CN114398233A - Load abnormity detection method, device, server and storage medium - Google Patents
Load abnormity detection method, device, server and storage medium Download PDFInfo
- Publication number
- CN114398233A CN114398233A CN202210038863.2A CN202210038863A CN114398233A CN 114398233 A CN114398233 A CN 114398233A CN 202210038863 A CN202210038863 A CN 202210038863A CN 114398233 A CN114398233 A CN 114398233A
- Authority
- CN
- China
- Prior art keywords
- service thread
- load
- thread
- kernel
- state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/301—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is a virtual computing platform, e.g. logically partitioned systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/45591—Monitoring or debugging support
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The embodiment of the disclosure discloses a load abnormity detection method, a device, a server and a storage medium, wherein the method comprises the following steps: acquiring a service thread set of a host machine; the service thread set comprises at least one service thread, and the service thread is used for simulating a virtual processor; traversing at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number ratio of kernel-state instructions in an instruction set of the service thread through Hypervisor; and if the number proportion of the current service thread is larger than the number proportion threshold value, determining that kernel-state load abnormity exists in the virtual processor simulated by the current service thread. According to the technical scheme of the embodiment of the invention, the kernel-state load abnormity of the virtual machine can be effectively detected without deploying information acquisition software in the virtual machine in advance, and the safety risk inside the virtual machine caused by the operation breakdown of a software program is avoided.
Description
Technical Field
The embodiment of the disclosure relates to a virtual machine technology, and in particular, to a load anomaly detection method, a load anomaly detection device, a server, and a storage medium.
Background
With the rise of cloud computing services, a large number of enterprise and personal services are deployed on a cloud server, and therefore monitoring of the operation state of the cloud server becomes particularly important, where the kernel-state load of the cloud server is an important component of the operation state of the cloud server.
In the prior art, for monitoring the kernel-state load of the cloud server, information acquisition software is usually deployed in advance inside a virtual machine of the cloud server, and the acquired kernel-state load is transmitted to a host machine through the information acquisition software.
However, such a monitoring manner is completely completed by information acquisition software which is pre-deployed in the virtual machine, and a user of the cloud server is often not allowed to deploy the information acquisition software due to consideration of factors such as security and the like, and even if the information acquisition software is deployed, the monitoring manner faces various risks such as software operation crash and security holes in operation.
Disclosure of Invention
The disclosure provides a load anomaly detection method, a load anomaly detection device, a server and a storage medium, so that kernel-state load anomaly detection in a virtual processor is realized by acquiring the number ratio of kernel-state instructions of the virtual processor and the load numerical value of a service thread.
In a first aspect, an embodiment of the present disclosure provides a load anomaly detection method, including:
acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
traversing the at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number proportion of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread.
In a second aspect, an embodiment of the present disclosure provides a load abnormality detection apparatus, including:
the service thread set acquisition module is used for acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
the number ratio acquisition module is used for traversing the at least one service thread, acquiring a load value of the service thread through system information of the service thread, and acquiring the number ratio of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
and the load exception acquisition module is used for determining that kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is greater than a load threshold and the number ratio is greater than a number ratio threshold.
In a third aspect, an embodiment of the present disclosure provides a server, including a memory, a processing device, and a computer program stored on the memory and executable on the processing device, where the processing device implements a load abnormality detection method according to any embodiment of the present disclosure when executing the program.
In a fourth aspect, embodiments of the present disclosure provide a storage medium containing computer-executable instructions for performing the load anomaly detection method of any of the embodiments of the present disclosure when executed by a computer processor.
According to the technical scheme of the embodiment, a service thread set used for simulating the virtual processor in the host is traversed, the kernel state load abnormity exists in the virtual processor simulated by the current service thread when the number proportion of kernel state instructions in the instruction set of the current service thread is acquired through the Hypervisor and is larger than the number proportion threshold value, and the load value of the current service thread is larger than the load threshold value, the effective detection of the kernel state load abnormity of the virtual machine can be realized without deploying information acquisition software in the virtual machine in advance, meanwhile, the influence of user safety precaution measures is avoided, and the safety risk in the virtual machine caused by the breakdown of a software program is avoided.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
FIG. 1 is a flow chart of one embodiment of a load anomaly detection method of the present disclosure;
FIG. 2 is a flow chart of one embodiment of a load anomaly detection method of the present disclosure;
fig. 3 is a block diagram of a load abnormality detection apparatus according to a third embodiment of the present disclosure;
fig. 4 is a block diagram of a server in a fourth embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Example one
Fig. 1 is a flowchart of a load anomaly detection method provided in an embodiment of the present disclosure, where this embodiment is applicable to detecting that a number ratio of kernel-state instructions of a virtual processor is greater than a number ratio threshold, and a load value of a service thread is greater than a load threshold, and determining that a kernel-state load anomaly exists in the virtual processor, where the method may be executed by a load anomaly detection apparatus in an embodiment of the present disclosure, and the apparatus may be implemented by software and/or hardware and integrated in a server, and typically may be integrated in a cloud server, where the method specifically includes the following steps:
s110, acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor.
