CN114006907B - Distributed server service degradation method, device, electronic device and medium - Google Patents
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
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- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
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- H—ELECTRICITY
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
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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 steps of obtaining service types of M nodes of a distributed server, wherein the service types are provided with N service attributes, N service attributes of each service type are provided with different weights, M and N are positive integers which are larger than 1, analyzing the service types and the service attributes through 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 size of the current load threshold with the size of the rated load threshold, 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 weight sequence to reject the data request received in the current time period.
Description
Technical Field
The present disclosure relates to the field of internet technologies, and more particularly, to a service degradation method and apparatus for a distributed server, an electronic device, and a computer readable storage medium.
Background
With the development of information technology, the amount of information data that a server needs to process is increasing. Under the condition of the rapid increase of the server pressure, according to the actual service condition and the flow, some services and pages are processed in a strategic way without processing or in a simple way, so that the server resources are released to ensure the normal operation or the efficient operation of the core transaction. In the related art, a distributed switch is arranged in a distributed system to realize service degradation, and in the degradation process, servers are different along with the processed service types, and effective degradation means cannot be adopted for different service types due to different load pressures of the servers corresponding to the different service types. Particularly in large promotion or second killing activities, the load pressure of the server increases dramatically, and the server is easily paralyzed when the server cannot be degraded according to the service type, so that the user experience is reduced.
Disclosure of Invention
In view of the above, the present disclosure provides a service degradation method, apparatus, electronic device and computer readable storage medium for a distributed server, 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 high.
A first aspect of the disclosure provides a service degradation method of a distributed server, which includes obtaining service types of M nodes of the distributed server, wherein the service types have N service attributes, N service attributes of each service type have different weights, M and N are positive integers larger than 1, analyzing the service types and the service attributes through an analytic hierarchy process to obtain a first weight ranking of the service types, obtaining a rated load threshold of a data request of the distributed server, comparing the rated load threshold with the rated load threshold, 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 weight ranking to reject the data request received in the current time period.
In some embodiments of the disclosure, the analyzing the service type and the service attribute by a hierarchical analysis method to obtain a first weight ranking of the service type includes establishing a hierarchical analysis model, the hierarchical analysis model including a highest layer, a middle layer, and a lowest layer, the middle layer including the service attribute, the lowest layer including the service type, establishing a comparison matrix and a hierarchical single ranking of the lowest layer and the middle layer, and performing a consistency check on the comparison matrix, establishing a hierarchical total ranking, and performing a consistency check to generate the first weight ranking of the service type.
In some embodiments of the disclosure, the downgrading the server of the node corresponding to the service type according to the first weight ranking includes generating a downgrade instruction according to the first weight ranking, receiving the downgrade instruction, checking whether a downgrade state of a target server to be downgraded is on or not, rejecting the downgrade instruction if the downgrade state of the target server is on, and downgrading the target server if the downgrade state of the target server is off, wherein the downgrade instruction is received.
In some embodiments of the disclosure, the receiving the degradation instruction and degrading the target server includes receiving the degradation instruction, executing the degradation instruction by the target server, counting a degradation start time and a current time interval of the target server, rejecting a data request from a user if the time interval is less than a set interval, and transmitting the time interval to a control center if the time interval is not less than the set interval.
In some embodiments of the present disclosure, after the time interval is sent to the control center, the service degradation method further includes obtaining server attributes of servers of the M nodes, calculating current load bearing values of the M nodes according to the server attributes, comparing the current load bearing values with a set threshold, rejecting data requests from users if the load bearing values are greater than the set threshold, receiving data requests from users if the load bearing values are not greater than the set threshold, and setting a degradation state of the target server to be closed.
In some embodiments of the present disclosure, after rejecting the data request from the user, if the load bearing value is greater than the set threshold, further comprising counting a number of rejects of the data request, generating a priority degradation policy according to the number of rejects.
In some embodiments of the present disclosure, the server attributes include CPU usage, storage usage, memory usage.
In some embodiments of the present disclosure, the service attributes include two or more of a critical path level, a current number of users, a network transmission data amount, a configuration flow limit level, a service usage frequency, and a service security level.
A second aspect of the disclosed embodiments provides a service degradation device of a distributed server, which includes an acquisition module configured to acquire service types of M nodes of the distributed server, wherein the service types have N service attributes, N service attributes of each service type have different weights, M and N are positive integers greater than 1, an analysis module configured to analyze the service types and the service attributes through a hierarchical analysis method to acquire a first weight ranking of the service types, and a processing module configured to acquire a rated load threshold of a data request of the distributed server, compare the size of the rated load threshold with the size of the rated load threshold, and start service degradation when the current load threshold is greater than the rated load threshold, and a degradation module configured to degrade the server of the node corresponding to the service type according to the first weight ranking so as to reject the data request received in the current time period.
