Service deployment method and device, electronic equipment and storage medium

Abstract

The invention discloses a service deployment method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring a metadata set of at least one time node; wherein the metadata set comprises a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes in the N deployment nodes; dividing the path data set of at least one time point according to a division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents path data corresponding to at least one time node contained in a set time period; and according to the at least one path data combination set, the service data set and the node data set, determining deployment strategies of the S deployment services, thereby improving the efficiency and applicability of service deployment.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a service deployment method, device, electronic device and storage medium. Background Art

[0002] With the rapid development of information technology, especially its widespread application in cloud computing, big data, the Internet of Things and other fields, service deployment, as a key link connecting technology implementation and user needs, has become increasingly important.

[0003] At present, traditional service deployment methods often rely on a single server or server cluster when facing large-scale, high-concurrency service requests, resulting in uneven resource allocation. Some servers (also known as deployment nodes) have idle resources, while other servers have tight resources. In addition, during the deployment process, due to insufficient server resources, there will be problems such as constant restarts or freezes, which requires manual adjustment of which server the service is deployed on, and it is impossible to achieve self-correspondence between the deployment relationship between servers and services. Summary of the invention

[0004] The present application provides a service deployment method, device, electronic device and storage medium to improve the efficiency and applicability of service deployment.

[0005] In a first aspect, a service deployment method is provided, including:

[0006] Obtain a metadata set of at least one time node; wherein the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, where N is an integer greater than 1, and both M and S are integers greater than 0;

[0007] Divide the path data set of the at least one time point according to the division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents the path data corresponding to at least one time node included in the set time period;

[0008] Determine deployment strategies for the S deployment services based on the at least one path data combination set, the service data set, and the node data set.

[0009] In some embodiments, before obtaining the metadata set of at least one time point, the method further includes:

[0010] Constructing a node topology graph of the N deployment nodes, and generating a path data set of at least one time node based on the round-trip delay of all path data between the N deployment nodes at at least one time node in the node topology graph;

[0011] Determining the node data set according to resource utilization rates of each of the N deployment nodes;

[0012] The path data set of the at least one time node is respectively assembled with the node data set and the service data set to be deployed to obtain a metadata set of the at least one time node, and the metadata set of the at least one time node is cached in a monitoring pool.

[0013] In some embodiments, determining the deployment strategies of the S deployment services according to the at least one path data set, the service data set, and the node data set includes:

[0014] Normalizing the at least one path data combination set respectively, and calculating a stability coefficient of the at least one path data combination set after the processing;

[0015] determining a target path data set from the path data combination set according to the respective stability coefficients and the node data set;

[0016] Mapping the target path data set to the node topology map to determine at least one target deployment node;

[0017] Determine deployment strategies for the S services to be deployed according to the at least one target deployment node and the service data set.

[0018] In some embodiments, the stability coefficient satisfies the following expression:

[0019]

[0020] Among them, the δ i Characterizes the stability coefficient of the i-th path data combination set, the RTT j represents the round trip delay corresponding to the jth path data in the i-th path data combination set, the S RTT (avg) represents the normalized value of the i-th path data combination set.

[0021] In some embodiments, the determining the target path data set from the path data set according to the respective stability coefficients and the node data set comprises:

[0022] According to the respective stability coefficients, screening out a candidate path data combination set that meets a stability coefficient threshold from the at least one path data combination set;

[0023] According to the node data set, the M abnormal deployment nodes are removed from the candidate path data combination set to obtain the target path data set.

[0024] In some embodiments, after determining the deployment strategies of the S deployment services according to the path data set, the service data set, and the node data set, the method further includes:

[0025] Obtaining the current deployment paths of the S deployment services during operation, and comparing the deployment paths with the recorded historical deployment paths;

[0026] If the similarity between the deployment path and the historical deployment path meets the similarity requirement, maintaining the deployment nodes included in the deployment path to run the S deployment services;

[0027] If the similarity between the deployment path and the historical deployment path does not meet the similarity requirement, the S deployment services on the deployment nodes in the deployment path are migrated to the historical deployment path.