A Virtual Machine (Virtual Machine) is a computer system which has complete hardware system functions and is simulated by software and runs in an isolated environment; the host machine is a host machine provided with the virtual machine, namely a host of the virtual machine; the virtual machines exist in a host machine in the form of processes (processes), namely, each business Process corresponds to one virtual machine; the virtual processor (VCPU) is a CPU in the virtual machine, the virtual processor exists in a host machine in a Thread (Thread) form, the service Thread is used for simulating the virtual processor, and the virtual processor is matched with the service Thread one by one; optionally, in this embodiment of the present disclosure, the number of virtual machines in the host (i.e., the number of business processes) and the number of virtual processors in each virtual machine (i.e., the number of business threads in each business process) are not specifically limited.
Optionally, in this embodiment of the present disclosure, the acquiring a service thread set of a host includes: and updating the service thread set of the host machine in real time according to the process information of the host machine. The user of the host changes, the number of the service processes in the host may change, and the service adjustment of the user may also cause the number of the virtual processors in each virtual machine to change, for example, a single virtual processor is changed into multiple virtual processors, that is, the number of the service threads in the corresponding service processes may also change simultaneously, so that the number of the service processes and the number of the service threads in each service process are obtained according to the process information in the host to update the service thread set of the host in real time, thereby ensuring the complete monitoring of all the virtual processors in the host.
S120, traversing the at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number proportion of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction.
Through the system information of the service thread, the load value of the service thread during operation can be obtained, the load value reflects the load degree of the service thread, and the higher the load value is, the higher the load degree of the service thread is. When the virtual processor executes an operating system call and falls into kernel code to execute, the virtual processor is in a kernel running state (namely a kernel state); when the virtual processor executes the service code of the user side in response to the user side movement, the virtual processor is in a user running state (namely, a user state). Hypervisor, a Virtual Machine Monitor (VMM), is an intermediate software layer running between a host and an operating system, and is used for constructing a Virtual Machine and executing the running of the Virtual Machine; acquiring the instruction type and the instruction number of each instruction in an instruction set read by a register (namely an instruction register) of the virtual processor within a certain detection time (for example, 2 seconds) through the Hypervisor; the instruction type comprises a kernel mode instruction and a user mode instruction; and further acquiring the quantity ratio of the kernel state instruction in the instruction set, wherein the quantity ratio reflects the number of times of the virtual machine executing the operating system of the host machine calling in the detection time and the ratio of the number of times of executing the user task calling, and the larger the value of the quantity ratio is, the longer the virtual machine executing the operating system calling of the host machine calling in the detection time is.
S130, if the load value of the current service thread is larger than a load threshold value and the number ratio is larger than a number ratio threshold value, determining that kernel-state load abnormity exists in the virtual processor simulated by the current service thread.
The load threshold may be predetermined as desired and is typically set to a large value, e.g., 90%; if the load value is larger, namely the load value is larger than the load threshold value, the load degree of the virtual processor is higher, and at the moment, the operating system of the host machine is possibly in a heavy load working state; the number-to-number ratio threshold may also be predetermined as desired, and is typically set to a larger value, e.g., 95%; if the number ratio is larger, that is, the number ratio is larger than the number ratio threshold, it indicates that most of the instructions acquired by the virtual machine are call instructions of the host operating system, no user-side service code is executed (i.e., when the number ratio is 100%) or only a small number of user-side service codes are executed (i.e., when the number ratio is larger than 95% and smaller than 100%), in fact, under the normal working state of the virtual machine, the working time under the user-mode instruction is usually much longer than that under the kernel-mode instruction, therefore, if the number of kernel-mode instructions is large, the virtual machine is mobilized by the operating system for a long time, which causes the kernel-mode load to be too high, at this time, the operating system of the host may be in an infinite loop or deadlock state, or unreasonable system calls exist in the user side service codes, so that the kernel mode load of the virtual processor is determined to have an exception.