In some embodiments of the present disclosure, the analysis module includes an analysis submodule configured to establish a hierarchical analysis model including a highest tier, a middle tier, and a lowest tier, the middle tier including the service attribute, the lowest tier including the service type, construct a comparison matrix and a hierarchical single rank of the lowest tier and the middle tier, and perform a consistency check on the comparison matrix, construct a hierarchical total rank, and perform a consistency check to generate a first weight rank of the service type.
In some embodiments of the present disclosure, the destaging module includes a destaging sub-module configured to generate a destaging instruction according to the first weight ordering, receive the destaging instruction, check whether a destaging state of a target server to be destaged is on, reject the destaging instruction if the destaging state of the target server is on, and destage the target server if the destaging state of the target server is off.
In some embodiments of the disclosure, the downgrade sub-module further includes a statistics module configured to receive the downgrade instruction, the target server executes the downgrade instruction, count a downgrade start time and a current time interval of the target server, reject a data request from a user if the time interval is less than a set interval, and send the time interval to a control center if the time interval is not less than the set interval.
In some embodiments of the disclosure, the service degradation device further includes a comparison module configured to obtain server attributes of servers of the M nodes after the time interval is sent to a control center, calculate current load bearing values of the M nodes according to the server attributes, compare the current load bearing values with a set threshold, reject data requests from users if the load bearing values are greater than the set threshold, and receive data requests from users if the load bearing values are not greater than the set threshold, and set a degradation state of the target server to be off.
A third aspect of the disclosed embodiments provides an electronic device comprising one or more processors, storage means for storing executable instructions which, when executed by the processors, implement a service degradation method according to the above.
A fourth aspect of the disclosed embodiments provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, implement a service degradation method according to the above.
A fifth aspect of the disclosed embodiments provides a computer program product comprising a computer program which, when executed by a processor, implements a service degradation method according to the above.
According to the service degradation method disclosed by the embodiment of the invention, the first weight sequence of the service types of different nodes can be obtained by adopting the hierarchical analysis method, and the degradation of the servers of the nodes is performed according to the first weight sequence, so that the priority degradation of unimportant services is ensured under the condition of higher load pressure in the current time period, and the user experience is improved.
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The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof 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 chart of a service degradation method according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates a flow chart of a first weight ordering of acquisition service types for a service degradation method according to an embodiment of the disclosure;
FIG. 4 schematically illustrates a flow diagram of downgrading a node server according to a service downgrading method of an embodiment of the disclosure;
FIG. 5 schematically illustrates a flow diagram of downgrading a target server according to a service downgrading method of an embodiment of the disclosure;
fig. 6 schematically illustrates a flow chart of a service degradation method after sending a time interval to a control center according to an embodiment of the present disclosure;
Fig. 7 schematically illustrates a block diagram of a service degradation 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 degradation 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 only exemplary 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 present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to 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/or 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 should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a convention should be interpreted in accordance with the meaning of one of skill in the art having generally understood the convention (e.g., "a system having at least one of A, B and C" would include, but not be limited to, systems having 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 should also be appreciated by those skilled in the art that virtually any disjunctive word and/or phrase presenting two or more alternative items, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the items, either of the items, or both. 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 of a distributed server, which comprises the steps of obtaining service types of M nodes of the distributed server, wherein the service types are provided with N service attributes, N service attributes of each service type are provided with different weights, M and N are positive integers larger than 1, analyzing the service types and the service attributes through an analytic hierarchy process 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 size of the rated load threshold with the size of the current 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 types according to the first weight sequence to reject the data request received in the current time period.
According to the embodiment of the disclosure, the first weight ordering of the service types of different nodes can be obtained by adopting the analytic hierarchy process, and the server of the node is degraded according to the first weight ordering, so that unimportant service is preferentially degraded under the condition of higher 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 illustrates 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 it 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, apparatus, electronic device and computer readable storage medium of the distributed server provided by the embodiments of the present disclosure may be used in the related aspects of the internet technical field, the big data technical field and the financial field, and may also be used in other fields other than the financial field, and the service degradation method, apparatus, electronic device and storage medium provided by the embodiments of the present disclosure do not limit the application 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 a medium used to provide 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. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the control center 105 through the network 104 using the terminal devices 101, 102, 103 to receive or transmit messages or the like, and the control center 105 transmits messages or requests or the like transmitted 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 or the like returned from the distributed servers 106, 107, 108. Various client applications, such as an input method application, a shopping class application, a web browser application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc. (which are examples only), 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 via 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, 103 may be various electronic devices supporting information acquisition and information transmission, where the information acquisition includes web browsing, voice broadcasting, and other modes, and the control center 105 may send information allocation to the distributed servers 106, 107, 108 to acquire or call the information, and finally return the information to the terminal devices, where the information is displayed by an information display device of the terminal devices, for example, a display screen may display pictures or characters, or may display information by voice broadcasting, and other modes. Among other things, electronic devices include, but are not limited to, smart speakers, smart phones, smart televisions, smart bracelets, tablet computers, laptop and desktop computers, and the like.