[0028] In an embodiment of the present application, a metadata set of at least one time node is obtained, and the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, so as to facilitate the subsequent selection of the optimal deployment node based on this, and avoid deploying the deployment service to the abnormal deployment node. The path data set of at least one time point is divided according to the division rule to obtain at least one path data combination set, and the at least one path data combination set represents the path data corresponding to at least one time node included in the set time period; according to the at least one path data combination set, the service data set, and the node data set, the deployment strategy of the S deployment services is determined, and a comprehensive analysis can be performed from the data sets of multiple dimensions to improve the efficiency and applicability of service deployment.

[0029] In a second aspect, a service deployment device is provided, including:

[0030] An acquisition module is used to acquire a metadata set of at least one time node; wherein the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, wherein N is an integer greater than 1, and both M and S are integers greater than 0;

[0031] A decomposition module, used to divide the path data set of the at least one time point according to a division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents the path data corresponding to at least one time node included in a set time period;

[0032] A deployment module is used to determine the deployment strategy of the S deployment services according to the at least one path data combination set, the service data set, and the node data set.

[0033] In some embodiments, the apparatus further comprises a metadata extraction module;

[0034] The metadata extraction module is used to construct a node topology map of the N deployment nodes, and generate a path data set of the at least one time node based on the round-trip delay of all path data between the N deployment nodes under at least one time node in the node topology map; determine the node data set according to the resource utilization rate of each of the N deployment nodes; assemble the path data set of the at least one time node with the node data set and the service data set to be deployed, respectively, to obtain the metadata set of the at least one time node, and cache the metadata set of the at least one time node to the monitoring pool.

[0035] According to a third aspect, an electronic device is provided, including:

[0036] A memory for storing a computer program; a processor for implementing any one of the methods described in the first aspect when executing the computer program stored in the memory.

[0037] According to a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to any one of the first aspects is implemented.

[0038] For each aspect from the second to the fourth aspect and the technical effects that may be achieved by each aspect, please refer to the above description of the technical effects that can be achieved by the first aspect or various possible schemes in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flow chart of a service deployment method provided in an embodiment of the present application;

[0040] Figure 2 A flowchart for extracting system metadata provided in an embodiment of the present application;

[0041] Figure 3 A logical diagram of service deployment provided for an embodiment of the present application;

[0042] Figure 4 A schematic diagram of the structure of a service deployment device provided in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0045] The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

[0046] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present application. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description. It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, which should be considered as exemplary, and their purpose is only to illustrate the feasibility of the implementation of the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0047] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are first explained below.

[0048] Round-trip time (RTT) refers to the time required for data to be transmitted from one end of the network to the other.

[0049] To further illustrate the technical solution provided by the embodiment of the present application, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiment of the present application provides the method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative labor. In the steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiment of the present application. The method may be executed or executed in parallel in the actual processing process or when the device is executed in accordance with the method sequence shown in the embodiment or drawings.

[0050] Figure 1 This is a flow chart of a service deployment method provided in an embodiment of the present application. The flow can be executed by a service deployment device, which can be implemented in software and / or hardware to improve the efficiency and applicability of service deployment. Figure 1 As shown, the process includes the following steps:

[0051] 101: Obtain a metadata set of at least one time point.

[0052] In this step, the metadata set includes path data sets of N deployment nodes, service data sets of S deployment services, and node data sets of M abnormal deployment nodes among the N deployment nodes, where N is an integer greater than 1, and M and S are both integers greater than 0.

[0053] In this step, the metadata set may be obtained periodically, for example, once every 2 minutes.

[0054] In some embodiments, before obtaining the metadata set of at least one time point, the path data of the deployment nodes, the abnormal conditions of the deployment nodes, and the service data of the deployment services at different time nodes can also be extracted in real time as the metadata set, so as to facilitate the subsequent service deployment analysis based on this. Specifically, Figure 2 As shown, a flowchart of extracting system metadata provided by an embodiment of the present application is exemplified.

[0055] 201: Construct a node topology graph of N deployment nodes, and generate a path data set of at least one time node based on round-trip delays of all path data between the N deployment nodes at at least one time node in the node topology graph.