Compared with the prior art, the method has the advantages that the information acquisition software is pre-deployed inside the virtual machine, and the kernel-state load of the virtual machine is obtained through the information acquisition software; in the embodiment of the disclosure, the Hypervisor is obviously located outside the virtual machine, and after the virtual machine is created by the Hypervisor, the instruction type in the register of the virtual machine is directly obtained by the Hypervisor, so as to obtain the quantity ratio of the kernel mode instructions, without deploying information acquisition software in advance inside the virtual machine, and being not affected by user safety precaution measures, there is no problem of running crash of the internal program of the virtual machine, and the virtual machine will not have security risk due to software bugs of the virtual machine itself.
Optionally, in this embodiment of the present disclosure, the obtaining, through the system information of the service thread, a load value of the service thread includes: acquiring the time occupation ratio of the service thread to process the virtual machine service in the detection time; if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread, including: if the number proportion of the current service thread is larger than a number proportion threshold value and the time proportion is larger than a time proportion threshold value, determining that kernel-state load abnormity exists in the virtual processor simulated by the current service thread.
Specifically, in the system information of the service thread, the service information executed by the service thread at the current moment is recorded; when the service thread is not called by the operating system and the user task, for example, when the service thread is in an idle state, the service thread itself is not used as the virtual processor, and therefore the virtual machine service is not processed; when the service thread is called by an operating system or a user task, the service thread is used as a virtual processor of the virtual machine and is used for processing the service of the virtual machine; within a certain detection time (for example, 2 seconds), acquiring a service thread as a virtual processor, processing the processing time (for example, 1.9 seconds) of the virtual machine service, and further acquiring the time proportion (namely, 95%); the larger the time ratio is, the more busy the service thread is, and the higher the load is; the time ratio threshold may be preset as needed, and is usually set to a large value, for example, 90%.
Optionally, in an embodiment of the present disclosure, the method further includes: if the load value of the current service thread is less than or equal to a load threshold value and/or the number proportion is less than or equal to a number proportion threshold value, determining that kernel-state load abnormity does not exist in the virtual processor simulated by the current service thread. When the number proportion of the service threads is greater than the number proportion threshold value and the time proportion is greater than the time proportion threshold value, the fact that the loads of the service threads are high and most of the loads are kernel-state loads is indicated, and therefore the abnormal kernel-state loads in the virtual machine simulated by the service threads can be determined, the phenomenon that the kernel-state loads are high due to normal calling of an operating system but the loads of the service threads are low and are falsely detected as the abnormal kernel-state loads is avoided; in particular, in order to improve the efficiency of detecting the core state load abnormality, in the process of acquiring the time ratio of processing the virtual machine service and the number ratio of the core state instructions, the detection data within the same detection time (for example, 2 seconds) may be acquired to ensure that the time ratio of processing the virtual machine service and the number ratio of the core state instructions are acquired simultaneously, thereby ensuring the timeliness of detecting the core state load abnormality in the virtual machine.
Optionally, in this embodiment of the present disclosure, when the number of kernel-state instructions in the instruction set of the service thread is obtained by the virtual machine monitor, the instruction address with the largest number of running times is also obtained by the virtual machine monitor synchronously; after determining that there is a kernel-state load exception in the virtual processor simulated by the current service thread, the method further includes: reporting the instruction address to a management device of the host machine, and/or sending the instruction address to a user device of the host machine.
Specifically, when the instruction number and the instruction type of each instruction read by the register of the virtual processor are obtained, the instruction address of each instruction, that is, the source of the instruction, can also be obtained at the same time; when determining that the kernel-state load of the virtual machine is abnormal, reporting the instruction address with the largest number of running times to management equipment of a host (for example, a management server of a cloud host) or sending the instruction address to user equipment of the host (for example, user side equipment connected with the cloud host) so that the management equipment or the user equipment can find the abnormal reason of the kernel-state load in time according to the instruction address, improve the reporting instantaneity of the instruction address, and simultaneously ensure that the reported instruction address is matched with the kernel-state load abnormity.
