Single indicator parameter collection method and device based on application performance monitoring

Abstract

The present invention belongs to the field of big data technology. The present invention provides a single-indicator parameter collection method and device based on application performance monitoring. The single-indicator parameter collection method based on application performance monitoring includes: collecting performance monitoring single-indicator parameters in a vertical collection manner; sending the performance monitoring single-indicator parameters to the middleware; and performing aggregation calculation on the performance monitoring single-indicator parameters forwarded by the middleware. The present invention has the following beneficial effects: higher monitoring timeliness. The collection end reports immediately after collecting a certain indicator without waiting for other indicators, realizing true real-time monitoring and improving monitoring timeliness. Flexible configuration. The collection frequency of different indicators on the collection end can be flexibly configured. Save resources. The analysis of monitoring data is completely placed on the server end, and there is only data collection logic in the application, which minimizes the occupancy of application resources.

Description

Technical Field

[0001] The present application can be used in the field of big data technology, and specifically relates to a single indicator parameter collection method and device based on application performance monitoring. Background Art

[0002] In the existing technology, the collection of monitoring data usually requires the use of a tracking method to weave the collection logic into the application. For example, by tracking the receipt and response of a transaction, the transaction time can be obtained by subtracting the timestamp of the receipt from the timestamp of the response. For example, operating indicators are usually obtained on a regular basis, such as collecting key indicators that measure the health of the operating system (such as the system's CPU, memory, IO status, etc.) every minute, and then reporting the indicators in a unified manner. After receiving these monitoring data, the monitoring system can process, aggregate, and analyze the data, and then store the analysis results in a database for use by operation and maintenance personnel to troubleshoot problems.

[0003] A technical drawback of existing monitoring data collection methods is that data collection is prone to duplication. For example, for transactions, it's often necessary to wait until the transaction is complete before calculating the transaction duration. Monitoring operating system metrics requires a timed trigger, complete collection, and assembly of a data set, which is then reported to the monitoring system's server for analysis. This presents several challenges:

[0004] 1. The coupling of monitoring data with different monitoring frequencies. For example, with the collection and reporting of various operating system indicators, once the data model for the reporting interface is agreed upon, the collection end must collect all the monitoring data before reporting. However, sometimes a flexible approach is required. For example, if the operating system network I / O rarely experiences problems, it is desirable to appropriately reduce the collection frequency, which traditional solutions cannot achieve.

[0005] 2. Failure to maximize the monitoring system's data aggregation and analysis capabilities. Monitoring data is reported uniformly, meaning the monitoring system server cannot process the data until all data has been collected. This fails to maximize the server's data aggregation and analysis capabilities (which are typically very powerful when faced with massive amounts of monitoring data). For example, transaction duration doesn't need to be calculated on the collection side until a response is received. Instead, transactions can be reported at the start and end of each transaction, allowing the server to leverage its powerful computing power to calculate the duration of each transaction.

[0006] 3. Waste of application resources. As mentioned above, monitoring data collection logic (i.e., the client) is typically embedded within the application, sharing CPU, memory, and other resources with the application process. Batch reporting of data consumes a certain amount of resources. For example, the aforementioned transaction time calculations or other pre-aggregations, if performed on the client, will consume CPU computing resources. Another example is the scheduled collection of operating system metrics. Because they must wait until collection is complete before reporting, they must be temporarily stored in memory, occupying application storage resources. A more reasonable solution should minimize the impact on application operations. Summary of the Invention

[0007] The present invention can be used in the field of big data technology, and the application fields of the single-indicator parameter collection method and device based on application performance monitoring disclosed in the present invention are not limited. The present invention not only has the aggregate analysis capabilities of the existing technology, but also allows each indicator to be independently collected, reported, and analyzed without relying on other indicators, which is very flexible.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a single indicator parameter collection method based on application performance monitoring, comprising:

[0010] Collect single indicator parameters of performance monitoring in a vertical collection mode;

[0011] Sending the performance monitoring single indicator parameter to the middleware;

[0012] Aggregate and calculate the performance monitoring single indicator parameters forwarded by the middleware.

[0013] In one embodiment, the middleware is a Kafka middleware, and sending the performance monitoring single indicator parameter to the middleware includes:

[0014] Send the performance monitoring single indicator parameter to the topic table of the Kafka middleware.