[0056] In some embodiments, constructing a node topology graph of the N deployment nodes may include the following process:

[0057] The N deployment nodes are abstracted and constructed into a two-dimensional graph. For example, a data structure (such as a dictionary or a class) is used to represent each deployment node, which may include the ID, location, status and other attributes of the deployment node, and a node list or set is created to store the N deployment nodes. Then, another data structure (such as a dictionary or an adjacency list) is used to represent the links between the deployment nodes. For each link, information such as the starting point, the end point and the RTT may be stored. Then, according to the node list and the links between the deployment nodes, a graph data structure is constructed (for example, a graph theory library (such as Python's NetworkX) may be used to simplify the construction and operation of the graph, also known as an initial node topology graph). Then, a certain deployment node is used as the initial node, and the second-layer deployment nodes are constructed by the topology extension method. Then, the third-layer deployment nodes are constructed based on the second-layer deployment nodes, and so on, until all the N deployment nodes are constructed into the initial node topology graph, thereby forming a node topology graph containing all deployment nodes and path data between all deployment nodes.

[0058] In some embodiments, generating a path data set of at least one time node based on the round-trip delay of all path data between N deployment nodes under at least one time node in the node topology graph may include the following process:

[0059] Taking a time node as an example, for the constructed node topology graph, measure the RTT of the path data from any initial deployment node to all other deployment nodes, and construct set T1 as {N1, N2, N3, ..., Nn, time, RTT}, where Nn represents the deployment node in the path data, time represents the measured time node, and RTT represents the RTT of the path data. Sort the deployment nodes under the path data in ascending order of RTT; then, from the remaining deployment nodes that are not used as initial deployment nodes, select one as a new initial deployment node, construct set T2, and so on, to construct a path data set TN{N1, N2, N3.....Nn, time, RTT} of N deployment nodes; where the smaller the RTT, the lower the network delay.

[0060] Furthermore, the RTT of the path data from any initial deployment node to all other deployment nodes can be measured by using the ping command, the tracert or traceroute command, or the transmission control protocol. The measurement method can be flexibly selected according to the actual scenario, and the embodiments of the present application are not limited here.

[0061] 202: Determine a node data set according to resource usage rates of each of the N deployment nodes.

[0062] In this step, the node data set can be determined based on at least one resource usage rate of the central processing unit (CPU) and disk usage of the N deployment nodes. For example, assuming that the CPU usage rate of the deployment node N1 is greater than 60%, or the disk usage rate is greater than 80%, the deployment node N1 is regarded as an abnormal deployment node and recorded in the node data set, so as to avoid deploying the deployment service on the deployment node based on this in the future.

[0063] 203: Assemble the path data set of at least one time node with the node data set and the service data set to be deployed, obtain the metadata set of at least one time node, and cache the metadata set of at least one time node to the monitoring pool.

[0064] For example, taking a time node as an example, assume that the assembled metadata set is M{T{T1{1,2,...n..},T2{2,1,...n..}......TN{3,2,...n..}},D{1,2,3,..S},P{M1.....Mn}}}, where n can be 30% of all topologies at a certain deployment starting point, and S is the number of required deployment services.

[0065] Furthermore, the metadata sets collected and assembled in real time can be placed in the monitoring pool in chronological order to ensure data integrity and avoid data loss or damage during the extraction process. It is also convenient to obtain the required metadata sets from the monitoring pool in the future and use them as the basis for corresponding service deployment analysis.

[0066] 102: Divide the path data set of at least one time point according to a division rule to obtain at least one path data combination set, where the at least one path data combination set represents path data corresponding to at least one time node included in a set time period.

[0067] In some embodiments, the path data set of at least one time point is divided according to a division rule to obtain at least one path data combination set, which can be: taking a metadata set as an example, the above-assembled metadata set is split, for example, when the metadata set M{T{T1{1,2,...n,time,RTT},T2{1,2,...n,time,RTT}......TN{1,2,...n,time,RTT}},D{1,2,3,..S},P{M1.....Mn}}} is split, the metadata set can be split into T{T1{1,2,...n,time,RTT},T2{1,2,...n,time,RTT}......TN{1,2,...n,time,RTT}},D{1,2,3,..S} and P{M1.....Mn}}} , where the node data set P is a fixed value that has been determined and does not participate in subsequent normalization, classification aggregation, path selection and other processes. Therefore, it can be split out to reduce the amount of subsequent data calculation; then, according to the time bucket division rule (for example, every 6 minutes or every 8 minutes as a group), the path data set of at least one time point is grouped to form at least one path data combination set (for example, Q1{T1{1,2,...n,time1,RTT},T2{1,2,...n,time1,RTT}..},Q2{T1{1,2,...n,time2,RTT},T2{1,2,...n,time2,RTT}..}......Qk{T1{1,2,...n,timek,RTT},T2{1,2,...n,timek,RTT}...}).