Optionally, in this embodiment of the present disclosure, after determining that there is a kernel-state load exception in the virtual processor simulated by the current service thread, the method further includes: acquiring an instruction address with the maximum operation times in the service thread through a virtual machine monitor; reporting the instruction address to a management device of the host machine, and/or sending the instruction address to a user device of the host machine. The instruction addresses of the instructions in the detection time are counted through the historical instructions accessed in the register after the kernel-state load abnormality of the virtual machine is determined, and the instruction address with the largest operation frequency is obtained, so that the instruction addresses are obtained in a targeted mode when the kernel-state load abnormality of the virtual machine is determined, the resource occupation of the virtual machine is reduced, and the problem that the extra resource overhead of the virtual machine is increased when the kernel-state load abnormality of the virtual machine does not exist is avoided.
According to the technical scheme of the embodiment, a service thread set used for simulating the virtual processor in the host is traversed, the kernel state load abnormity exists in the virtual processor simulated by the current service thread when the number proportion of kernel state instructions in the instruction set of the current service thread is acquired through the Hypervisor and is larger than the number proportion threshold value, and the load value of the current service thread is larger than the load threshold value, the effective detection of the kernel state load abnormity of the virtual machine can be realized without deploying information acquisition software in the virtual machine in advance, meanwhile, the influence of user safety precaution measures is avoided, and the safety risk in the virtual machine caused by the breakdown of a software program is avoided.
Example two
Fig. 2 is a method for detecting load anomaly according to an embodiment of the present disclosure, which is embodied on the basis of the foregoing embodiment, in the embodiment of the present disclosure, if a time ratio of processing the virtual machine service in the detection time of the current service thread is greater than a time ratio threshold, the number ratio of kernel-state instructions in the instruction set of the current service thread is continuously obtained through Hypervisor, otherwise, the processing time of processing the virtual machine service in the detection time of the next service thread is obtained, and the method specifically includes:
s201, acquiring host process information; s202 is performed.
S202, acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor; s203 is performed.
S203, traversing at least one service thread to obtain the time proportion of the current service thread to process the virtual machine service in the detection time; s204 is performed.
S204, judging whether the time ratio of the current service thread is larger than a time ratio threshold value; if yes, go to S205; if not, go to S209.
If the time ratio of the current service thread processing the virtual machine service in the detection time is less than or equal to the time ratio threshold, the load of the service thread per se is low, the number ratio of the kernel state instructions of the current service thread does not need to be acquired at the moment, the time ratios of other service threads in the service thread set are continuously acquired, and the detection efficiency of each service thread in the service thread set is further improved.
S205, acquiring the number ratio of kernel-state instructions in the instruction set of the current service thread and the instruction address with the largest operation times through a Hypervisor; s206 is performed.
S206, judging whether the number ratio of the current service thread is larger than a number ratio threshold value; if yes, go to S207; if not, go to S209.
S207, determining that kernel-state load abnormity exists in the virtual processor simulated by the current service thread; s208 is performed.
S208, reporting the instruction address to a management device of the host machine, and sending the instruction address to a user device of the host machine; 209 is performed.
S209, judging whether the service thread set is traversed; if yes, returning to S203; if not, go to S210.
And S210, ending.
According to the technical scheme of the embodiment of the disclosure, a service thread set used for simulating a virtual processor in a host is traversed, the time proportion of processing the virtual machine service in the detection time of the current service thread is obtained and is greater than a time proportion threshold, the number proportion of kernel-state instructions in an instruction set of the current service thread is obtained through Hypervisor, and when the number proportion of kernel-state instructions in the instruction set of the current service thread is greater than the number proportion threshold, the kernel-state load abnormity exists in the virtual processor simulated by the current service thread, and the detection efficiency of each service thread in the service thread set is further improved while the kernel-state load abnormity detection result accuracy in the virtual machine is ensured.
EXAMPLE III
Fig. 3 is a block diagram of a load abnormality detection apparatus provided in the third embodiment of the present disclosure, which specifically includes: a service thread set acquisition module 310, a number ratio acquisition module 320 and a load exception acquisition module 330;
a service thread set obtaining module 310, configured to obtain a service thread set of a host; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
the number ratio obtaining module 320 is configured to traverse the at least one service thread, obtain a load value of the service thread through system information of the service thread, and obtain a number ratio of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
a load exception obtaining module 330, configured to determine that a kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is greater than a load threshold and the number fraction is greater than a number fraction threshold.