[0015] In one embodiment, the performing of aggregate calculation on the performance monitoring single indicator parameter forwarded by the middleware includes:

[0016] Subscribe to the performance monitoring single indicator parameter from the topic table;

[0017] Store the performance monitoring single indicator parameters in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator;

[0018] The Druid database is used to perform aggregate calculations on the performance monitoring single indicator parameters.

[0019] In one embodiment, the aggregate calculation of the performance monitoring single indicator parameter using the Druid database includes:

[0020] The Druid database is used to aggregate and calculate the performance monitoring single indicator parameters according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time.

[0021] In a second aspect, the present invention provides a single indicator parameter collection device based on application performance monitoring, the device comprising:

[0022] Single indicator parameter collection module, used to collect single indicator parameters of performance monitoring in a vertical collection mode;

[0023] A single indicator parameter sending module is used to send the performance monitoring single indicator parameter to the middleware;

[0024] The single indicator parameter aggregation calculation module is used to perform aggregation calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0025] In one embodiment, the single indicator parameter sending module includes:

[0026] The single indicator parameter sending unit is used to send the performance monitoring single indicator parameter to the topic table of the Kafka middleware.

[0027] In one embodiment, the single indicator parameter aggregation calculation module includes:

[0028] A single indicator parameter subscription unit, configured to subscribe to the performance monitoring single indicator parameter from the topic table;

[0029] A single indicator parameter storage unit is used to store the performance monitoring single indicator parameter in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator;

[0030] The single indicator parameter aggregation calculation unit is used to use the Druid database to perform aggregation calculation on the performance monitoring single indicator parameter.

[0031] In one embodiment, the single indicator parameter aggregation calculation unit includes:

[0032] The single indicator parameter aggregation calculation subunit is used to use the Druid database to perform aggregation calculation on the performance monitoring single indicator parameter according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time.

[0033] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of a single-indicator parameter collection method based on application performance monitoring are implemented.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a single-indicator parameter collection method based on application performance monitoring.

[0035] As can be seen from the above description, the embodiments of the present invention provide a method and device for collecting single-indicator parameters based on application performance monitoring. First, the single-indicator parameters of performance monitoring are collected in a vertical manner; then, the single-indicator parameters of performance monitoring are sent to the middleware; and finally, the single-indicator parameters of performance monitoring forwarded by the middleware are aggregated and calculated. Specifically, the present invention has the following beneficial effects:

[0036] 1. Higher monitoring efficiency. When the collection end collects a certain indicator, it reports it immediately without waiting for other indicators, realizing true real-time monitoring and improving monitoring efficiency.

[0037] 2. Flexible configuration: The collection frequency of different indicators on the collection end can be flexibly configured.

[0038] 3. Resource saving: The analysis of monitoring data is completely placed on the server side, and the application only has data collection logic, which minimizes the use of application resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 Schematic diagram of a flow chart of a single indicator parameter collection method based on application performance monitoring in an embodiment of the present invention;

[0041] Figure 2 200 is a flow chart of step 200 in an embodiment of the present invention;

[0042] Figure 3 300 is a flowchart of an embodiment of the present invention;

[0043] Figure 4 103 is a flow chart of step 103 in an embodiment of the present invention;

[0044] Figure 5This is a flow chart of a single indicator parameter collection method based on application performance monitoring in a specific embodiment of the present invention;

[0045] Figure 6 A mind map of a single-index parameter collection method based on application performance monitoring in a specific embodiment of the present invention;

[0046] Figure 7 1 is a block diagram of a single indicator parameter collection device based on application performance monitoring in an embodiment of the present invention;

[0047] Figure 8 It is a block diagram of the single indicator parameter sending module 20 in a specific embodiment of the present invention;

[0048] Figure 9 This is a block diagram of the single index parameter aggregation calculation module 30 in a specific embodiment of the present invention;

[0049] Figure 10 This is a block diagram of the single index parameter aggregation calculation unit 303 in a specific embodiment of the present invention;

[0050] Figure 11 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0052] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0054] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0055] The embodiment of the present invention provides a specific implementation of a single indicator parameter collection method based on application performance monitoring, see Figure 1 , the method specifically includes the following contents:

[0056] Step 100: Collect performance monitoring single indicator parameters in a vertical collection manner.

