CN114006907A

CN114006907A - Service degradation method and device for distributed server, electronic equipment and medium

Info

Publication number: CN114006907A
Application number: CN202111266932.7A
Authority: CN
Inventors: 尹勇; 罗涛
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2021-10-28
Filing date: 2021-10-28
Publication date: 2022-02-01

Abstract

The disclosure provides a service degradation method and device of a distributed server, electronic equipment and a readable storage medium, which can be applied to the financial field or other fields. The service degradation method comprises the following steps: acquiring service types of M nodes of a distributed server, wherein the service types have N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers greater than 1; analyzing the service types and the service attributes by a hierarchical analysis method to obtain a first weight sequence of the service types; obtaining a rated load threshold value of a data request of a distributed server, comparing the current load threshold value with the rated load threshold value, and starting service degradation when the current load threshold value is larger than the rated load threshold value; and degrading the server of the node corresponding to the service type according to the first weighted ranking order so as to reject the data request received in the current time period.

Description

Service degradation method and device for distributed server, electronic equipment and medium

Technical Field

The present disclosure relates to the field of internet technologies, and in particular, to a method and an apparatus for degrading service of a distributed server, an electronic device, and a computer-readable storage medium.

Background

With the development of information technology, the amount of information data which needs to be processed by the server is larger and larger. Under the condition of sharp increase of the server pressure, some services and pages are processed in a policy-free or simple mode according to the actual service condition and flow, so that server resources are released to ensure normal operation or efficient operation of core transactions. In the related art, a distributed switch is arranged in a distributed system and used for realizing degradation of services, in the degradation process, the types of services processed by a server are different, and effective degradation means cannot be adopted for different service types due to different load pressures of the servers corresponding to different service types. Particularly, in large promotion or killing activities, the load pressure of the server is increased sharply, and the server is easy to be paralyzed when the load pressure cannot be degraded according to the service type, so that the user experience is reduced.

Disclosure of Invention

In view of this, the present disclosure provides a service degradation method and apparatus for a distributed server, an electronic device, and a computer-readable storage medium, which can degrade different servers according to service types, effectively reduce load pressure of the servers, and provide better experience for users when the load pressure is higher.

A first aspect of the present disclosure provides a service degradation method for a distributed server, including: obtaining service types of M nodes of a distributed server, wherein the service types have N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers larger than 1; analyzing the service types and the service attributes by a hierarchical analysis method to obtain a first weight sequence of the service types; obtaining a rated load threshold value of a data request of the distributed server, comparing the current load threshold value with the rated load threshold value, and starting service degradation when the current load threshold value is larger than the rated load threshold value; and degrading the server of the node corresponding to the service type according to the first weighted ranking order so as to reject the data request received in the current time period.

In some embodiments of the present disclosure, the analyzing the service type and the service attribute by a hierarchical analysis method, and obtaining the first weight ranking of the service type includes: establishing a hierarchical analysis model, wherein the hierarchical analysis model comprises a highest layer, a middle layer and a lowest layer, the middle layer comprises the service attribute, and the lowest layer comprises the service type; establishing a comparison matrix and a level single sequence of the lowest layer and the middle layer, and carrying out consistency check on the comparison matrix; a hierarchical total ordering is constructed and a consistency check is performed to generate a first weighted ordering of the service types.

In some embodiments of the present disclosure, the downgrading, according to the first weighted ordering, the servers of the nodes corresponding to the service type includes: generating a downgrade instruction according to the first weight ranking; receiving the degradation instruction, and checking whether the degradation state of the target server to be degraded is started; if the degradation state of the target server is started, rejecting the degradation instruction; and if the degradation state of the target server is closed, receiving the degradation instruction and degrading the target server.

In some embodiments of the present disclosure, the receiving the destage instruction, destaging the target server comprises: receiving the degradation instruction, executing the degradation instruction by the target server, and counting the degradation starting time and the current time interval of the target server; if the time interval is smaller than the set interval, rejecting the data request from the user; and if the time interval is not less than the set interval, sending the time interval to a control center.

In some embodiments of the disclosure, after sending the time interval to the control center, the service degradation method further comprises: obtaining server attributes of the servers of the M nodes; calculating the current load bearing values of the M nodes according to the server attribute; comparing the current load bearing value with a set threshold value; if the load bearing value is larger than the set threshold value, rejecting a data request from a user; and if the load bearing value is not greater than the set threshold value, receiving a data request from a user, and setting the degradation state of the target server to be closed.

In some embodiments of the present disclosure, after the load bearing value is greater than the set threshold and the data request from the user is rejected, counting the rejected times of the data request, and generating a priority degradation policy according to the rejected times.

In some embodiments of the present disclosure, the server attributes include CPU usage, storage usage, and memory usage.

In some embodiments of the present disclosure, the service attributes include: two or more of a critical path degree level, a current user number, a network transmission data amount, a configuration current limiting level, a service use frequency, and a service security level.