According to the technical scheme of the embodiment, a service thread set used for simulating the virtual processor in the host is traversed, the kernel state load abnormity exists in the virtual processor simulated by the current service thread when the number proportion of kernel state instructions in the instruction set of the current service thread is acquired through the Hypervisor and is larger than the number proportion threshold value, and the load value of the current service thread is larger than the load threshold value, the effective detection of the kernel state load abnormity of the virtual machine can be realized without deploying information acquisition software in the virtual machine in advance, meanwhile, the influence of user safety precaution measures is avoided, and the safety risk in the virtual machine caused by the breakdown of a software program is avoided.
Optionally, on the basis of the above technical solution, the quantity ratio obtaining module 320 is specifically configured to obtain a time ratio of processing the virtual machine service in the detection time by the service thread.
Optionally, on the basis of the foregoing technical solution, the load exception obtaining module 330 is specifically configured to determine that a kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is greater than a load threshold, the number proportion is greater than a number proportion threshold, and the time proportion is greater than a time proportion threshold.
Optionally, on the basis of the above technical solution, the number ratio obtaining module 320 specifically includes:
the time ratio obtaining unit is used for traversing the at least one service thread to obtain the time ratio of the current service thread processing the virtual machine service in the detection time;
a quantity ratio obtaining unit, configured to obtain, by using a virtual machine monitor, a quantity ratio of kernel-state instructions in an instruction set of the current service thread if the time ratio of the current service thread is greater than a time ratio threshold.
And the traversal execution unit is used for continuously acquiring the processing time of the next service thread for processing the virtual machine service in the detection time if the time ratio of the current service thread is less than or equal to the time ratio threshold value until the service thread set is traversed.
Optionally, on the basis of the foregoing technical solution, the load exception obtaining module 330 is further configured to determine that no kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is less than or equal to a load threshold and/or the number proportion is less than or equal to a number proportion threshold.
Optionally, on the basis of the above technical solution, the number ratio obtaining module 320 is specifically further configured to, when obtaining the number ratio of the kernel-state instructions in the instruction set of the service thread through the virtual machine monitor, further obtain the instruction address with the largest number of running times through the virtual machine monitor synchronously.
Optionally, on the basis of the above technical solution, the load abnormality detection apparatus further includes:
and the instruction address sending module is used for reporting the instruction address to the management equipment of the host machine and/or sending the instruction address to the user equipment of the host machine.
Optionally, on the basis of the above technical solution, the load abnormality detection apparatus further includes:
and the instruction address acquisition module is used for acquiring the instruction address with the maximum operation times in the service thread through the virtual machine monitor.
Optionally, on the basis of the above technical solution, the service thread set obtaining module 310 is specifically configured to update the service thread set of the host in real time according to the process information of the host.
The device can execute the load abnormity detection method provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method. Technical details that are not elaborated in this embodiment may be referred to a method provided by any embodiment of the present disclosure.
Example four
FIG. 4 illustrates a schematic diagram of a server 400 suitable for use in implementing embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The server shown in fig. 4 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present disclosure.
As shown in fig. 4, the server 400 may include a processing device (e.g., central processing unit, graphics processor, etc.) 401 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage device 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the server 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
Generally, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the server 400 to communicate wirelessly or by wire with other devices to exchange data. While fig. 4 illustrates a server 400 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 409, or from the storage device 408, or from the ROM 402. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 401.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may 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 or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the server; or may exist separately and not be assembled into the server.
The computer readable medium carries one or more programs which, when executed by the server, cause the server to: acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor; traversing the at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number proportion of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction; if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented by software or hardware. The name of the module does not constitute a limitation on the module itself in some cases, for example, the number ratio obtaining module may be described as "a module for traversing the at least one service thread to obtain the load value of the service thread through the system information of the service thread, and obtaining the number ratio of the kernel-state instructions in the instruction set of the service thread through the virtual machine monitor". The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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 or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
According to one or more embodiments of the present disclosure, [ example 1 ] there is provided a load abnormality detection method including:
acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
traversing the at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number proportion of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread.