[0057] Specifically, the horizontal reporting in the existing technology is changed to vertical reporting. For example, the traditional way of monitoring JVM (Java Virtual Machine) requires a timed thread to collect the memory and GC status of the JVM at regular intervals and report them uniformly. In this mode, the data model of the reporting interface is a collection of various indicators collected, such as the content usage of different generations (young generation, old generation, permanent generation) in the heap memory, the GC time consumption and the number of GC times of different generations. To put it in a more vivid way, these indicators are horizontally flattened in the interface, and each indicator is equal. Each indicator is reported independently, and is reported immediately as soon as it is collected, and is no longer flattened in a certain interface and reported at one time. Therefore, the data models of different indicators are also consistent, including indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID, and collection time.

[0058] Step 200: Send the performance monitoring single indicator parameter to the middleware.

[0059] It's understandable that middleware is a type of software that sits between application systems and system software. It leverages the basic services (functions) provided by system software to connect various components of networked application systems or applications, enabling resource and function sharing. Currently, there's no strict definition, but the generally accepted definition by IDC is: middleware is an independent system software service program that enables distributed applications to share resources across different technologies. Middleware resides on top of the client and server operating systems, managing computing resources and network communications. In this sense, middleware can be expressed as: middleware = platform + communication. This limits the term to only what is used in distributed systems, and also distinguishes it from support software and utility software.

[0060] Middleware is a type of computer software that connects software components and applications. It comprises a set of services, enabling multiple programs running on one or more machines to interact over a network. The interoperability provided by this technology has driven the evolution of consistent distributed architectures, which are commonly used to support and simplify complex distributed applications. This architecture includes web servers, transaction monitors, and message queue software. Middleware is a broad category of infrastructure software, often considered reusable. As the name suggests, middleware sits between the operating system and user applications.

[0061] Middleware sits above the operating system, network, and database, and beneath application software. Its overall purpose is to provide an operating and development environment for the applications above it, helping users flexibly and efficiently develop and integrate complex applications. Among the many definitions of middleware, the most widely accepted is the one by IDC: middleware is independent system software or service programs that enable distributed applications to share resources across different technologies. Middleware resides above the client and server operating systems, managing computing resources and network communications.

[0062] In recent years, more and more areas of human life have become inseparable from computers, network technologies, and communications technologies. Furthermore, with the rapid development of computer technology, more and more application software is required to operate on a variety of network protocols, hardware manufacturers, and network platforms and environments. This has led to software developers facing data fragmentation, operational difficulties, poor system compatibility, and the need to develop multiple applications to achieve operational goals. Therefore, the emergence of middleware technology has greatly reduced the burden on developers and made network operations more efficient.

[0063] Step 300: performing aggregate calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0064] Aggregation operation is to calculate a value from a set of values (perform custom aggregation operation on the values of the set). For example: merge, average, maximum, minimum

[0065] As can be seen from the above description, the embodiment of the present invention provides a single-indicator parameter collection method based on application performance monitoring. First, the performance monitoring single-indicator parameter is collected in a vertical collection manner; then, the performance monitoring single-indicator parameter is sent to the middleware; and finally, the performance monitoring single-indicator parameter forwarded by the middleware is aggregated and calculated. Specifically, the present invention has the following beneficial effects:

[0066] 1. Higher monitoring efficiency. When the collection end collects a certain indicator, it reports it immediately without waiting for other indicators, realizing true real-time monitoring and improving monitoring efficiency.

[0067] 2. Flexible configuration: The collection frequency of different indicators on the collection end can be flexibly configured.

[0068] 3. Resource saving: The analysis of monitoring data is completely placed on the server side, and the application only has data collection logic, which minimizes the use of application resources.

[0069] In one embodiment, the middleware is Kafka middleware. Figure 2 , step 200 includes:

[0070] Step 201: Send the performance monitoring single indicator parameter to the topic table of the Kafka middleware.

[0071] Kafka message middleware is a high-throughput distributed publish-subscribe messaging system and a distributed, partitioned, and reliable distributed log storage service. Its advantages include building real-time streaming data pipelines, reliably acquiring data between systems and applications, and building real-time streaming applications to transform or react to data streams.

[0072] In one embodiment, see Figure 3 , step 300 includes:

[0073] Step 301: Subscribe to the performance monitoring single indicator parameter from the topic table;

[0074] Step 302: Store the performance monitoring single indicator parameter in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator;

[0075] Step 303: Utilize the Druid database to perform aggregate calculation on the performance monitoring single indicator parameter.

[0076] In steps 301 to 303, the server first receives these independently reported data through the message middleware and, based on information such as the metric type, stores the metric in the corresponding database table for aggregation calculation. The Druid database is used here. Druid is a high-performance real-time analytics database and can perform aggregation calculations (such as sum, average, and maximum) by directly configuring the table structure.

[0077] In one embodiment, see Figure 4 , step 303 further includes:

[0078] Step 3031: Utilize the Druid database to aggregate and calculate the performance monitoring single indicator parameters according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID, and collection time.

[0079] It is understood that in the embodiments of the present invention, the message middleware does not need to be Kafka. This is just an example, and other message middleware products can also be used. The aggregation database does not need to be Druid, and can also use FluxDB or ClickHouse.

[0080] In a specific embodiment, the present invention also takes jvm (Java virtual machine) monitoring as an example to provide a specific embodiment of a single indicator parameter collection method based on application performance monitoring, see Figure 5 as well as Figure 6 .

[0081] Terminology Introduction:

[0082] Application performance monitoring: By collecting, reporting, and analyzing application performance monitoring data, we can achieve the goal of real-time understanding of system health.

[0083] Step S1: Collect performance monitoring single indicator parameters in a vertical collection mode;

[0084] Technically, solving the above problem requires changing the original horizontal reporting to vertical reporting by using a single indicator report and utilizing the Druid database for server-side aggregate calculations. For example, in the case of JVM (Java Virtual Machine) monitoring, the traditional method requires a timed thread to collect JVM memory and garbage collection (GC) information at regular intervals and report it uniformly. In this model, the data model of the reporting interface is a collection of various collected indicators, such as the content usage of different generations of heap memory (young generation, old generation, permanent generation), and the GC time and number of GCs for different generations. To put it in a more vivid way, these indicators are laid out horizontally in the interface, and each indicator is equal.

[0085] In this specific embodiment, collected single-metric parameters for application performance monitoring are reported vertically. This means each metric is reported independently and immediately upon collection, rather than being reported all at once in a single interface. Consequently, the data model for each metric is consistent, including metric name, metric type, metric collection frequency, metric category, metric application, metric link ID, and collection time.

[0086] Step S2: Send the performance monitoring single indicator parameter to the middleware;

[0087] The server first receives this independently reported data through the message middleware and, based on information such as the metric type, stores it in the corresponding database table for aggregation calculations. This is done using the Druid database, a high-performance real-time analytics database. Aggregate calculations (such as sum, average, and maximum) can be performed directly by configuring the table structure.

[0088] Step S3: performing aggregate calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0089] For example, in the example above, the server confirms receipt of a heap memory young generation memory size metric based on the metric type (server operations personnel need to maintain a correspondence between the metric and the database representation). It then stores the metric in the JVM memory information minute table based on the timestamp. This table is configured with an averaging operator for the memory size column and is a minute table (automatically aggregated once a minute). At the end of the minute, the average memory size of the young generation for that minute can be directly queried from Druid. This not only maintains the original aggregation and analysis capabilities, but also allows each metric to be independently collected, reported, and analyzed without relying on other metrics, providing great flexibility.

[0090] As can be seen from the above description, the embodiment of the present invention provides a single-indicator parameter collection method based on application performance monitoring. First, the performance monitoring single-indicator parameter is collected in a vertical collection manner; then, the performance monitoring single-indicator parameter is sent to the middleware; and finally, the performance monitoring single-indicator parameter forwarded by the middleware is aggregated and calculated. Specifically, the present invention has the following beneficial effects:

[0091] 1. Higher monitoring efficiency. When the collection end collects a certain indicator, it reports it immediately without waiting for other indicators, realizing true real-time monitoring and improving monitoring efficiency.

[0092] 2. Flexible configuration: The collection frequency of different indicators on the collection end can be flexibly configured.

[0093] 3. Resource saving: The analysis of monitoring data is completely placed on the server side, and the application only has data collection logic, which minimizes the use of application resources.

[0094] Based on the same inventive concept, the embodiments of the present application also provide a single-indicator parameter collection device based on application performance monitoring, which can be used to implement the method described in the above embodiments, such as the following embodiments. Since the principle of solving the problem by the single-indicator parameter collection device based on application performance monitoring is similar to that of the single-indicator parameter collection method based on application performance monitoring, the implementation of the single-indicator parameter collection device based on application performance monitoring can refer to the implementation of the single-indicator parameter collection method based on application performance monitoring, and the repeated parts will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements the predetermined function. Although the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceived.

[0095] The embodiment of the present invention provides a specific implementation of a single indicator parameter collection device based on application performance monitoring that can implement a single indicator parameter collection method based on application performance monitoring, see Figure 7 The single indicator parameter collection device based on application performance monitoring specifically includes the following contents:

[0096] The single indicator parameter collection module 10 is used to collect the performance monitoring single indicator parameter in a vertical collection manner;

[0097] The single indicator parameter sending module 20 is used to send the performance monitoring single indicator parameter to the middleware;

[0098] The single indicator parameter aggregation calculation module 30 is used to perform aggregation calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0099] In one embodiment, see Figure 8 , the single indicator parameter sending module 20 includes:

[0100] The single indicator parameter sending unit 201 is used to send the performance monitoring single indicator parameter to the topic table of the Kafka middleware.

[0101] In one embodiment, see Figure 9 , the single indicator parameter aggregation calculation module 30 includes:

[0102] A single indicator parameter subscription unit 301 is used to subscribe to the performance monitoring single indicator parameter from the topic table;

[0103] The single indicator parameter storage unit 302 is used to store the performance monitoring single indicator parameter in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator;

[0104] The single indicator parameter aggregation calculation unit 303 is used to perform aggregation calculation on the performance monitoring single indicator parameter using the Druid database.

[0105] In one embodiment, see Figure 10 , the single index parameter aggregation calculation unit 303 includes:

[0106] The single indicator parameter aggregation calculation subunit 3031 is used to use the Druid database to perform aggregation calculation on the performance monitoring single indicator parameter according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time.

[0107] As can be seen from the above description, the embodiment of the present invention provides a single-indicator parameter collection device based on application performance monitoring. First, the performance monitoring single-indicator parameter is collected in a vertical collection manner; then, the performance monitoring single-indicator parameter is sent to the middleware; and finally, the performance monitoring single-indicator parameter forwarded by the middleware is aggregated and calculated. Specifically, the present invention has the following beneficial effects:

[0108] 1. Higher monitoring efficiency. When the collection end collects a certain indicator, it reports it immediately without waiting for other indicators, realizing true real-time monitoring and improving monitoring efficiency.

[0109] 2. Flexible configuration: The collection frequency of different indicators on the collection end can be flexibly configured.

[0110] 3. Resource saving: The analysis of monitoring data is completely placed on the server side, and the application only has data collection logic, which minimizes the use of application resources.

[0111] The embodiment of the present application also provides a specific implementation of an electronic device that can implement all steps in the single indicator parameter collection method based on application performance monitoring in the above embodiment, see Figure 11 , electronic equipment specifically includes the following:

[0112] Processor 1201, memory 1202, communications interface 1203, and bus 1204;

[0113] The processor 1201, the memory 1202, and the communication interface 1203 communicate with each other via the bus 1204; the communication interface 1203 is used to implement information transmission between the server device and the client device and other related devices;

[0114] The processor 1201 is configured to call a computer program in the memory 1202. When the processor executes the computer program, all steps of the single indicator parameter collection method based on application performance monitoring in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0115] Step 100: Collect performance monitoring single indicator parameters in a vertical collection mode;

[0116] Step 200: Send the performance monitoring single indicator parameter to the middleware;

[0117] Step 300: performing aggregate calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0118] Embodiments of the present application also provide a computer-readable storage medium capable of implementing all steps of the single-indicator parameter collection method based on application performance monitoring in the above-mentioned embodiment. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the computer program implements all steps of the single-indicator parameter collection method based on application performance monitoring in the above-mentioned embodiment. For example, when the processor executes the computer program, the following steps are implemented:

[0119] Step 100: Collect performance monitoring single indicator parameters in a vertical collection mode;

[0120] Step 200: Send the performance monitoring single indicator parameter to the middleware;

[0121] Step 300: performing aggregate calculation on the performance monitoring single indicator parameters forwarded by the middleware.

[0122] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the hardware + program embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0123] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0124] Although the present application provides method operation steps such as embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative work. The order of steps listed in the embodiments is only one way of executing the steps among many steps and does not represent the only execution order. When an actual device or client product is executed, it can be executed in the order shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0125] For the convenience of description, the above devices are described in terms of functions divided into various modules. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules that implement the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, it is entirely possible to implement the same functionality by logically programming the method steps in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0127] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0128] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0129] Embodiments of this specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. Embodiments of this specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communications network. In distributed computing environments, program modules may be located in local and remote computer storage media, including storage devices.

[0130] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between the various embodiments can be referenced across them. Each embodiment focuses on the differences from the other embodiments. In particular, since the system embodiments are generally similar to the method embodiments, their description is relatively simple. For relevant parts, reference can be made to the description of the method embodiments. Throughout this specification, reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the embodiments in this specification. In this specification, the schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and integrate the different embodiments or examples, and features of different embodiments or examples, described in this specification, without conflict.

[0131] The above description is merely an example of the embodiments of this specification and is not intended to limit the embodiments of this specification. For those skilled in the art, various modifications and variations of the embodiments of this specification are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of this specification shall be included within the scope of the claims of the embodiments of this specification.

Claims

1. A single indicator parameter collection method based on application performance monitoring, characterized in that: include: Collect performance monitoring single indicator parameters in a vertical collection mode, wherein the performance monitoring single indicator parameters include: indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID, and collection time; Sending the performance monitoring single indicator parameter to the middleware; Performing aggregate calculation on the performance monitoring single indicator parameters forwarded by the middleware; The vertical collection method for collecting performance monitoring single indicator parameters includes: Each indicator is reported independently and immediately after collection, rather than being reported all at once in a certain interface. The middleware is a Kafka middleware, and sending the performance monitoring single indicator parameter to the middleware includes: Send the performance monitoring single indicator parameter to the topic table of the Kafka middleware; The aggregate calculation of the performance monitoring single indicator parameter forwarded by the middleware includes: Subscribe to the performance monitoring single indicator parameter from the topic table; Store the performance monitoring single indicator parameters in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator; The Druid database is used to perform aggregate calculations on the performance monitoring single indicator parameters. Specifically, the server first receives these independently reported data through the message middleware, and stores the indicators in the corresponding database table for aggregate calculations based on the indicator type information.

2. The single indicator parameter collection method based on application performance monitoring according to claim 1, characterized in that: The utilizing the Druid database to perform aggregate calculation on the performance monitoring single indicator parameter includes: The Druid database is used to aggregate and calculate the performance monitoring single indicator parameters according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time.

3. A single indicator parameter collection device based on application performance monitoring, characterized in that: include: A single indicator parameter collection module is used to collect performance monitoring single indicator parameters in a vertical collection manner, wherein the performance monitoring single indicator parameters include: indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time; A single indicator parameter sending module is used to send the performance monitoring single indicator parameter to the middleware; A single indicator parameter aggregation calculation module is used to perform aggregation calculation on the performance monitoring single indicator parameters forwarded by the middleware; The single indicator parameter collection module is specifically used to report each indicator independently, and report it immediately after collection, instead of flattening it in a certain interface and reporting it all at once; The single indicator parameter sending module includes: A single indicator parameter sending unit is used to send the performance monitoring single indicator parameter to the topic table of the Kafka middleware; The single indicator parameter aggregation calculation module includes: A single indicator parameter subscription unit, configured to subscribe to the performance monitoring single indicator parameter from the topic table; A single indicator parameter storage unit is used to store the performance monitoring single indicator parameter in the corresponding Druid database according to the indicator type and timestamp of the performance monitoring single indicator; The single indicator parameter aggregation calculation unit is used to perform aggregation calculation on the performance monitoring single indicator parameter using the Druid database, specifically: The server first receives these independently reported data through the message middleware, and stores the indicators in the corresponding database table for aggregation calculation based on the indicator type information.

4. The single indicator parameter collection device based on application performance monitoring according to claim 3, characterized in that: The single indicator parameter aggregation calculation unit includes: The single indicator parameter aggregation calculation subunit is used to use the Druid database to perform aggregation calculation on the performance monitoring single indicator parameter according to the indicator name, indicator type, indicator collection frequency, indicator category, indicator application, indicator link ID and collection time.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the single indicator parameter collection method based on application performance monitoring according to any one of claims 1 to 2 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the single indicator parameter collection method based on application performance monitoring described in any one of claims 1 to 2 are implemented.

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