A second aspect of the embodiments of the present disclosure provides a service degradation apparatus for a distributed server, including: the system comprises an acquisition module, a service module and a service module, wherein the acquisition module is configured to acquire service types of M nodes of a distributed server, the service types are provided with N service attributes, the N service attributes of each service type are provided with different weights, and M and N are positive integers larger than 1; the analysis module is configured to analyze the service types and the service attributes through a hierarchical analysis method to obtain a first weight sequence of the service types; the processing module is configured to obtain a rated load threshold of a data request of the distributed server, compare the current load threshold with the rated load threshold, and start service degradation when the current load threshold is larger than the rated load threshold; and the degradation module is configured to degrade the server of the node corresponding to the service type according to the first weighted ranking so as to reject the data request received in the current time period.

In some embodiments of the present disclosure, the analysis module comprises an analysis submodule configured to build a hierarchical analysis model comprising a highest layer, a middle layer and a lowest layer, the middle layer comprising the service attributes, the lowest layer comprising the service types; establishing a comparison matrix and a level single sequence of the lowest layer and the middle layer, and carrying out consistency check on the comparison matrix; a hierarchical total ordering is constructed and a consistency check is performed to generate a first weighted ordering of the service types.

In some embodiments of the present disclosure, the demotion module includes a demotion submodule configured to generate demotion instructions according to the first weight ranking; receiving the degradation instruction, and checking whether the degradation state of the target server to be degraded is started; if the degradation state of the target server is started, rejecting the degradation instruction; and if the degradation state of the target server is closed, receiving the degradation instruction and degrading the target server.

In some embodiments of the present disclosure, the downgrading submodule further includes a statistics module, the statistics module is configured to receive the downgrading instruction, the target server executes the downgrading instruction, and counts a downgrading start time and a current time interval of the target server; if the time interval is smaller than the set interval, rejecting the data request from the user; and if the time interval is not less than the set interval, sending the time interval to a control center.

In some embodiments of the present disclosure, the service downgrading apparatus further includes a comparison module, configured to obtain the server attributes of the servers of the M nodes after sending the time interval to a control center; calculating the current load bearing values of the M nodes according to the server attribute; comparing the current load bearing value with a set threshold value, and if the load bearing value is larger than the set threshold value, rejecting a data request from a user; and if the load bearing value is not greater than the set threshold value, receiving a data request from a user, and setting the degradation state of the target server to be closed.

A third aspect of the embodiments of the present disclosure provides an electronic device, including: one or more processors; storage means for storing executable instructions that, when executed by the processor, implement the service downgrading method according to the above.

A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, implement a service downgrading method according to the above.

A fifth aspect of an embodiment of the present disclosure provides a computer program product comprising a computer program which, when executed by a processor, implements a service downgrading method according to the above.

According to the service degradation method disclosed by the embodiment of the disclosure, the first weight sequence of the service types of different nodes can be obtained by adopting a hierarchical analysis method, and the servers of the nodes are degraded according to the first weight sequence, so that unimportant services are preferentially degraded under the condition of high load pressure in the current time period, and the user experience is improved.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

fig. 1 schematically illustrates an application scenario of a service degradation method of a distributed server according to an embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow diagram of a service downgrading method, according to an embodiment of the disclosure;

FIG. 3 schematically illustrates a flow chart for obtaining a first weighted ranking of service types according to a service downgrading method of an embodiment of the disclosure;

FIG. 4 schematically illustrates a flow diagram for downgrading a node server for a service downgrading method according to an embodiment of the disclosure;

FIG. 5 schematically illustrates a flow diagram for downgrading a target server for a service downgrading method according to an embodiment of the disclosure;

FIG. 6 schematically illustrates a flow diagram of a service downgrading method after sending a time interval to a control center, according to an embodiment of the disclosure;

FIG. 7 schematically illustrates a block diagram of a service downgrading apparatus, according to an embodiment of the present disclosure;

FIG. 8 schematically illustrates a block diagram of an electronic device adapted to implement a service downgrading method, according to an embodiment of the disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "a or B" should be understood to include the possibility of "a" or "B", or "a and B".

The embodiment of the disclosure provides a service degradation method for a distributed server, which includes: acquiring service types of M nodes of a distributed server, wherein the service types have N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers greater than 1; analyzing the service types and the service attributes by a hierarchical analysis method to obtain a first weight sequence of the service types; obtaining a rated load threshold value of a data request of the distributed server, comparing the current load threshold value with the rated load threshold value, and starting service degradation when the current load threshold value is larger than the rated load threshold value; and degrading the server of the node corresponding to the service type according to the first weighted ranking order so as to reject the data request received in the current time period.

According to the embodiment of the disclosure, the first weight sequence of the service types of different nodes can be obtained by adopting a hierarchical analysis method, and the servers of the nodes are degraded according to the first weight sequence, so that unimportant services are preferentially degraded under the condition of high load pressure in the current time period, and the user experience is improved.

Fig. 1 schematically illustrates an application scenario of a service degradation method of a distributed server according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of an application scenario in which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, but does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios. It should be noted that the service degradation method, the apparatus, the electronic device, and the computer-readable storage medium of the distributed server provided by the embodiments of the present disclosure may be used in related aspects in the internet technology field, the big data technology field, and the financial field, and may also be used in other fields outside the financial field.