In accordance with one or more embodiments of the present disclosure, [ example 2 ] there is provided the method of example 1, further comprising:
acquiring the time occupation ratio of the service thread to process the virtual machine service in the detection time;
if the number proportion of the current service thread is larger than a number proportion threshold value and the time proportion is larger than a time proportion threshold value, determining that kernel-state load abnormity exists in the virtual processor simulated by the current service thread.
In accordance with one or more embodiments of the present disclosure, [ example 3 ] there is provided the method of example 2, further comprising:
traversing the at least one service thread to obtain the time proportion of the current service thread to process the virtual machine service in the detection time;
if the time ratio of the current service thread is greater than a time ratio threshold, acquiring the number ratio of kernel-state instructions in an instruction set of the current service thread through a virtual machine monitor;
and if the time ratio of the current service thread is less than or equal to a time ratio threshold, continuously acquiring the processing time of processing the virtual machine service in the detection time of the next service thread until the service thread set is traversed.
According to one or more embodiments of the present disclosure, [ example 4 ] there is provided the method of example 3, further comprising:
if the load value of the current service thread is less than or equal to a load threshold value and/or the number proportion is less than or equal to a number proportion threshold value, determining that kernel-state load abnormity does not exist in the virtual processor simulated by the current service thread.
According to one or more embodiments of the present disclosure, [ example 5 ] there is provided the method of any one of examples 1-4, further comprising:
when the number of kernel-state instructions in the instruction set of the service thread is obtained by the virtual machine monitor, the instruction address with the maximum operation times is synchronously obtained by the virtual machine monitor;
and reporting the instruction address to a management device of the host machine and/or sending the instruction address to a user device of the host machine after determining that the kernel state load abnormality exists in the virtual processor simulated by the current service thread.
According to one or more embodiments of the present disclosure, [ example 6 ] there is provided the method of any one of examples 1-4, further comprising:
after determining that kernel state load abnormity exists in the virtual processor simulated by the current service thread, acquiring an instruction address with the maximum operation times in the service thread through a virtual machine monitor;
reporting the instruction address to a management device of the host machine, and/or sending the instruction address to a user device of the host machine.
According to one or more embodiments of the present disclosure, [ example 7 ] there is provided the method of example 1, further comprising:
and updating the service thread set of the host machine in real time according to the process information of the host machine.
According to one or more embodiments of the present disclosure, [ example 8 ] there is provided a load abnormality detection apparatus including:
the service thread set acquisition module is used for acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
the number ratio acquisition module is used for traversing the at least one service thread, acquiring a load value of the service thread through system information of the service thread, and acquiring the number ratio of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
and the load exception acquisition module is used for determining that kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is greater than a load threshold and the number ratio is greater than a number ratio threshold.
According to one or more embodiments of the present disclosure, [ example 9 ] there is provided the apparatus of example 8, the number ratio obtaining module 320, specifically configured to obtain a time ratio of the service thread processing the virtual machine service within the detection time;
the load exception obtaining module 330 is specifically configured to determine that a kernel-state load exception exists in the virtual processor simulated by the current service thread if the number proportion of the current service thread is greater than a number proportion threshold and the time proportion is greater than a time proportion threshold.
According to one or more embodiments of the present disclosure, [ example 10 ] there is provided the apparatus of example 9, the number fraction obtaining module, specifically comprising:
the time ratio obtaining unit is used for traversing the at least one service thread to obtain the time ratio of the current service thread processing the virtual machine service in the detection time;
a quantity ratio obtaining unit, configured to obtain, by using a virtual machine monitor, a quantity ratio of kernel-state instructions in an instruction set of the current service thread if the time ratio of the current service thread is greater than a time ratio threshold;
and the traversal execution unit is used for continuously acquiring the processing time of the next service thread for processing the virtual machine service in the detection time if the time ratio of the current service thread is less than or equal to the time ratio threshold value until the service thread set is traversed.
According to one or more embodiments of the present disclosure, [ example 11 ] there is provided the apparatus of example 10, the load exception obtaining module is specifically configured to determine that there is no kernel-state load exception in the virtual processor simulated by the current service thread if the load value of the current service thread is less than or equal to a load threshold and/or the number fraction is less than or equal to a number fraction threshold.
According to one or more embodiments of the present disclosure, [ example 12 ] there is provided the apparatus of any one of examples 8 to 11, the number ratio obtaining module, specifically, the apparatus is further configured to, when obtaining the number ratio of the kernel-state instructions in the instruction set of the service thread through a virtual machine monitor, further obtain, through the virtual machine monitor, the instruction address with the largest number of running times;
the load abnormality detection device further includes:
and the instruction address sending module is used for reporting the instruction address to the management equipment of the host machine and/or sending the instruction address to the user equipment of the host machine.