The distributed servers 106, 107, 108 may be servers providing various services, such as a background management server (by way of example only) that provides support for WEB sites that users utilize instructions or fetched information sent by the terminal devices 101, 102, 103 or browsed, or WEB servers, FTP servers, enterprise core application servers, and other primary task servers, etc. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., a web page, information, or data acquired or generated according to the voice command of the user or the user request) to the terminal device. The distributed servers 106, 107, 108 are used to complete work tasks in conjunction with the control center 105.
It should be noted that the service degradation method provided by the embodiments of the present disclosure may be generally performed by the control center 105. Accordingly, the service degradation apparatus provided by the embodiments of the present disclosure may be generally provided in the server 105. In alternative embodiments, the service degradation methods provided by embodiments of the present disclosure may be performed generally by distributed servers 106, 107, 108 in conjunction with control center 105. Accordingly, the service degradation devices provided by 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 are merely illustrative. There may be any number of terminal devices, networks and control centers, and distributed servers, as desired for implementation.
Fig. 2 schematically illustrates a flow chart of a service degradation method according to an embodiment of the present disclosure.
The service degradation method of 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 the distributed server are acquired, 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. For example, M has a value of 2, 3 or 4, N has a value of 3,4 or 5, etc.
According to embodiments of the present disclosure, the distributed servers may be, for example, servers deployed in different locations, which may be used to process different traffic. Servers handling the same kind of traffic have one node or may have multiple nodes. Nodes that handle the same kind of traffic have a service type, i.e. their corresponding traffic class. Each service type has a plurality of service attributes including, for example, two or more of a critical path degree level, a current number of users, a network transmission data amount, a configuration flow restriction level, a service usage frequency, and a service security level.
In an embodiment of the present disclosure, the N service attributes for each service type have different weights. For example, service types include login service, query user information service, payment service, and the like. For login service, the service attributes included are critical path degree level, current user number, network transmission data amount, configuration flow limit level, service use frequency and service security level. And, each service attribute included therein has a different weight corresponding to the login service, for example, the key path degree level, the current number of users, etc. in the login service and the query user information service are different.
In operation S202, the service type and the service attribute are analyzed by a hierarchical analysis method, and a first weight ranking of the service type is obtained. Operation S202 is described in detail below with reference to fig. 3.
Fig. 3 schematically illustrates a flow chart of a first weight ordering of acquisition service types for a service degradation method according to an embodiment of the disclosure.
As shown in fig. 3, in an embodiment of the present disclosure, a process 300 of obtaining a first weight ranking of service types by analyzing service types and service attributes through a hierarchical analysis method (THE ANALYTIC HIERARCHY process, abbreviated as AHP) includes operations S301 to S303.
In operation S301, a hierarchical analysis model is established, the hierarchical analysis model including a highest layer, a middle layer, and a lowest layer, the middle layer including service attributes, the lowest layer including service types.
In the embodiment of the present disclosure, the highest layer is the problem to be solved, and in the embodiment, the highest layer is the first weight ranking of the service types. The middle layer comprises service attributes, namely, factors to be considered in acquiring the first weight sequence of the service types, and analysis is performed according to the difference of the service attributes of each service type. The lowest layer includes the service types, i.e. the service types that need to be downgraded.
In operation S302, a comparison matrix and a hierarchical order of the lowest layer and the middle layer are constructed, and consistency check is performed on the comparison matrix.
In an embodiment of the present disclosure, a pair-wise comparison matrix is a comparison that represents the relative importance of all factors of the layer to a certain factor of the previous layer. The comparison result of the ith factor relative to the jth factor, represented by element a ij of the pair-wise comparison matrix, is given using the 1-9 scale method of table-1 below. For example, all factors of the layer may be service types, and a certain factor of the upper layer may be service attributes.
TABLE-1
Starting from layer 2 of the analytic hierarchy model, a pair comparison matrix is constructed for a plurality of factors subordinate to the same layer as each factor of the previous layer, up to the lowest layer.