As shown in fig. 1, an application scenario 100 according to an embodiment of the present disclosure may include

terminal devices

101, 102, 103, a network 104 and a control center 105, distributed

servers

106, 107, 108. The network 104 is used to provide a medium of communication links between the

terminal devices

101, 102, 103 and the control center 105 or between the control center 105 and the

distributed servers

106, 107, 108. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the control center 105 through the network 104 to receive or send messages and the like, and the control center 105 sends messages or requests and the like sent by the

terminal devices

101, 102, 103 to the

distributed servers

106, 107, 108 through the network 104 for processing, or receives instructions or messages and the like returned from the

distributed servers

106, 107, 108. Various client applications, such as an input method application, a shopping application, a web browser application, a search application, an instant messaging tool, a mailbox client, social platform software, etc. (just examples), may be installed on the

terminal devices

101, 102, 103, and data exchange, data call, data transmission, etc. may be implemented between the terminal devices and the load balancing server and the cluster server through the network. The control center 105 is used to control the

distributed servers

106, 107, 108 to downgrade, thereby providing a better experience for the user.

The

terminal devices

101, 102, and 103 may be various electronic devices supporting information acquisition and information transmission, where the information acquisition includes web browsing, voice broadcasting, and the like, and may be performed by sending a request instruction to the control center 105, and the control center 105 allocates and sends information to the

distributed servers

106, 107, and 108 to perform information acquisition or call, and finally return the information to the terminal devices, and perform display by an information display device of the terminal devices, such as displaying pictures or characters by a display screen, or performing information display by voice broadcasting, and the like. The electronic devices include, but are not limited to, smart speakers, smart phones, smart televisions, smart bracelets, tablet computers, laptop portable computers, desktop computers, and the like.

The

distributed servers

106, 107, 108 may be servers that provide various services, such as a backend management server (by way of example only) that provides support for a website that a user browses or retrieves information or information using instructions sent by the

terminal devices

101, 102, 103, or WEB servers, FTP servers, enterprise core application servers, and other primary task servers, etc. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to a voice instruction of the user or the user request) to the terminal device. The distributed

servers

106, 107, 108 are used to complete work tasks in cooperation with the control center 105.

It should be noted that the service degradation method provided by the embodiment of the present disclosure may be generally executed by the control center 105. Accordingly, the service downgrading apparatus provided by the embodiments of the present disclosure may be generally disposed in the server 105. In an alternative embodiment, the service degradation method provided by the embodiment of the present disclosure may be generally performed by the distributed

servers

106, 107, and 108 in cooperation with the control center 105. Accordingly, the service downgrading apparatus provided by the embodiments of the present disclosure may be generally disposed in the distributed

servers

106, 107, 108 and the control center 105.

It should be understood that the number of terminal devices, networks and control centers, distributed servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks and control centers, and distributed servers, as desired for implementation.

Fig. 2 schematically shows a flow chart of a service downgrading method according to an embodiment of the present disclosure.

The service degradation method according to the embodiment of the present disclosure is described in detail below with reference to fig. 2.

As shown in fig. 2, the service degradation method 200 of the distributed server of the embodiment of the present disclosure includes operations S201 to S204.

In operation S201, service types of M nodes of a distributed server are obtained, where a service type has N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers greater than 1. For example, M can be 2, 3, or 4, N can be 3, 4, or 5, and so on.

According to embodiments of the present disclosure, the distributed servers may be, for example, servers deployed at different locations, and different servers may be used to process different services. The server for processing the same service may have one node or a plurality of nodes. Nodes handling the same traffic have a service type, i.e. their corresponding traffic class. Each service type has a plurality of service attributes, for example, the service attributes include two or more of a critical path degree level, a current user number, a network transmission data amount, a configuration current limiting level, a service use frequency and a service security level.

In an embodiment of the present disclosure, the N service attributes of each service type have different weights. For example, the service types include a login service, a query user information service, a payment service, and the like. For the login service, the service attributes include a critical path degree level, the number of current users, the network transmission data volume, a configuration current limiting level, a service use frequency and a service security level. And, each service attribute included therein has different weight corresponding to the login service, for example, the weight of the degree of the critical path, the number of current users, etc. in the login service and the query user information service are different.

In operation S202, the service types and the service attributes are analyzed by a hierarchical analysis method, and a first weight ranking of the service types is obtained. Operation S202 is described in detail below with reference to fig. 3.

Fig. 3 schematically shows a flowchart for obtaining a first weight ranking of service types according to a service downgrading method of an embodiment of the present disclosure.

As shown in fig. 3, in The embodiment of The present disclosure, The process 300 of obtaining The first weight ranking of The service type by analyzing The service type and The service attribute through a hierarchical analysis method (AHP) includes operations S301 to S303.

In operation S301, a hierarchical analysis model is established, where the hierarchical analysis model includes a top layer, a middle layer and a bottom layer, the middle layer includes service attributes, and the bottom layer includes service types.

In an embodiment of the present disclosure, the highest layer is a problem to be solved, and in this embodiment, the highest layer is a first weight ranking of service types. The middle layer comprises service attributes, namely, factors to be considered for obtaining the first weight sorting of the service types are analyzed according to the difference of the service attributes of each service type. The lowest layer includes the service type, i.e., the type of service that needs to be downgraded.

In operation S302, comparison matrices and hierarchical single ranks of the lowest layer and the middle layer are constructed, and consistency check is performed on the comparison matrices.

In embodiments of the present disclosure, the pair-wise comparison matrix is a comparison that represents the relative importance of all factors of the current layer to one factor of the previous layer. Element a of the pairwise comparison matrix_ijThe results of the comparison of the ith factor expressed relative to the jth factor are given using the scale 1-9 method as shown in Table-1 below. For example, all factors of the layer may be service type, and some factor of the upper layer may be service attribute.

TABLE-1

Starting from the 2 nd layer of the hierarchical analysis model, a pair comparison matrix is constructed for a plurality of factors of the same layer depending on each factor of the previous layer, and the comparison matrix is constructed to the lowest layer.

For example, a pairwise comparison matrix A is constructed based on a plurality of service attributes and the final selected service type importance degree, the service attributes including a critical path degree grade (A)₁) Current number of users (A)₂) Network transmission data volume (A)₃) Configuring the current limiting class (A)₄) Service usage frequency (A)₅) And service security level (A)₆). Constructed as a pair-wise comparison matrix A of

After the paired comparison matrix A is constructed, calculating the level single sequence (single-layer weight vector) and carrying out consistency check on the comparison matrix A to determine the inconsistent allowable range of the comparison matrix A.

Specifically, feature weight vectors of the paired comparison matrix a are calculated, and if the paired comparison matrix is a uniform matrix, normalized feature weight vectors of the corresponding maximum feature roots are taken. And if the first contrast matrix is not a consistent matrix, using the normalized feature vector corresponding to the maximum feature root as a weight vector, namely determining the weight vector by using a feature root method.

For example, if the maximum eigenvalue λ of a is calculated to be 6.35, the response is determined to have the eigenvector W⁽²⁾＝(0.16，0.19，0.19，0.05，0.12，0.30)^T。

The step of performing consistency check on the comparison matrix A comprises the following steps:

first, the identity index CI is constructed as (λ -n)/(n-1), where n is the number of orders representing the comparison matrix and λ represents the largest eigenroot of the comparison matrix. When CI is 0, it indicates that the constructed paired comparison matrix a has consistency. When CI is close to 0, it indicates that the constructed pair comparison matrix has satisfactory consistency. When the CI is larger, the constructed pairwise comparison matrix is more inconsistent. In judging the consistency of the comparison matrix, there may be a difference, but not too large. That is, if the consistency index is within the set range, the comparison matrix A passes the consistency check, otherwise, the comparison matrix A does not pass the consistency check, and the comparison matrix needs to be reconstructed.

For example, the consistency index CI of the comparison matrix a is calculated to be (6.35-6)/(6-1) to be 0.07.

Next, a random consistency index RI is obtained. The consistency check is calculated by calculating a consistency ratio CR, which is calculated by a random consistency index RI, which is a statistically derived value. For example, the random consistency index yields RI 1.24 by table lookup.

Next, the consistency ratio CR is calculated from the values of RI and CI. Specifically, the consistency ratio CR is CI/RI, and when the consistency ratio CR < x, the degree of inconsistency of the pair comparison matrix a is considered to be within an allowable range, and satisfactory consistency is obtained, that is, the pair comparison matrix a is considered to pass the consistency check. Where x is a set value that can be adjusted for different scenarios. If the consistency ratio CR is larger than or equal to x, the comparison matrix A is considered to not pass the consistency check, and the comparison matrix A needs to be reconstructed. For example, CR 0.07/1.24 0.0565 < 0.1 indicates that the pairwise comparison matrix a passes the consistency check.

In the embodiment of the present disclosure, as described above, the pair-wise comparison matrix for the login service, the payment service, and the query user information service with respect to 6 service attributes is:

the same method is adopted for the paired comparison matrix B_n(n-1, 2, 3, 4, 5, 6) performing consistency check to determine a pairwise comparison matrix B_nAll passed the consistency test.

According to the pair comparison matrix, the maximum eigenvalue and the corresponding eigenvector obtained by calculation are as follows:

λ₁＝0.302，λ₂＝3.02，λ₃＝3.05，λ₄＝3.05，λ₅＝3.00，λ₆＝3.02。

in operation S303, a hierarchical overall ranking is constructed and a consistency check is performed to generate a first weighted ranking of service types.

And calculating the weight vector of the relative importance of all the factors of the lower layer to the highest layer. And the consistency check is used for checking, if the consistency check passes the check, the decision can be made according to the result represented by the total sorting weight vector, otherwise, the model needs to be considered again or the paired comparison matrix with the larger consistency ratio CR needs to be reconstructed.

For example, the feature weight vector W ═ W⁽³⁾×W^(2）I.e. by

Thus, the first weight ordering to determine the service type is:

login service > payment service > query user information service

In other words, in the first weight ranking of the service types, the weight of the login service is greater than that of the payment service and is greater than that of the inquiry user information service. Downgraded services may be ordered according to the first weights of the respective service types. For example, if the weight of the query subscriber information service is the minimum, the query subscriber information service can be preferentially degraded, i.e., the query subscriber information service is turned off.

In operation S203, a rated load threshold of the data request of the distributed server is obtained, the current load threshold is compared with the rated load threshold, and when the current load threshold is greater than the rated load threshold, service degradation is started.

In an embodiment of the disclosure, the data requests of the distributed servers are data requests from users, and the entire system of distributed servers has a nominal load threshold. In actual operation, due to activities like sales promotion or killing in seconds, data requests from users received by the system within a certain current time or a certain future time will increase sharply, resulting in the rated load threshold of the system being exceeded. Therefore, when the current load threshold of the system is greater than the rated load threshold of the system, the servers of the system need to be degraded to relieve the processing pressure of the servers.

In operation S204, the servers of the nodes corresponding to the service types are downgraded according to the first weighted ranking to reject the data request received in the current time period.

In the embodiment of the present disclosure, after receiving the instruction of service degradation, the control center needs to degrade the server of the node corresponding to the service type according to the first weighted reordering. For example, as described above, the service types obtained by the first weight ranking are ranked as login service > payment service > query user information service, that is, the first weight of the query user information service is the smallest, so that the downgrading instruction may be set to downgrade the server of the node corresponding to the query user information service preferentially to reject the data request received in the current time period. For example, a data request for inquiring user information service received in the current time period is rejected, and the data request for login service and the data request for payment service are not degraded.

In an optional embodiment of the disclosure, the service degradation instruction may include an instruction to degrade a plurality of services, for example, may be an instruction generated according to the first weight ranking and including service degradation to the payment service and the query user information service. And in the service degradation process, the service degradation is preferentially carried out on the service for inquiring the user information, and under the condition that the current load threshold of the system is still larger than the rated load threshold, the service degradation is continuously carried out on the payment service until the current load threshold is smaller than or equal to the rated load threshold.

In this embodiment, the service type is a login service, a payment service, and a service for querying user information, and in other optional embodiments, the service type may also be a service with a larger number or another service type other than the examples, and the type and the number of the service type are not limited in this disclosure.

Fig. 4 schematically shows a flowchart for downgrading a node server according to a service downgrading method of an embodiment of the present disclosure.

In an embodiment of the present disclosure, the process 400 of downgrading a server of a node corresponding to a service type according to the first weighted ranking includes operations S401 to S404.

In operation S401, a demotion instruction is generated according to the first weight ranking.

In the embodiment of the disclosure, the downgrading instruction is generated according to the first weight sequence, and the downgrading instruction includes at least one downgrading request of a corresponding service type. The downgrading instruction comprises a downgrading request queue, and the downgrading request queue in the downgrading instruction is generated according to a first weight sequence, for example, in the first weight sequence, a service type with a small weight can be a service type which is arranged at the front of the downgrading request queue and is downgraded preferentially, so that the service type with an unimportant downgrading priority is indicated. The service type with large weight can be arranged at the rear column of the degradation request queue, and in the degradation process, the service type with relatively important weight is degraded, so that the use experience of the user is ensured.

When the control center issues the downgrading instruction to the server of the node, the control center may select one downgrading request or multiple downgrading requests in the downgrading request queue, which is adjusted according to an actual demand and a difference between a current load threshold and a rated load threshold of the system.

In operation S402, a destage instruction is received, and it is checked whether a destage status of a target server to be destaged is on.

In the embodiment of the disclosure, a degradation request queue in the degradation instruction includes one or more servers to be degraded, and after receiving the degradation instruction, the control center issues the degradation instruction to a target server to be degraded and checks the degradation state of the target server, so as to determine whether to execute the degradation instruction according to the current state of the target server.

In operation S403, if the degradation status of the target server is on, the degradation instruction is rejected.

And the degradation state of the target server is started, the target server is degraded, the target server does not need to be degraded, and the degradation instruction of the control center is refused.

In operation S404, if the degradation status of the target server is closed, a degradation instruction is received, and the target server is degraded.

And if the degradation state of the target server is closed, indicating that the target server can be degraded, receiving a degradation instruction, and degrading the target server to relieve the current load pressure of the system.

Fig. 5 schematically shows a flowchart of a method of downgrading a target server according to an embodiment of the present disclosure.

As shown in fig. 5, after receiving the destaging instruction, the process 500 of destaging the target server includes operations S501 to S504.

In operation S501, a destaging instruction is received, the target server executes the destaging instruction, and the destaging start time and the current time interval of the target server are counted.

And after receiving the degradation instruction, the target server executes the degradation instruction, records the degradation starting time of the target server after the target server starts to degrade, and calculates the time length after the target server degrades along with the start of the degradation of the target server, namely, the degradation starting time of the target server and the current time interval are counted. So as to carry out subsequent control on the target server according to the counted time interval.

In operation S502, the time interval counted in operation S501 is compared with the set interval. If the time interval is less than the set interval, operation S503 is performed, and if the time interval is not less than the set interval, operation S504 is performed. In the embodiments of the present disclosure, the set interval is adjusted according to actual requirements, for example, the set interval is 10 s. In alternative embodiments, the set interval may be of other lengths of time.

In the embodiment of the disclosure, by setting the set interval of server degradation, it is ensured that the server can realize the reduction of the current load threshold of the server after the degradation. That is, it is necessary to ensure that the server is in the degraded state for a certain time, rather than immediately closing the degraded state after the degradation.

In operation S503, a data request from a user is rejected.

The time interval is less than the set interval indicating that the servers of the system are not degraded to the predetermined load threshold, and therefore, in this case, when there is a data request from a user associated with that server type, the data request from the user is directly rejected.

In operation S504, the time interval is transmitted to the control center.

The time interval is not less than the set interval, indicating that the servers of the system may have degraded to the predetermined load threshold, and certainly not. The statistical time interval is thus sent to the control centre, which performs further control in accordance with the statistical time interval.

Fig. 6 schematically shows a flow chart of a service downgrading method after sending a time interval to a control center according to an embodiment of the disclosure.

As shown in fig. 6, the flow 600 after the time interval is transmitted to the control center includes operations S601 to S605.

In operation S601, server attributes of servers of M nodes are acquired.

And after the time interval is sent to the control center, the server attributes of the M node servers are obtained. The server attributes include CPU usage, storage usage, memory usage, etc., for example storage usage may be JVM usage. The server attribute of the server of the node may reflect the operation state of the entire system, for example, when the CPU utilization, the storage utilization, the memory utilization, and the like are all at higher values, it indicates that the load pressure of the server is higher, and if the CPU utilization, the storage utilization, the memory utilization, and the like are at lower values, it indicates that the load pressure of the server is lower. According to different load pressures of the servers, the degradation state of the servers can be continuously opened or closed, and the adjustment of the servers is realized.

In operation S602, current load bearing values of the M nodes are calculated according to the server attributes.

In the embodiment of the present disclosure, the server attributes of the servers of each node are different, and the current load bearing values of the M nodes are calculated by obtaining the server attributes of the servers of each node and performing statistics on the server attributes of each node.

In operation S603, the current load bearing value is compared with a set threshold.

After the current load bearing values of the M nodes are calculated in operation S602, the current load bearing values are compared with a set threshold, and subsequent operations are performed according to the comparison result.

In operation S604, if the load bearing value is greater than the set threshold, the data request from the user is rejected.

If the calculated load bearing value is greater than the set threshold, it indicates that the degradation of the current service type has not reached the stable and operable state of the system, and the degraded state needs to be maintained, and the data request from the user is rejected, that is, the degraded service type still maintains the degraded state.

In an alternative embodiment, there is an unexecuted queue in the destage request queue of the destage instruction, and at this time, the destage instruction in the unexecuted queue can be continuously executed, so as to further reduce the load bearing value.

In operation S605, if the load bearing value is not greater than the set threshold, a data request from the user is received, and the degradation status of the target server is set to be off.

If the calculated load bearing value is not greater than the set threshold value, it indicates that the degradation of the current service type has already realized the stable and operable state of the system, receives the data request from the user, and normally processes the data. And, the degraded state of the target server is set to off.

In the embodiment of the disclosure, after the load bearing value is greater than the set threshold and the data request from the user is rejected, the method further includes counting the rejected times of the data request, and generating a priority degradation policy according to the rejected times.

Counting the rejected times of the data request from the user can indicate the unimportance degree of the data request according to the rejected times, for example, the more the rejected times, the less important the service type is, when performing the degradation, the preferential degradation strategy can be generated according to the rejected times, thereby improving the efficiency.

In embodiments of the present disclosure, downgrading a service type includes rejecting some or all data requests from a user, shutting down a failed service, delaying feedback or suspending use of data requests from a user for non-critical service types, and the like.

The degradation may be performed in the following manner. For example, part of the user experience is sacrificed. The specific method can be that the commodity page does not display the special service icon and the promotion information; the checkout page does not display the self-service/311/411 appointment calendar; the order detail page does not display GIS order tracks or invoices and the like; page turning after 10 pages is prohibited by the evaluation list; real-time statistics and report form forbidding; enforcing the routing or index fields in the mandatory query conditions; the brushing prevention degradation of the soybean collar beans is verified as jigsaw puzzle verification; h5 change PC page; general content is used instead of the personalized recommended content. As another example, the security level is lowered. The method specifically comprises the steps of submitting an order or making a comment or logging in without calling a wind control interface; the front end of the settlement page places an order without starting a verification code; the centralized session is unavailable, and the cookie is decrypted; ip limit service, registration and login are not limited in times; and the commodity modification content is not subjected to sensitive word filtering. As another example, portions of the business logic are sacrificed. The number of the beans is not checked during auction bidding; the evaluation is published, and whether to return goods or not is not checked. For another example, the task processing is delayed, specifically, the task processing may be a WMS task processing engine, a task such as pause, call, energy saving subsidy, or the like; OFW handles high priority, orders with simpler splitting logic, and the like, in preference. For another example, the loss of data persistence may specifically be user address update, write redis, not write back to the database; stock pre-occupation, redis writing and asynchronous data writing back to a database; the user adds a new common ticket and writes redis, which is not lasting; the order secondary split task mechanism is reduced from JMQ to a redis queue and the like. For another example, accuracy/real-time performance is reduced, and particularly, real-time price is overdue and is not returned; changing the dynamic page into a static drag page; degrading a nickname interface of the user and displaying a pin of the user; the stock state interface is degraded to display the goods; draw is abnormal and all users show a loser. For another example, the performance is reduced, specifically, the database replaces cache to prevent duplication and query; database task queue polling replaces MQ; the CDN is dropped to the source station; the local cache is reduced to RPC. For another example, the disaster tolerance capability is reduced, specifically, automatic scheduling is changed into manual scheduling; VIP demotes to real ip, etc.

Fig. 7 schematically illustrates a block diagram of a service downgrading apparatus, according to an embodiment of the present disclosure.

As shown in fig. 7, the service degradation apparatus 700 of this embodiment includes an obtaining module 710, an analyzing module 720, a processing module 730, and a degrading module 740.

An obtaining module 710 configured to obtain service types of M nodes of a distributed server, where a service type has N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers greater than 1. The obtaining module 710 may be configured to perform the operation S201 described above, and is not described herein again.

The analysis module 720 is configured to analyze the service type and the service attribute by a hierarchical analysis method, and obtain a first weight ranking of the service type. The analysis module 720 may be configured to perform the operation S202 described above, which is not described herein again.

The processing module 730 is configured to obtain a rated load threshold of the data request of the distributed server, compare the current load threshold with the rated load threshold, and start service degradation when the current load threshold is greater than the rated load threshold. The processing module 730 can be configured to perform the operation S203 described above, which is not described herein again.

A downgrading module 740 configured to downgrade, according to the first weighted ranking, a server of the node corresponding to the service type to reject the data request received in the current time period. The downgrade module 740 may be configured to perform the operation S204 described above, and will not be described herein.

In an embodiment of the present disclosure, the analysis module includes an analysis submodule configured to establish a hierarchical analysis model, the hierarchical analysis model includes a highest layer, an intermediate layer, and a lowest layer, the intermediate layer includes service attributes, and the lowest layer includes service types; establishing comparison matrixes and level single sequencing of the lowest layer and the middle layer, and carrying out consistency check on the comparison matrixes; a hierarchical total ordering is constructed and a consistency check is performed to generate a first weighted ordering of service types.

In an embodiment of the present disclosure, the demotion module includes a demotion submodule configured to generate demotion instructions according to the first weight ranking; receiving a degradation instruction, and checking whether the degradation state of a target server to be degraded is started or not; if the degradation state of the target server is started, rejecting a degradation instruction; and if the degradation state of the target server is closed, receiving a degradation instruction and degrading the target server.

In the embodiment of the disclosure, the degradation submodule further includes a statistical module, the statistical module is configured to receive a degradation instruction, the target server executes the degradation instruction, and counts a degradation start time and a current time interval of the target server; if the time interval is smaller than the set interval, rejecting the data request from the user; and if the time interval is not less than the set interval, sending the time interval to a control center.

In an embodiment of the present disclosure, the service degradation apparatus further includes a comparison module, where the comparison module is configured to obtain server attributes of the servers of the M nodes after sending the time interval to the control center; calculating the current load bearing values of the M nodes according to the server attribute; comparing the current load bearing value with a set threshold value, and if the load bearing value is larger than the set threshold value, rejecting a data request from a user; and if the load bearing value is not greater than the set threshold value, receiving a data request from a user, and setting the degradation state of the target server to be closed.

Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

For example, any number of the obtaining module 710, the analyzing module 720, the processing module 730, and the degrading module 740, the analyzing sub-module, the degrading sub-module, the counting module, and the comparing module may be combined and implemented in one module, or any one of the modules may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the disclosure, at least one of the obtaining module 710, the analyzing module 720, the processing module 730, the degrading module 740, the analyzing submodule, the degrading submodule, the counting module, and the comparing module may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware, and firmware, or an appropriate combination of any several of them. Alternatively, at least one of the obtaining module 710, the analyzing module 720, the processing module 730 and the degrading module 740, the analyzing sub-module, the degrading sub-module, the counting module and the comparing module may be at least partially implemented as a computer program module, which when executed, may perform the corresponding functions.

Fig. 8 schematically illustrates a block diagram of an electronic device adapted to implement the service downgrading method described above, according to an embodiment of the present disclosure. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 8, an electronic device 800 according to an embodiment of the present disclosure includes a processor 801 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. The processor 801 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flows according to embodiments of the present disclosure.

In the RAM 803, various programs and data necessary for the operation of the electronic apparatus 800 are stored. The processor 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. The processor 801 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or RAM 803. Note that the programs may also be stored in one or more memories other than the ROM 802 and RAM 803. The processor 801 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.

Electronic device 800 may also include input/output (I/O) interface 805, input/output (I/O) interface 805 also connected to bus 804, according to an embodiment of the present disclosure. Electronic device 800 may also include one or more of the following components connected to I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a signal such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: 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), 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. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 802 and/or RAM 803 described above and/or one or more memories other than the ROM 802 and RAM 803.

Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product is run on an electronic device, the program code being adapted to cause the electronic device to carry out the method of service downgrading provided by the embodiments of the present disclosure.

The computer program, when executed by the processor 801, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted in the form of a signal on a network medium, distributed, downloaded and installed via communication section 809, and/or installed from removable media 811. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., 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 or flowchart illustration, and combinations of blocks in the block diagrams 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.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. A service degradation method for a distributed server comprises the following steps:

acquiring service types of M nodes of a distributed server, wherein the service types have N service attributes, the N service attributes of each service type have different weights, and M and N are positive integers greater than 1;

analyzing the service types and the service attributes by a hierarchical analysis method to obtain a first weight sequence of the service types;

obtaining a rated load threshold of a data request of the distributed server, comparing the current load threshold with the rated load threshold, and starting service degradation when the current load threshold is larger than the rated load threshold;

and degrading the server of the node corresponding to the service type according to the first weighted ranking order so as to reject the data request received in the current time period.

2. The service degradation method according to claim 1, wherein the analyzing the service types and the service attributes by a hierarchical analysis method, and obtaining the first weighted ranking of the service types comprises:

establishing a hierarchical analysis model, wherein the hierarchical analysis model comprises a highest layer, a middle layer and a lowest layer, the middle layer comprises the service attribute, and the lowest layer comprises the service type;

establishing a comparison matrix and a level single sequence of the lowest layer and the middle layer, and carrying out consistency check on the comparison matrix;

a hierarchical total ordering is constructed and a consistency check is performed to generate a first weighted ordering of the service types.

3. The service degradation method of claim 1, wherein the degrading of the server of the node corresponding to the service type according to the first weighted ordering comprises:

generating a downgrade instruction according to the first weight ranking;

receiving the degradation instruction, and checking whether the degradation state of the target server to be degraded is started;

if the degradation state of the target server is started, rejecting the degradation instruction;

and if the degradation state of the target server is closed, receiving the degradation instruction and degrading the target server.

4. The service degradation method of claim 3, wherein the receiving the degradation instruction to degrade the target server comprises:

receiving the degradation instruction, executing the degradation instruction by the target server, and counting the degradation starting time and the current time interval of the target server;

if the time interval is smaller than the set interval, rejecting the data request from the user;

and if the time interval is not less than the set interval, sending the time interval to a control center.

5. The service degradation method of claim 4, wherein after sending the time interval to a control center, the service degradation method further comprises:

obtaining server attributes of the servers of the M nodes;

calculating the current load bearing values of the M nodes according to the server attribute;

comparing the current load bearing value with a set threshold value,

if the load bearing value is larger than the set threshold value, rejecting a data request from a user;

and if the load bearing value is not greater than the set threshold value, receiving a data request from a user, and setting the degradation state of the target server to be closed.

6. The service degradation method according to claim 5, wherein after the load bearing value is greater than the set threshold and the data request from the user is rejected, the method further comprises counting the number of times that the data request is rejected, and generating a priority degradation policy according to the number of times that the data request is rejected.

7. The service degradation method according to claim 5, wherein the server attributes include CPU usage, storage usage, memory usage.

8. The service degradation method of claim 1, wherein the service attributes comprise: two or more of a critical path degree level, a current user number, a network transmission data amount, a configuration current limiting level, a service use frequency, and a service security level.

9. A service degradation apparatus of a distributed server, comprising:

the system comprises an acquisition module, a service module and a service module, wherein the acquisition module is configured to acquire service types of M nodes of a distributed server, the service types are provided with N service attributes, the N service attributes of each service type are provided with different weights, and M and N are positive integers larger than 1;

the analysis module is configured to analyze the service types and the service attributes through a hierarchical analysis method to obtain a first weight sequence of the service types;

the processing module is configured to obtain a rated load threshold of a data request of the distributed server, compare the current load threshold with the rated load threshold, and start service degradation when the current load threshold is larger than the rated load threshold;

and the degradation module is configured to degrade the server of the node corresponding to the service type according to the first weighted ranking so as to reject the data request received in the current time period.

10. An electronic device, comprising:

one or more processors;

storage means for storing executable instructions that, when executed by the processor, implement the service downgrading method of any of claims 1 to 8.

11. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, implement the service downgrading method of any of claims 1 to 8.

12. A computer program product comprising a computer program which, when executed by a processor, implements a service downgrading method according to any one of claims 1 to 8.