According to one or more embodiments of the present disclosure, [ example 13 ] there is provided the apparatus of any one of examples 8-11, further comprising:
the instruction address acquisition module is used for acquiring the instruction address with the maximum operation times in the service thread through a virtual machine monitor;
and the instruction address sending module is used for reporting the instruction address to the management equipment of the host machine and/or sending the instruction address to the user equipment of the host machine.
According to one or more embodiments of the present disclosure, [ example 14 ] there is provided the apparatus of example 8, the business thread set obtaining module, configured to update the business thread set of the host in real time according to the process information of the host.
According to one or more embodiments of the present disclosure, [ example 15 ] there is provided a server comprising a memory, a processing device, and a computer program stored on the memory and executable on the processing device, the processing device implementing the load abnormality detection method according to any one of examples 1-7 when executing the program.
According to one or more embodiments of the present disclosure, [ example 16 ] there is provided a storage medium containing computer-executable instructions for performing the load anomaly detection method of any one of examples 1-7 when executed by a computer processor.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (10)
1. A method of detecting load anomalies, comprising:
acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
traversing the at least one service thread to obtain a load value of the service thread through system information of the service thread and obtain the number proportion of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread.
2. The method according to claim 1, wherein the obtaining the load value of the service thread through the system information of the service thread comprises:
acquiring the time occupation ratio of the service thread to process the virtual machine service in the detection time;
if the load value of the current service thread is greater than a load threshold value and the number ratio is greater than a number ratio threshold value, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread, including:
if the time ratio of the current service thread is greater than a time ratio threshold and the number ratio is greater than a number ratio threshold, determining that kernel-state load exception exists in the virtual processor simulated by the current service thread.
3. The method of claim 2, wherein traversing the at least one business thread to obtain a load value of the business thread through system information of the business thread and obtain a ratio of a number of kernel-state instructions in an instruction set of the business thread through a virtual machine monitor, further comprises:
traversing the at least one service thread to obtain the time proportion of the current service thread to process the virtual machine service in the detection time;
if the time ratio of the current service thread is greater than a time ratio threshold, acquiring the number ratio of kernel-state instructions in an instruction set of the current service thread through a virtual machine monitor;
and if the time ratio of the current service thread is less than or equal to a time ratio threshold, continuously acquiring the processing time of processing the virtual machine service in the detection time of the next service thread until the service thread set is traversed.
4. The method of claim 1, further comprising:
if the load value of the current service thread is less than or equal to a load threshold value and/or the number proportion is less than or equal to a number proportion threshold value, determining that kernel-state load abnormity does not exist in the virtual processor simulated by the current service thread.
5. The method according to any one of claims 1 to 4, wherein when the number of kernel-state instructions in the instruction set of the service thread is obtained by the virtual machine monitor, the instruction address with the largest number of running times is obtained by the virtual machine monitor synchronously;
after determining that there is a kernel-state load exception in the virtual processor simulated by the current service thread, the method further includes:
reporting the instruction address to a management device of the host machine, and/or sending the instruction address to a user device of the host machine.
6. The method according to any of claims 1-4, wherein after determining that there is a kernel-mode load exception in the virtual processor emulated by the current business thread, further comprising:
acquiring an instruction address with the maximum operation times in the service thread through a virtual machine monitor;
reporting the instruction address to a management device of the host machine, and/or sending the instruction address to a user device of the host machine.
7. The method of claim 1, wherein obtaining the set of business threads of the host comprises:
and updating the service thread set of the host machine in real time according to the process information of the host machine.
8. A load abnormality detection device characterized by comprising:
the service thread set acquisition module is used for acquiring a service thread set of a host machine; the business thread set comprises at least one business thread, and the business thread is used for simulating a virtual processor;
the number ratio acquisition module is used for traversing the at least one service thread, acquiring a load value of the service thread through system information of the service thread, and acquiring the number ratio of kernel-state instructions in an instruction set of the service thread through a virtual machine monitor; wherein the instruction set comprises the kernel-state instruction and a user-state instruction;
and the load exception acquisition module is used for determining that kernel-state load exception exists in the virtual processor simulated by the current service thread if the load value of the current service thread is greater than a load threshold and the number ratio is greater than a number ratio threshold.
