Monitoring method based on cat platform and related device

Abstract

Embodiments of the present application provide a monitoring method based on a CAT platform and related equipment. The monitoring method based on the CAT platform comprises: obtaining routing parameters, traffic parameters and service parameters; predicting whether the integrated migration process can continue to operate normally based on the routing parameters, the traffic parameters and the service parameters; if it is predicted that the integrated migration process cannot operate normally, generating a format vector, a traffic vector, a trend vector and a policy vector based on the routing parameters, the traffic parameters and the service parameters; determining an adjustment parameter according to the format vector, the traffic vector, the trend vector and the policy vector; and updating the life research and development system based on the adjustment parameter to make the integrated migration process resume normal operation. Embodiments of the present application can at least monitor and warn various aspects in the data migration process to a certain extent.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer and communication, in particular, to a monitoring method based on CAT platform and related equipment. BACKGROUND

[0002] Currently, in the field of Internet, many systems need continuous update and iteration, and thus there is a problem of migration of new and old functions or new and old interfaces. In the migration process, there are many differences between the new and old interfaces, so it is necessary to monitor and warn each aspect in the data migration process. However, the current monitoring platform cannot realize unified monitoring of each aspect in the data migration process, and each aspect needs to be monitored separately through different monitoring platforms. SUMMARY

[0003] Embodiments of the present application provide a monitoring method based on a CAT platform and related equipment, thereby at least to some extent, the unified monitoring and warning of each aspect in the data migration process can be realized.

[0004] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0005] According to an aspect of an embodiment of the present application, a monitoring method based on a CAT platform is provided, which is applied to an integrated migration process between a first interface and a second interface of a life research and development system, and the method comprises:

[0006] obtaining routing parameters, traffic parameters and service parameters;

[0007] based on the routing parameters, the traffic parameters and the service parameters, predicting whether the integrated migration process can continue to operate normally;

[0008] if it is predicted that the integrated migration process cannot operate normally, generating a format vector, a traffic vector, a trend vector and a strategy vector based on the routing parameters, the traffic parameters and the service parameters;

[0009] determining an adjustment parameter according to the format vector, the traffic vector, the trend vector and the strategy vector;

[0010] updating the life research and development system based on the adjustment parameter, so as to restore the integrated migration process to normal operation.

[0011] In an embodiment of the present application, the prediction of whether the integrated migration process can continue to operate normally based on the routing parameters, the traffic parameters and the service parameters specifically comprises:

[0012] comparing the routing parameter and the traffic parameter to determine whether the traffic of any one of the first interface and the second interface will suddenly change in the next time period;

[0013] comparing the routing parameter and the traffic parameter to determine whether the format of the data flow matches the format of the second interface in the next time period;

[0014] if the traffic of any one of the first interface and the second interface will suddenly change in the next time period or the format of the data flow does not match the format of the second interface in the next time period, it is determined that the integrated migration process cannot normally run in the next time period.

[0015] In an embodiment of the present application, the prediction of whether the integrated migration process can normally run in the next time period based on the routing parameter, the traffic parameter and the service parameter specifically comprises:

[0016] inputting the routing parameter, the traffic parameter and the service parameter into a monitoring model, and the monitoring model outputs the result of the prediction of whether the integrated migration process can normally run in the next time period.

[0017] In an embodiment of the present application, the training method of the monitoring model specifically comprises:

[0018] obtaining a parameter sample set, wherein each parameter sample is previously labeled with a corresponding result of whether it can normally run;

[0019] inputting the data of each parameter sample into a monitoring model respectively to obtain the result of whether it can normally run output by the monitoring model;

[0020] if the result of whether it can normally run obtained after the data of the parameter sample is input into the monitoring model is inconsistent with the result of whether it can normally run previously labeled for the parameter sample, the coefficients of the monitoring model are adjusted until they are consistent;

[0021] when the data of all the parameter samples is input into the monitoring model, the result of whether it can normally run obtained is consistent with the result of whether it can normally run previously labeled for the parameter sample, and the training is completed.

[0022] In an embodiment of the present application, the specific steps of determining the adjustment parameter according to the format vector, the traffic vector, the trend vector and the policy vector comprise:

[0023] If the traffic of any one of the first interface and the second interface will suddenly change in the next time period, the adjustment parameter is determined according to the traffic vector, the trend vector and the policy vector, the adjustment parameter including adjustment of at least one parameter in the routing mode, the gray traffic mode and the gray policy.

[0024] If it is determined that the format of the data flow does not match the format of the second interface in the next time period, the adjustment parameter is determined according to the format vector, the traffic vector and the policy vector, the adjustment parameter including adjustment of at least one parameter in the gray traffic mode and the gray policy.

[0025] In an embodiment of the present application, the specific step of determining the adjustment parameter according to the format vector, the traffic vector, the trend vector and the policy vector includes:

[0026] The format vector, the traffic vector, the trend vector and the policy vector are input into a diagnosis model, and the diagnosis model outputs the adjustment parameter.

[0027] In an embodiment of the present application, the training method of the monitoring model specifically includes:

[0028] A set of vector samples is obtained, each vector sample being previously labeled with a corresponding adjustment parameter;

[0029] The data of each vector sample is input into a diagnosis model respectively, and the adjustment parameter output by the diagnosis model is obtained;

[0030] If the adjustment parameter obtained after the data of the vector sample is input into the diagnosis model is inconsistent with the adjustment parameter previously labeled for the vector sample, the coefficients of the diagnosis model are adjusted until consistency is achieved.

[0031] When the data of all the vector samples is input into the diagnosis model, the adjustment parameter obtained is consistent with the adjustment parameter previously labeled for the vector sample, and the training is completed.

[0032] According to an aspect of an embodiment of the present application, a monitoring device based on a CAT platform is provided, which includes:

[0033] A running parameter acquisition module is configured to acquire routing parameters, traffic parameters and service parameters, the routing parameters including a routing mode, a gray traffic mode and a gray policy.

[0034] A running status prediction module is configured to predict whether the integrated migration process can continue to operate normally based on the routing parameters, the traffic parameters and the service parameters.

[0035] a parameter vector generation module configured to generate a format vector, a traffic vector, a trend vector and a policy vector based on the routing parameter, the traffic parameter and the service parameter if it is predicted that the integrated migration process cannot run normally;

[0036] an adjustment parameter determination module configured to determine an adjustment parameter according to the format vector, the traffic vector, the trend vector and the policy vector;

[0037] a system update module configured to update the living research and development system based on the adjustment parameter so as to make the integrated migration process run normally.

[0038] According to an aspect of an embodiment of the present application, a computer readable medium having a computer program stored thereon is provided, the computer program being executed by a processor to implement the CAT platform-based monitoring method as described in the above embodiments.

[0039] According to an aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the CAT platform-based monitoring method as described in the above embodiments.

[0040] In the technical solutions provided by some embodiments of the present application, the routing parameter, the traffic parameter and the service parameter are acquired through the CAT platform, and the running state is analyzed based on the above parameters, if it is predicted that the migration process cannot run normally, the above parameters are vectorized, and the parameters that need to be adjusted are determined according to the parameter vector, the unified monitoring, early warning and adjustment of each aspect in the data migration process are realized, meanwhile, based on the routing parameter, the traffic parameter and the service parameter, it is predicted whether the integrated migration process can continue to run normally, the running state can be predicted in advance, and adjustment can be made in advance, most of the abnormal running states in the migration process can be prevented.

[0041] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0042] The drawings herein are incorporated into the specification and form a part of the specification, show embodiments consistent with the present application, and together with the specification serve to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. In the drawings:

[0043] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solutions of the embodiments of the present application can be applied is shown;

[0044] Figure 2 A flow chart schematically showing a monitoring method based on a CAT platform according to an embodiment of the present application is shown.

[0045] Figure 3 is shown according to Figure 2 A flow chart showing a specific implementation of step S200 in the monitoring method based on a CAT platform according to the corresponding embodiment is shown.

[0046] Figure 4 is shown according to Figure 2 A flow chart showing a specific implementation of step S400 in the monitoring method based on a CAT platform according to the corresponding embodiment is shown.

[0047] Figure 5 A block diagram schematically showing a monitoring device based on a CAT platform according to an embodiment of the present application is shown.

[0048] Figure 6 The structure of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown. DETAILED DESCRIPTION

[0049] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0050] Moreover, described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the

[0051] The block diagrams shown in the accompanying drawings are merely functional entities, and do not necessarily have to correspond to physically independent entities. That is, these functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0052] The flowchart shown in the drawing is only an example and does not necessarily include all the contents and operations / steps, nor does it have to be executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to the actual situation.

[0053] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of the present application can be applied is shown.

[0054] As shown in Figure 1 , the system architecture can include one or more of terminal devices (such as a smartphone 101, a tablet computer 102, and a portable computer 103 as shown in Figure 1 , of course, a desktop computer, etc.), a network 104, and a server 105. The network 104 is a medium for providing a communication link between the terminal device and the server 105. The network 104 can include various connection types, such as wired communication links, wireless communication links, etc.

[0055] It should be understood that Figure 1 the number of terminal devices, networks, and servers in is only illustrative. Depending on the implementation needs, there can be any number of terminal devices, networks, and servers. For example, the server 105 can be a server cluster composed of multiple servers, etc.

[0056] A user can use a terminal device to interact with the server 105 through the network 104 to receive or send messages, etc. The server 105 can be a server that provides various services. For example, a user uploads routing parameters, traffic parameters, and service parameters to the server 105 using the terminal device 103 (which can also be the terminal device 101 or 102), and the server 105 can obtain the routing parameters, traffic parameters, and service parameters; based on the routing parameters, the traffic parameters, and the service parameters, predict whether the integrated migration process can continue to operate normally; if it is predicted that the integrated migration process cannot operate normally, generate a format vector, a traffic vector, a trend vector, and a policy vector based on the routing parameters, the traffic parameters, and the service parameters; determine an adjustment parameter according to the format vector, the traffic vector, the trend vector, and the policy vector; update the life research and development system based on the adjustment parameter to restore the integrated migration process to normal operation.

[0057] It should be noted that the CAT platform-based monitoring method provided by the embodiments of the present application is generally executed by the server 105, and correspondingly, the CAT platform-based monitoring device is generally provided in the server 105. However, in other embodiments of the present application, the terminal device can also have similar functions as the server, so as to execute the CAT platform-based monitoring scheme provided by the embodiments of the present application.

[0058] The implementation details of the technical solutions of the embodiments of the present application are described in detail as follows:

[0059] Figure 2 A flowchart of a CAT platform-based monitoring method according to an embodiment of the present application is shown, which can be executed by a server, which can be the server shown in Figure 1 Referring to Figure 2 The CAT platform-based monitoring method at least includes:

[0060] Step S100, acquiring routing parameters, traffic parameters and service parameters;

[0061] Step S200, predicting whether the integrated migration process can continue to operate normally based on the routing parameters, the traffic parameters and the service parameters;

[0062] Step S300, if it is predicted that the integrated migration process cannot operate normally, generating a format vector, a traffic vector, a trend vector and a strategy vector based on the routing parameters, the traffic parameters and the service parameters;

[0063] Step S400, determining an adjustment parameter according to the format vector, the traffic vector, the trend vector and the strategy vector;

[0064] Step S500, updating the living research and development system based on the adjustment parameter, so as to make the integrated migration process resume normal operation.

[0065] In the embodiments of the present application, the running parameters such as routing parameters, traffic parameters and service parameters are acquired first, and then analysis and prediction are performed based on the above running parameters to determine the running state of the integrated migration. If it is predicted that the running state is not normal, the above running parameters are processed by vectorization to obtain a format vector, a traffic vector, a trend vector and a strategy vector, and data analysis is performed according to the above vectors to determine an adjustment parameter. Finally, the living research and development system is updated based on the adjustment parameter, so as to make the integrated migration process resume normal operation.

[0066] The embodiments of the present application obtain routing parameters, traffic parameters and service parameters through the CAT platform, and analyze the running state based on the above parameters. If it is predicted that the migration process cannot run normally, the above parameters are vectorized, and the parameters that need to be adjusted are determined according to the parameter vector, thereby realizing unified monitoring, early warning and adjustment of each aspect in the data migration process. Meanwhile, based on the routing parameters, the traffic parameters and the service parameters, it is predicted whether the integrated migration process can continue to run normally, the running state can be predicted in advance, and adjustment can be made in advance, which can prevent most abnormal running states in the migration process.

[0067] In step S100, the routing parameters include routing mode, gray traffic mode and gray strategy. Specifically, the routing mode refers to the traffic routing strategy executed in the integrated migration process, which includes parallel strategy, gray strategy, white list strategy, full cut strategy and no cut strategy. The gray traffic mode refers to the way of traffic distribution in the integrated migration process, including distribution according to the white list and distribution according to the predetermined rule. The gray strategy refers to the specific strategy of traffic distribution in the integrated migration process. When the gray traffic mode is distribution according to the white list, the gray strategy is the specific white list; when the gray traffic mode is distribution according to the predetermined rule, the gray strategy is the specific distribution rule, such as proportional distribution, preferential distribution of a certain interface or staggered distribution, etc.

[0068] The traffic parameters include data stream traffic, first interface traffic and second interface traffic.

[0069] The service parameters include running environment, format of data stream, format of first interface and format of second interface. The running environment includes running scene, protocol, system, etc. The format in the format of data stream, the format of first interface and the format of second interface can include message, address and other format information.

[0070] In step S200, the running state of the integrated migration process is predicted based on the running parameters obtained in step S100, most running abnormalities can be prevented in advance, early warning and adjustment can be realized before the abnormalities occur, most small abnormalities in the running process can be avoided, and the efficiency of integrated migration is improved.

[0071] The implementation of step S200 can have various forms.

[0072] Specifically, in some embodiments, the specific implementation of step S200 can refer to Figure 3 . Figure 3 is based on Figure 2 The detailed description of step S200 in the monitoring method based on the CAT platform according to the corresponding embodiments is shown, in which step S200 can include the following steps:

[0073] Step S210, comparing the routing parameter and the traffic parameter, determining whether the traffic of any one of the first interface and the second interface will suddenly change in the next time period;

[0074] Step S220, comparing the routing parameter and the traffic parameter, determining whether the format of the data flow matches the format of the second interface in the next time period;

[0075] Step S230, if the traffic of any one of the first interface and the second interface will suddenly change in the next time period or the format of the data flow does not match the format of the second interface in the next time period, determining that the integrated migration process in the next time period cannot run normally.

[0076] In the embodiment, by comparing and analyzing the traffic parameter, the routing parameter and the traffic parameter, the running parameters of the running state of the integrated migration process are obtained, and the running state of the integrated migration process is predicted based on the running parameters, so that most of the running abnormalities can be prevented in advance, early warning and adjustment are realized before the abnormalities occur, most of the small abnormal situations in the running process can be avoided, and the efficiency of the integrated migration is improved.

[0077] In the embodiment, step S210 and step S220 can be executed synchronously or asynchronously, which is specifically allocated according to the traffic environment at that time.

[0078] In step S210, the change trend of the data flow traffic, the first interface traffic and the second interface traffic is determined by comparing the routing parameter and the traffic parameter, and according to the change trend, it is determined whether the traffic of any one of the first interface and the second interface will suddenly change, for example, suddenly increase or decrease greatly, in the next time period under the setting allocation of the current routing parameter. If the traffic of any one of the first interface and the second interface suddenly increases or decreases greatly, it proves that the running state will be abnormal soon, and the routing parameter needs to be adjusted to realize the dynamic balance of the traffic. At this time, it can be determined in step S230 that the integrated migration process in the next time period cannot run normally, and the routing parameter is adjusted.

[0079] In step S220, by comparing the routing parameters and the traffic parameters, the change of the data stream of various formats and the switching of the protocol message and the environment format of the first interface and the second interface are determined, it is judged whether the format of the data stream matches the format of the second interface in the next time period, if the format of the data stream changes to be not matched with the format of the second interface or the format of the second interface changes to be not matched with the format of the data stream, it can be predicted in advance to adjust the gateway or interface parameters. When it is predicted that the format of the data stream changes to be not matched with the format of the second interface or the format of the second interface changes to be not matched with the format of the data stream, it can be judged that the format of the data stream does not match the format of the second interface in the next time period. At this time, in step S230, it can be determined that the integrated migration process cannot normally run in the next time period, and the routing parameters or the interface parameters are adjusted.

[0080] Specifically, in other embodiments, the specific implementation of step S200 can also rely on a machine learning model. The present embodiment is based on Figure 2 The details of another embodiment of step S200 in the monitoring method based on the CAT platform shown in the corresponding embodiment are described, wherein step S200 can include the following steps:

[0081] The routing parameters, the traffic parameters and the service parameters are input into a monitoring model, and the monitoring model outputs a result of whether the integrated migration process can normally run in the next time period.

[0082] The present embodiment can more accurately predict the running state by comprehensively predicting the running state through the monitoring model, and can more accurately predict the running state by more accurately finding the correlation between the routing parameters, the traffic parameters and the service parameters.

[0083] The training method of the monitoring model includes:

[0084] A parameter sample set is obtained, wherein each parameter sample is previously labeled with a corresponding result of whether it can normally run;

[0085] The data of each parameter sample is input into the monitoring model respectively, and a result of whether it can normally run output by the monitoring model is obtained;

[0086] If the result of whether it can normally run obtained after the data of the parameter sample is input into the monitoring model is inconsistent with the result of whether it can normally run previously labeled for the parameter sample, the coefficients of the monitoring model are adjusted until they are consistent;

[0087] When the data of all the parameter samples is input into the monitoring model, the result of whether it can normally run obtained is consistent with the result of whether it can normally run previously labeled for the parameter samples, and the training is completed.

[0088] In step S300, the routing parameters, traffic parameters, and service parameters are vectorized. The resulting vectors help analyze the reasons for malfunctions. The format vector includes multiple dimensions, representing the format of the current data stream, the format of the first interface, and the format of the second interface. The traffic vector includes multiple dimensions, representing the data stream traffic, the traffic of the first interface, and the traffic of the second interface. The trend vector includes multiple dimensions, representing the trends in data stream traffic changes, the trends in traffic changes of the first interface, and the trends in traffic changes of the second interface. The policy vector includes multiple dimensions, representing the routing method, the gray-scale traffic method, and the gray-scale policy.

[0089] In step S400, based on the comparative analysis of the above parameter vectors, the direction of adjustment can be obtained so as to eliminate the anomaly before it occurs.

[0090] There are many ways to implement step S400.

[0091] Specifically, in some embodiments, the specific implementation of step S400 can be found in [reference needed]. Figure 4 . Figure 4 It is based on Figure 2 The detailed description of step S400 in the CAT platform-based monitoring method shown in the corresponding embodiment includes the following steps:

[0092] Step S410: If the traffic of either the first interface or the second interface will suddenly change in the next time period, then determine the adjustment parameters according to the traffic vector, the trend vector and the policy vector. The adjustment parameters include adjustments to at least one parameter of the routing method, the gray-scale traffic method and the gray-scale policy.

[0093] Step S420: If it is determined that the format of the data stream does not match the format of the second interface in the next time period, then the adjustment parameter is determined according to the format vector, the traffic vector and the strategy vector. The adjustment parameter includes the adjustment of at least one parameter of the grayscale traffic method and the grayscale strategy.

[0094] In step S410, if the traffic of either the first interface or the second interface suddenly increases or decreases significantly, it indicates that the operating status is about to become abnormal. At this time, it is necessary to determine which of the following items in the routing method, gray-scale traffic method, and gray-scale strategy need to be switched based on the data flow traffic, the traffic of the first interface, the traffic of the second interface, the trend of data flow traffic, the trend of the trend of the trend of the trend of the first interface traffic, and the trend of the trend of the second interface traffic, and to determine the specific parameters after the switch.

[0095] In step S420, if the format of the data stream changes to be incompatible with the format of the second interface or the format of the second interface changes to be incompatible with the format of the data stream, it is necessary to determine whether the model, protocol, scenario and environment of the interface need to be switched, whether the gateway parameters need to be changed, and whether the traffic distribution needs to be guided according to the format vector, the traffic vector and the policy vector.

[0096] Specifically, in other embodiments, the specific implementation of step S400 can also rely on a machine learning model. The embodiment is based on Figure 2 The details of another embodiment of step S400 in the monitoring method based on the CAT platform are shown in the corresponding embodiment, and the monitoring method based on the CAT platform can include the following steps:

[0097] The format vector, the traffic vector, the trend vector and the policy vector are input into a diagnostic model, and the diagnostic model outputs an adjustment parameter.

[0098] The embodiment can obtain more accurate adjustment items and corresponding adjustment parameters through comprehensive evaluation of the running state by the monitoring model, so that the integrated migration process runs more smoothly.

[0099] The training method of the monitoring model specifically includes:

[0100] A set of vector samples is obtained, and each vector sample is previously labeled with a corresponding adjustment parameter;

[0101] The data of each vector sample is input into a diagnostic model respectively to obtain an adjustment parameter output by the diagnostic model;

[0102] If the adjustment parameter obtained after the data of the vector sample is input into the diagnostic model is inconsistent with the adjustment parameter previously labeled for the vector sample, the coefficients of the diagnostic model are adjusted until they are consistent.

[0103] When the data of all the vector samples is input into the diagnostic model, the adjustment parameter obtained is consistent with the adjustment parameter previously labeled for the vector sample, and the training is completed.

[0104] The device embodiment of the present application is introduced below, which can be used to execute the monitoring method based on the CAT platform in the above-mentioned embodiments of the present application. For details not disclosed in the device embodiment of the present application, please refer to the above-mentioned embodiments of the monitoring method based on the CAT platform.

[0105] Figure 5 A block diagram of a monitoring device based on the CAT platform according to an embodiment of the present application is shown.

[0106] Reference is made to Figure 5As shown, the CAT platform-based monitoring device 500 according to an embodiment of the present application comprises:

[0107] The running parameter acquisition module 510 is configured to acquire routing parameters, traffic parameters and service parameters.

[0108] The running status prediction module 520 is configured to predict whether the integrated migration process can continue to run normally based on the routing parameters, the traffic parameters and the service parameters.

[0109] The parameter vector generation module 530 is configured to generate a format vector, a traffic vector, a trend vector and a strategy vector based on the routing parameters, the traffic parameters and the service parameters if it is predicted that the integrated migration process cannot run normally.

[0110] The adjustment parameter determination module 540 is configured to determine adjustment parameters according to the format vector, the traffic vector, the trend vector and the strategy vector.

[0111] The running system updating module 550 is configured to update the life science research and development system based on the adjustment parameters, so as to restore the integrated migration process to normal running.

[0112] Figure 6 A structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0113] It should be noted that, Figure 6 The computer system of the electronic device shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0114] As Figure 6 shown, the computer system comprises a central processing unit (CPU) 1801, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 1802 or programs loaded from a storage portion 1808 into a random access memory (RAM) 1803, such as performing the methods described in the above embodiments. In the RAM 1803, various programs and data required for system operation are also stored. The CPU 1801, the ROM 1802 and the RAM 1803 are connected to each other through a bus 1804. An input / output (I / O) interface 1805 is also connected to the bus 1804.

[0115] The following components are connected to the I / O interface 1805: an input part 1806 including a keyboard, a mouse, etc.; an output part 1807 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), etc., and a speaker, etc.; a storage part 1808 including a hard disk, etc.; and a communication part 1809 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication part 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to the I / O interface 1805 as necessary. A removable medium 1811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 1810 as necessary, so that a computer program read therefrom is installed in the storage part 1808 as necessary.

[0116] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication part 1809, and / or installed from the removable medium 1811. When the computer program is executed by the central processing unit (CPU) 1801, various functions defined in the system of the present application are executed.

[0117] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In this application, the computer-readable signal medium can include a data signal carrying computer-readable computer programs in a baseband or as a part of a carrier wave. Such a propagated data signal can take on various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium that can transmit, propagate or transport programs for use by or in connection with an instruction execution system, device or apparatus. The computer programs contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination thereof.

[0118] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In the flowcharts or block diagrams, each block can represent a module, a program segment or a part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders than that shown in the drawings. For example, two blocks that are shown in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0119] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can also be located in a single processor. In some cases, the names of the units do not limit the units themselves.

[0120] As another aspect, the present application also provides a computer readable medium, which can be included in the electronic device described in the above embodiments, or can exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the method described in the above embodiments.

[0121] It should be noted that although several modules or units for performing actions are mentioned in the above detailed description, the division into the modules or units is not mandatory. In fact, according to the embodiments of the present application, features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, features and functions of one module or unit described above can be further divided into a plurality of modules or units.

[0122] From the above description of the embodiments, those skilled in the art will readily appreciate that the example embodiments described herein can be implemented by software and / or by hardware coupled with software. Accordingly, the technical solutions of the embodiments of the present application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, or the like) or on a network, and includes a number of instructions for causing a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the methods according to the embodiments of the present application.

[0123] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such

[0124] It should be understood that the present application is not limited to the precise construction that has been described above and illustrated in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the present application. The scope of the present application is limited only by the appended claims.

Claims

1. A monitoring method based on the CAT platform, characterized in that, In the process of integrating the first and second interfaces of the life and survival research and development system, the method includes: Obtain routing parameters, traffic parameters, and business parameters; Based on the routing parameters, traffic parameters, and service parameters, it is predicted whether the integrated migration process can continue to operate normally. This prediction includes: comparing the routing parameters and traffic parameters to determine whether the traffic of either the first interface or the second interface will suddenly change in the next time period; comparing the routing parameters and service parameters to determine whether the data stream format matches the format of the second interface in the next time period; if the traffic of either the first interface or the second interface will suddenly change in the next time period, or if the data stream format does not match the format of the second interface in the next time period, then it is determined that the integrated migration process cannot operate normally in the next time period. If the integrated migration process is predicted to fail to operate normally, then a format vector, a traffic vector, a trend vector, and a policy vector are generated based on the routing parameters, the traffic parameters, and the service parameters. Based on the format vector, the traffic vector, the trend vector, and the policy vector, adjustment parameters are determined; wherein, determining the adjustment parameters includes: if the traffic of either the first interface or the second interface will suddenly change in the next time period, then the adjustment parameters are determined based on the traffic vector, the trend vector, and the policy vector, and the adjustment parameters include adjustments to at least one parameter among routing method, gray-scale traffic method, and gray-scale policy; if the format of the data stream does not match the format of the second interface in the next time period, then the adjustment parameters are determined based on the format vector, the traffic vector, and the policy vector, and the adjustment parameters include adjustments to at least one parameter among gray-scale traffic method and gray-scale policy; The life and development R&D system is updated based on the adjusted parameters to restore the integrated migration process to normal operation.

2. A monitoring device based on the CAT platform, characterized in that, The monitoring device based on the CAT platform includes: The runtime parameter acquisition module is used to acquire routing parameters, traffic parameters, and service parameters; The operation status prediction module is used to predict whether the integrated migration process between the first interface and the second interface of the life and development system can continue to operate normally based on the routing parameters, the traffic parameters and the service parameters. The parameter vector generation module is used to generate a format vector, a traffic vector, a trend vector, and a strategy vector based on the routing parameters, the traffic parameters, and the service parameters if the integrated migration process is predicted to fail to operate normally. The parameter adjustment determination module is used to determine the adjustment parameters based on the format vector, the flow vector, the trend vector, and the strategy vector. The system update module is used to update the life and development system based on the adjustment parameters, so that the integrated migration process can be restored to normal operation. The operational status prediction module is specifically used for: By comparing the routing parameters and the traffic parameters, it is determined whether the traffic of either the first interface or the second interface will suddenly change in the next time period; by comparing the routing parameters and the service parameters, it is determined whether the format of the data stream matches the format of the second interface in the next time period; if the traffic of either the first interface or the second interface will suddenly change in the next time period or the format of the data stream does not match the format of the second interface in the next time period, it is determined that the integrated migration process cannot operate normally in the next time period. The adjustment parameter determination module is specifically used for: If the traffic of either the first interface or the second interface changes suddenly in the next time period, the adjustment parameters are determined based on the traffic vector, the trend vector, and the policy vector. The adjustment parameters include adjustments to at least one parameter among the routing method, the gray-scale traffic method, and the gray-scale policy. If the format of the data stream does not match the format of the second interface in the next time period, the adjustment parameters are determined based on the format vector, the traffic vector, and the policy vector. The adjustment parameters include adjustments to at least one parameter among the gray-scale traffic method and the gray-scale policy.

3. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the monitoring method based on the CAT platform as described in claim 1.

4. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the monitoring method based on the CAT platform as described in claim 1.

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