For example, a pair comparison matrix a is constructed based on a plurality of service attributes including a critical path degree class (a 1), a current user number (a 2), a network transmission data amount (a 3), a configuration flow restriction class (a 4), a service usage frequency (a 5), and a service security level (a 6) and the finally selected service type importance degree. The constructed paired comparison matrix A is
After the paired comparison matrix A is constructed, calculating hierarchical single-order (single-layer weight vector) and carrying out consistency test on the comparison matrix A to determine the allowable range of inconsistency of the comparison matrix A.
Specifically, the feature weight vector of the pair comparison matrix A is calculated, and if the pair comparison matrix A is a uniform matrix, the normalized feature weight vector of the corresponding maximum feature root is taken. If the first contrast matrix is not the uniform matrix, the normalized feature vector corresponding to the maximum feature root is used as the weight vector, namely, the feature root method is used for determining the weight vector.
For example, if the maximum eigenvalue λ=6.35 of a is calculated, the eigenvector of the response is determined to be W (2)＝(0.16,0.19,0.19,0.05,0.12,0.30)T.
The step of consistency test for the comparison matrix A is as follows:
First, a consistency index ci= (λ -n)/(n-1) is constructed, where n is the order representing the comparison matrix and λ represents the maximum eigenvalue of the comparison matrix. When ci=0, it means that the constructed pair-wise comparison matrix has consistency with respect to the comparison matrix a. When CI is close to 0, this indicates satisfactory consistency in the construction of the pair wise comparison matrix. The larger the CI, the more serious the build-up of pairwise comparison matrix inconsistencies. There may be differences in judging the consistency of the comparison matrix, but not so much. That is, if the consistency index is within the set range, the comparison matrix A passes the consistency test, otherwise, the comparison matrix A does not pass the consistency test, and the comparison matrix needs to be reconstructed.
For example, the consistency index ci= (6.35-6)/(6-1) =0.07 of the comparison matrix a is calculated.
Next, a random uniformity index RI is acquired. 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 uniformity index is found by look-up table to be ri=1.24.
Next, the coincidence ratio CR is calculated from the values of RI and CI. Specifically, the consistency ratio cr=ci/RI, and when the consistency ratio CR < x, the degree of inconsistency of the pair of comparison matrices a is considered to be within the allowable range, with satisfactory consistency, that is, the pair of comparison matrices a is considered to pass the consistency test. Where x is a set value that can be adjusted for different scenarios. If the consistency ratio CR is equal to or greater than x, the comparison matrix A is considered to pass the consistency test, and the pair comparison matrix A is reconstructed. For example, cr=0.07/1.24=0.0565 <0.1, then the pair wise comparison matrix a is indicated to pass the consistency check.
In an embodiment of the present disclosure, as described above, the pairwise comparison matrix for the login service, the payment service, the query user information service with respect to 6 service attributes is:
The pair comparison matrix B n (n=1, 2,3,4,5, 6) was subjected to the consistency test in the same manner as described above, and it was determined that the pair comparison matrix B n passed the consistency test.
According to the pair comparison matrix, the calculated maximum eigenvalue and corresponding eigenvector 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 total ordering is constructed and a consistency check is performed to generate a first weight ordering of service types.
And calculating weight vectors of all factors of the lower layers for the relative importance of the highest layer. And the consistency check is used for checking, if the consistency check passes, a decision can be made according to the result represented by the total sorting weight vector, otherwise, the model is needed to be reconsidered or a pair of comparison matrixes with larger consistency ratio CR is needed to be reconstructed.
For example, the feature weight vector w=w (3)×W(2）, i.e
Thus, the first weight ranking that determines the service type is:
login service > Payment service > query user information service
That is, in the first weight ranking of the acquired service types, the weight of the login service is larger than that of the payment service and that of the query user information service. The downgraded services may be performed according to a first ranking of the respective service types. For example, if the weight of the query user information service is minimum, the query user information service may be degraded preferentially, i.e., turned off.
In operation S203, a rated load threshold of the data request of the distributed server is obtained, the sizes of the current load threshold and the rated load threshold are compared, and when the current load threshold is greater than the rated load threshold, service degradation is started.
In an embodiment of the present disclosure, the data request of the distributed server is a data request from a user, and the entire distributed server system has a rated load threshold. During actual operation, data requests from users received by the system during a current or future time will increase dramatically, resulting in exceeding the rated load threshold of the system, due to activities like promotions or killing for seconds. Therefore, when the current load threshold of the system is greater than the rated load threshold of the system, the server of the system needs to be degraded to relieve the processing pressure of the server.
In operation S204, the server of the node corresponding to the service type is downgraded according to the first weight ranking to reject the data request received in the current time period.
In an embodiment of the present disclosure, after receiving an instruction for service degradation, a control center needs to degrade a server of a node corresponding to a service type according to a first weight ranking. For example, as described above, the service type of the first weight ranking is ranked as login service > payment service > and the querying user information service, that is, the first weight of the querying user information service is the smallest, so the downgrade instruction may be set to preferentially downgrade the server of the node corresponding to the querying user information service, so as to reject the data request received in the current time period. For example, data requests received during the current time period for querying the user information service are rejected, while no degradation is performed for login service data requests, payment service data requests.
In an alternative embodiment of the present disclosure, the service degradation instruction may include an instruction for degrading a plurality of services, for example, an instruction generated according to the first weight ranking and including service degradation for a payment service and a service for querying user information. And in the service degradation process, preferentially carrying out service degradation on the information service of the inquiring user, and continuing to carry out service degradation on the payment service under the condition that the current load threshold of the system is still larger than the rated load threshold until the current load threshold is smaller than or equal to the rated load threshold.
In this embodiment, the service type is exemplified by a login service, a payment service, and a service for inquiring user information, and in other alternative embodiments, the service type may be a greater number of services or other service types except for examples, and the type and number of the service types are not limited in this disclosure.
According to the service degradation method disclosed by the embodiment of the invention, the first weight sequence of the service types of different nodes can be obtained by adopting the hierarchical analysis method, and the degradation of the servers of the nodes is performed according to the first weight sequence, so that the priority degradation of unimportant services is ensured under the condition of higher load pressure in the current time period, and the user experience is improved.
Fig. 4 schematically illustrates a flow chart of downgrading a node server according to a service downgrading method of an embodiment of the disclosure.
In an embodiment of the present disclosure, the downgrading process 400 for a server of a node corresponding to a service type according to a first weight ranking includes operations S401 to S404.
In operation S401, a demotion instruction is generated according to a first weight ranking.
In an embodiment of the present disclosure, when the downgrade instruction is generated according to the first weight ordering, the downgrade instruction includes at least one downgrade request of a corresponding service type. The destaging instruction comprises a destaging request queue, the destaging request queue in the destaging instruction is generated according to a first weight sequence, for example, in the first weight sequence, the service type with small weight can be a front column arranged in the destaging request queue, destaging is carried out preferentially, and the service type with unimportant priority destaging is indicated. The service type with the large weight can be arranged at the later column of the degradation request queue, and the service type with the relatively important service type is degraded in the degradation process, so that the use experience of the user is ensured.
The destage request queue included in the destage instruction, when issued by the control center to the server of the node, may select one destage request or multiple destage requests in the destage request queue, which is adjusted according to the actual demand and the difference between the current load threshold and the rated load threshold of the system.
In operation S402, a demotion instruction is received, and it is checked whether a demotion state of a target server to be demoted is on.
In the embodiment of the disclosure, one or more servers to be demoted are included in a demotion request queue in the demotion instruction, after receiving the demotion instruction, the control center issues the demotion instruction to a target server to be demoted, and checks the demotion state of the target server, so that whether to execute the demotion instruction is determined according to the current state of the target server.
In operation S403, if the degraded state of the target server is on, the degraded instruction is rejected.
The degradation state of the target server is opened, which indicates that the target server has been degraded, and no degradation is needed, and at this time, the degradation instruction of the control center is rejected.
In operation S404, if the degradation status of the target server is closed, a degradation instruction is received to degrade the target server.
And if the degradation state of the target server is closed, the target server is indicated to be capable of degrading, a degradation instruction is received, and the target server is degraded, so that the current load pressure of the system is relieved.
Fig. 5 schematically illustrates a flowchart of downgrading a target server according to a service downgrading method of an embodiment of the present disclosure.
As shown in fig. 5, after receiving the destaging instruction, a flow 500 of destaging the target server includes operations S501 to S504.
In operation S501, a degradation instruction is received, and the target server executes the degradation instruction, counting a degradation start time of the target server and a current time interval.
And after the target server receives the degradation instruction, executing the degradation instruction, recording the degradation starting time of the target server after the target server starts to degrade, and simultaneously calculating the duration after the target server is degraded along with the start of the degradation of the target server, namely counting the degradation starting time and the current time interval of the target server. So that the target server is subsequently controlled according to the counted time intervals.
In operation S502, the time interval counted in operation S501 is compared with the size of 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 embodiment of the present disclosure, the setting interval is adjusted according to actual requirements, for example, the setting interval is 10s. In other alternative embodiments, the set interval may be other lengths of time.
In the embodiment of the disclosure, by setting the set interval of server degradation, the server is ensured to be capable of reducing the current load threshold of the server after the degradation. That is, it is necessary to ensure that the server is in a degraded state for a certain period of time, rather than the downgraded stand being closed.
In operation S503, a data request from a user is denied.
The time interval being less than the set interval indicates that the server of the system has not degraded to a predetermined load threshold, and therefore in this case, when there is a data request from the user associated with that server type, the data request from the user is directly denied.
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 server of the system may or may not have degraded to the predetermined load threshold. The statistical time interval is thus sent to the control center, from which further control takes place.
Fig. 6 schematically illustrates a flow chart of a service degradation method after sending a time interval to a control center according to an embodiment of the present disclosure.
As shown in fig. 6, the flow 600 after transmitting the time interval 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, obtaining the server attributes of the M node servers. 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 running state of the whole system, for example, when the CPU usage, the storage usage, the memory usage, etc. are all at a higher value, this indicates that the load pressure of the server is higher, and if at a lower value, this 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 started or closed, and the adjustment of the servers is realized.
In operation S602, current load bearing values of M nodes are calculated according to server attributes.
In the embodiment of the disclosure, the server attribute of the server of each node is different, and the current load bearing values of the M nodes are calculated by acquiring the server attribute of the server of each node and counting the server attribute of each node.
In operation S603, the magnitude of the current load bearing value is compared with the set threshold value.
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 value, and a subsequent operation is performed according to the comparison result.
In operation S604, if the load bearing value is greater than the set threshold value, the data request from the user is denied.
And if the calculated load bearing value is larger than the set threshold value, the degradation of the current service type does not reach the stable and operable state of the system, the degraded state is required to be kept, and the data request from the user is refused, namely the service type which is degraded still keeps the degraded state.
In an alternative embodiment, there is an unexecuted queue in the demotion request queue of demotion instructions, at this time, execution of demotion instructions in the unexecuted queue may be continued, and the load bearing value is further reduced.
In operation S605, if the load bearing value is not greater than the set threshold, a data request from a user is received and the degraded state of the target server is set to be off.
And if the calculated load bearing value is not greater than the set threshold value, the degradation of the current service type is indicated to realize the stable and operable state of the system, the data request from the user is received, and the data processing is performed normally. And, the degraded state of the target server is set to off.
In an embodiment of the present disclosure, after rejecting the data request from the user, if the load bearing value is greater than the set threshold, the method further includes counting a number of rejected data requests, and generating a priority degradation policy according to the number of rejected data requests.
Counting the number of times the data request from the user is refused, the degree of unimportance of the data request can be indicated according to the number of times the data request is refused, for example, the more the number of times the data request is refused, the service type is relatively unimportant, and when the data request is downgraded, a priority downgrading strategy can be generated according to the number of times the data request is refused, so that the efficiency is improved.
In embodiments of the present disclosure, downgrading a service type includes rejecting some or all of the data requests from the user, shutting down the failed service, delaying feedback or suspending use of data requests from the user for unimportant service types, and the like.
Degradation may be performed as follows. For example, part of the user experience is sacrificed. The method comprises the steps of enabling commodity pages not to display special services icon and promotion information, enabling settlement pages not to display self-lifting/311/411 appointment calendars, enabling order detail pages not to display GIS order tracks or ordering and the like, enabling an evaluation list to inhibit page turning after 10 pages, enabling real-time statistics and report disabling, enabling forced necessary inquiry conditions to be subjected to routing or index fields, enabling beans to be prevented from being degraded to be subjected to jigsaw verification, enabling H5 to change into PC pages, and enabling universal content to replace personalized recommended content. As another example, the security level is reduced. The method comprises the steps of submitting orders, posting comments or logging in, not calling a wind control interface, enabling no verification code when the front end of a settlement page orders, enabling no centralized session, decrypting cookies, enabling an ip limit service, not limiting the number of times of registration and logging in, and not filtering sensitive words of commodity modification contents. As another example, part of the business logic is sacrificed. The method can be concretely used for checking the number of the Beijing beans when bidding in auction, publishing and evaluating, checking whether to return goods or not, and the like. For example, the task processing is suspended, and the tasks such as scheduling, energy-saving patch and the like are suspended by a WMS task processing engine, and the OFW is used for preferentially processing orders with high priority and simpler splitting logic and the like. For example, the data persistence can be lost, specifically, the data base is updated by the address of the user, the rediss are written and not written back, the stock is preempted, the rediss are written and written back asynchronously, the ticket is newly added by the user, the rediss are written and not durable, and the task mechanism of order secondary splitting is reduced to a rediss queue from JMQ. The method also comprises the steps of reducing accuracy/instantaneity, namely that the real-time price is out of date and cannot return to the source, changing the dynamic page into a static bottom page, degrading a user nickname interface, displaying user pins, degrading an inventory state interface, displaying goods, drawing a lottery, and displaying the fact that all users are not winning a prize. For another example, the performance is reduced, and the method can be concretely that a database replaces buffer memory to prevent heavy and inquiry, a database task queue polls to replace MQ, CDN is reduced to a source station, and local buffer memory is reduced to RPC. For example, the disaster recovery capability is reduced, and specifically, automatic scheduling is changed into manual scheduling, VIP is degraded into real ip, and the like.
Fig. 7 schematically illustrates a block diagram of a service degradation apparatus according to an embodiment of the present disclosure.
As shown in fig. 7, the service degradation apparatus 700 of this embodiment includes an acquisition module 710, an analysis module 720, a processing module 730, and a degradation module 740.
The acquiring module 710 is configured to acquire service types of M nodes of the distributed server, where the service types have N service attributes, and N service attributes of each service type have different weights, where M and N are positive integers greater than 1. The obtaining module 710 may be configured to perform the operation S201 described above, which is not described herein.
The analysis module 720 is configured to analyze the service type and the service attribute through 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.
And the processing module 730 is configured to obtain a rated load threshold value of the data request of the distributed server, compare the current load threshold value with the rated load threshold value, and start service degradation when the current load threshold value is greater than the rated load threshold value. The processing module 730 may be configured to perform the operation S203 described above, which is not described herein.
And a downgrade module 740 configured to downgrade the server of the node corresponding to the service type according to the first weight sequence, so as to reject the data request received in the current time period. The degradation module 740 may be configured to perform the operation S204 described above, which is not described herein.
In an embodiment of the disclosure, the analysis module includes an analysis submodule configured to establish a hierarchical analysis model, the hierarchical analysis model including a highest layer, a middle layer, and a lowest layer, the middle layer including service attributes, the lowest layer including service types, establish a comparison matrix and a hierarchical order of the lowest layer and the middle layer, and perform a consistency check on the comparison matrix, establish a hierarchical total order, and perform a consistency check to generate a first weight order of the service types.
In an embodiment of the disclosure, the downgrade module includes a downgrade sub-module configured to generate downgrade instructions according to a first weight ordering, to receive the downgrade instructions, to check whether a downgrade state of a target server to be downgraded is on, to reject the downgrade instructions if the downgrade state of the target server is on, and to receive the downgrade instructions if the downgrade state of the target server is off, to downgrade the target server.
In an embodiment of the disclosure, the degradation sub-module further includes a statistics module configured to receive the degradation instruction, the target server executes the degradation instruction, count a degradation start time of the target server and a current time interval, reject a data request from the user if the time interval is less than the set interval, and send the time interval to the control center if the time interval is not less than the set interval.
In an embodiment of the disclosure, the service degradation device further includes a comparison module configured to obtain server attributes of the servers of the M nodes after sending the time interval to the control center, calculate current load bearing values of the M nodes according to the server attributes, compare the current load bearing values with a set threshold, reject the data request from the user if the load bearing values are greater than the set threshold, receive the data request from the user if the load bearing values are not greater than the set threshold, and set a degradation state of the target server to be closed.
Any number of modules, sub-modules, units, sub-units, or at least some of the functionality of any number of the sub-units according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented as split into multiple 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-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in any other reasonable manner of hardware or firmware that integrates or encapsulates the circuit, or in any one of or a suitable combination of three of software, hardware, and firmware. Or one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be at least partially implemented as computer program modules, which, when executed, may perform the corresponding functions.
For example, any of the acquisition module 710, the analysis module 720, the processing module 730, and the degradation module 740, the analysis sub-module, the degradation sub-module, the statistics module, and the alignment module may be combined in one module to be implemented, or any one of the modules may be split into a plurality of modules. Or at least some of the functionality of one or more of the modules may be combined with, and implemented in, at least some of the functionality of other modules. According to embodiments of the present disclosure, at least one of the acquisition module 710, the analysis module 720, the processing module 730, and the degradation module 740, the analysis sub-module, the degradation sub-module, the statistics module, and the alignment module may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or as hardware or firmware in any other reasonable manner of integrating or packaging the circuitry, or as any one of or a suitable combination of any of the three implementations of software, hardware, and firmware. Or at least one of the acquisition module 710, the analysis module 720, the processing module 730, and the degradation module 740, the analysis sub-module, the degradation sub-module, the statistics module, and the alignment 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 degradation method described above, according to an embodiment of the present disclosure. The electronic device shown in fig. 8 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
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 an associated chipset and/or special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 801 may also include on-board memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the disclosure.
In the RAM 803, various programs and data required for the operation of the electronic device 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 flow according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or the RAM 803. Note that the program may be stored in one or more memories other than the ROM 802 and the RAM 803. The processor 801 may also perform various operations of the method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, the electronic device 800 may also include an input/output (I/O) interface 805, the input/output (I/O) interface 805 also being connected to the bus 804. The electronic device 800 may also include one or more of an input portion 806 including a keyboard, mouse, etc., an output portion 807 including a display such as a Cathode Ray Tube (CRT), liquid Crystal Display (LCD), etc., and speakers, etc., a storage portion 808 including a hard disk, etc., and a communication portion 809 including a network interface card such as a LAN card, modem, etc., connected to the I/O interface 805. The communication section 809 performs communication processing via a network such as the internet. The drive 810 is also connected to the I/O interface 805 as needed. 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 needed so that a computer program read out therefrom is mounted into the storage section 808 as needed.
The present disclosure also provides a computer-readable storage medium that may be included in the apparatus/device/system described in the above embodiments, or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present 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 context of this 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, the computer-readable storage medium may include ROM 802 and/or RAM 803 and/or one or more memories other than ROM 802 and RAM 803 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program comprising program code for performing the methods provided by the embodiments of the present disclosure, the program code for causing an electronic device to implement the service degradation methods provided by the embodiments of the present disclosure when the computer program product is run on the electronic device.
The above-described functions defined in the system/apparatus of the embodiments of the present disclosure are performed when the computer program is executed by the processor 801. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be based 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, distributed, and downloaded and installed in the form of a signal on a network medium, and/or from a removable medium 811 via a communication portion 809. The computer program may comprise program code that is transmitted using any appropriate network medium, including but not limited to wireless, wireline, etc., or any suitable combination of the preceding.
According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, 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., connected via the Internet using an Internet service provider).
The flowcharts 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 the features recited in the various embodiments of the disclosure and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. These examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (10)
1. A service degradation method of a distributed server, comprising:
Obtaining service types of M nodes of a distributed server, wherein the service types have N service attributes, N service attributes of each service type have different weights, M and N are positive integers larger than 1, and the service attributes comprise the number of current users, the network transmission data amount, the configuration current limit level, the service use frequency, the critical path degree level and the service security level;
Analyzing the service type and the service attribute through an analytic hierarchy process to obtain a first weight ranking of the service type;
Acquiring 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 weight sequence so as to reject the data request received in the current time period.
2. The service degradation method of claim 1, wherein the analyzing the service type and the service attribute by a hierarchical analysis method, obtaining a first weight ranking of the service type 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;
constructing a comparison matrix and a hierarchical order of the lowest layer and the middle layer, and carrying out consistency test on the comparison matrix;
And constructing a hierarchical total sequence, and performing consistency check to generate a first weight sequence of the service type.
3. The service degradation method of claim 1, wherein the degrading the server of the node corresponding to the service type according to the first weight ranking comprises:
generating a degradation instruction according to the first weight sequence;
Receiving the degradation instruction, and checking whether the degradation state of the target server to be degraded is started or not;
if the degradation state of the target server is opened, 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, degrading 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 smaller 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:
Acquiring server attributes of servers of the M nodes;
calculating current load bearing values of the M nodes according to the server attributes;
comparing the current load bearing value with a set threshold value,
If the load bearing value is larger than the set threshold value, rejecting the data request from the 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 of claim 5, wherein after rejecting a data request from a user after the load bearing value is greater than the set threshold, further comprising counting a number of rejections of the data request, generating a priority degradation policy based on the number of rejections.
7. The service degradation method of claim 5, wherein the server attributes include CPU usage, storage usage, memory usage.
8. A service degradation apparatus of a distributed server, comprising:
The acquisition module is configured to acquire service types of M nodes of the distributed server, wherein the service types have N service attributes, N service attributes of each service type have different weights, M and N are positive integers larger than 1, and the service attributes comprise the current user quantity, network transmission data quantity, configuration current limiting grade, service use frequency, critical path degree grade and service security grade;
The analysis module is configured to analyze the service type and the service attribute through a hierarchical analysis method and acquire a first weight sequence of the service type;
The processing module is configured to acquire 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 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 weight sequence so as to reject the data request received in the current time period.
9. An electronic device, comprising:
one or more processors;
storage means for storing executable instructions which when executed by the processor implement the service degradation method according to any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, implement the service degradation method according to any one of claims 1 to 7.
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| CN103580902A (en) * | 2012-08-07 | 2014-02-12 | 腾讯科技（深圳）有限公司 | Computer information system and dynamic disaster recovery method thereof |
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