9. A server comprising a memory, a processing device and a computer program stored on the memory and executable on the processing device, wherein the processing device implements the load anomaly detection method according to any one of claims 1 to 7 when executing the program.
10. A storage medium containing computer-executable instructions for performing the load anomaly detection method of any one of claims 1-7 when executed by a computer processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210038863.2A CN114398233B (en) | 2022-01-13 | 2022-01-13 | Load abnormality detection method and device, server and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210038863.2A CN114398233B (en) | 2022-01-13 | 2022-01-13 | Load abnormality detection method and device, server and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114398233A true CN114398233A (en) | 2022-04-26 |
| CN114398233B CN114398233B (en) | 2023-06-06 |
Family
ID=81231020
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210038863.2A Active CN114398233B (en) | 2022-01-13 | 2022-01-13 | Load abnormality detection method and device, server and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114398233B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106951321A (en) * | 2017-02-13 | 2017-07-14 | 深信服科技股份有限公司 | The management method and device of CPU resources of virtual machine |
| CN111209079A (en) * | 2019-12-27 | 2020-05-29 | 山东乾云启创信息科技股份有限公司 | Scheduling method, device and medium based on Roc processor |
| CN112463288A (en) * | 2019-09-09 | 2021-03-09 | 北京奇虎科技有限公司 | Behavior monitoring method and system based on pile insertion |
-
2022
- 2022-01-13 CN CN202210038863.2A patent/CN114398233B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106951321A (en) * | 2017-02-13 | 2017-07-14 | 深信服科技股份有限公司 | The management method and device of CPU resources of virtual machine |
| CN112463288A (en) * | 2019-09-09 | 2021-03-09 | 北京奇虎科技有限公司 | Behavior monitoring method and system based on pile insertion |
| CN111209079A (en) * | 2019-12-27 | 2020-05-29 | 山东乾云启创信息科技股份有限公司 | Scheduling method, device and medium based on Roc processor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114398233B (en) | 2023-06-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111090536B (en) | Method, device, medium and electronic equipment for acquiring memory leakage information | |
| CN113835992B (en) | Memory leakage processing method and device, electronic equipment and computer storage medium | |
| CN110377341B (en) | Method, device, medium and electronic equipment for monitoring no-response exception | |
| CN107644075B (en) | Method and device for collecting page information | |
| CN110618928A (en) | Memory leak detection method and device, terminal equipment and medium | |
| CN110554918B (en) | Current limiting method, current limiting device, electronic equipment and computer readable storage medium | |
| CN113760503A (en) | Task migration method and device, electronic equipment and computer readable medium | |
| CN112084024A (en) | Memory monitoring method, device, medium and electronic equipment | |
| CN112817701B (en) | Timer processing method, device, electronic equipment and computer readable medium | |
| CN114398233B (en) | Load abnormality detection method and device, server and storage medium | |
| CN114741686A (en) | Method and device for detecting program white list and related equipment | |
| CN111026504B (en) | Processing method and device for configuring instruction for acquiring processor information in virtual machine, CPU chip, system on chip and computer | |
| CN111382057B (en) | Test case generation method, test method and device, server and storage medium | |
| CN111949528A (en) | Memory leak detection method and device, electronic equipment and storage medium | |
| CN111538717A (en) | Data processing method and device, electronic equipment and computer readable medium | |
| CN116383013B (en) | Method for collecting monitoring information of server equipment and electronic equipment | |
| CN111782410B (en) | Lock jam monitoring method and device, electronic equipment and computer readable medium | |
| CN111026571B (en) | Processor down-conversion processing method and device and electronic equipment | |
| CN111404824B (en) | Method, apparatus, electronic device, and computer-readable medium for forwarding request | |
| CN110489341B (en) | Test method and device, storage medium and electronic equipment | |
| CN117093284A (en) | Plug-in calling method, device, medium and electronic equipment | |
| CN116302142A (en) | Lifecycle event management method, lifecycle event management device, storage medium, and electronic apparatus | |
| CN115373894A (en) | Data recovery method and device, electronic equipment and computer readable medium | |
| CN116701013A (en) | Message consumption method, device, electronic equipment and computer readable medium | |
| CN116263824A (en) | Resource access method and device, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |