | 一种数据筛选方法和数据筛选装置 | |
CN106911784B (zh) | 一种执行异步事件的方法和装置 | |
CN109614271A (zh) | 多个集群数据一致性的控制方法、装置、设备及存储介质 | |
CN107704362A (zh) | 一种基于Ambari监控大数据组件的方法及装置 | |
CN117370053A (zh) | 一种面向信息系统业务运行全景监测方法及系统 | |
CN117435335A (zh) | 算力调度方法、装置、计算机设备和存储介质 | |
CN111949493A (zh) | 一种基于推理应用的边缘ai服务器功耗测试方法及装置 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 19910586 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 19910586 Country of ref document: EP Kind code of ref document: A1 |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 19910586 Country of ref document: EP Kind code of ref document: A1 |
|
ENP | Entry into the national phase |
Ref document number: 3168303 Country of ref document: CA |
|
32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 16.02.22) |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 19910586 Country of ref document: EP Kind code of ref document: A1 |