[0068] 103: Determine deployment strategies for S deployment services according to at least one path data combination set, a service data set, and a node data set.

[0069] In some embodiments, determining the deployment strategy of S deployment services according to at least one path data set, service data set, and node data set may include the following process:

[0070] First, normalization processing is performed on at least one path data combination set, and a stability coefficient of each of the at least one path data combination set after the processing is calculated.

[0071] In some embodiments, the normalization processing method may include linear normalization, minimum-maximum normalization, Z-score normalization, etc., which can be reasonably selected according to the path data combination set. Further, the normalization processing function can be: Among them, RTT represents the RTT of the path data contained in any of the above-mentioned path data combination sets Q, n is the number of deployment nodes in the path data contained in Q, and k is the number of path data combination sets contained after being bucketed by time.

[0072] In some embodiments, the stability coefficient satisfies the following expression:

[0073]

[0074] Among them, δ i Characterizes the stability coefficient of the i-th path data combination set, RTT j Characterizes the round-trip delay corresponding to the jth path data in the i-th path data combination set, S RTT (avg) represents the normalized value of the i-th path data combination set.

[0075] Secondly, a target path data set is determined from at least one path data combination set according to respective stability coefficients and node data sets.

[0076] In some embodiments, this step may be: based on their respective stability coefficients, screening out candidate path data combination sets that meet the stability coefficient threshold from at least one path data combination set; based on the node data set, removing M abnormal deployment nodes contained in the candidate path data combination set to obtain a target path data set.

[0077] For example, first, the stability coefficients of all path data sets can be used to form a stability set (for example, δ(δ 1 ,…,δ k )), and then 1 ,…,δ k ) to calculate the standard deviation, so as to filter out the path data combination set that meets the standard deviation threshold (for example, 30% closest to 0) in the subsequent step. This δ can satisfy the following expression:

[0078] Then, for the screened candidate path data combination set (assuming Q1), combined with the above-mentioned determination of abnormal deployment nodes, the corresponding abnormal deployment nodes can be removed from the path data of the path data combination set to form a target path data set. Assuming that there are 5 deployment nodes in total, of which 5 are abnormal deployment nodes, then 5 in all path data in Q1{T1{1,2,...n,time1,RTT},T2{1,2,...n,time1,RTT}...} will be kicked out.

[0079] Next, the target path data set is mapped to the node topology map to determine at least one target deployment node.

[0080] In this step, specifically, the deployment nodes on the path data in the target path data set are mapped to the node topology map, and the deployment nodes with the highest proportion are selected layer by layer, so as to select the best full-path deployment node.

[0081] Finally, according to at least one target deployment node and service data set, determine the deployment strategy of S services to be deployed. In this step, specifically: take the full path deployment node as the starting node of the link for service deployment, and deploy it downward in sequence. For high availability of the service, use a layer-by-layer descending method for mapping. For example, assuming that the target deployment node is {N1, N2, N3, N4} and the deployment service is {S1, S2, S3, S4}, then the mapping relationship is {N1{S1, S4}, N2{S2, S1}, N3{S3, S2}, N4{S4, S3}}. Each deployment service has two copies, which can be deployed on different deployment nodes to ensure that after one of the deployment nodes is paralyzed, the deployment service can also be run normally on another deployment node.

[0082] Furthermore, when the deployment strategies of the S deployment services are determined, the deployment services can be deployed accordingly according to the determined target deployment nodes and mapping relationships, and then the corresponding deployment paths can be recorded and started.

[0083] In other embodiments, after the deployment strategies of the S deployment services are determined, they may also be monitored in real time, specifically:

[0084] Obtain the current deployment path of the S deployment services during operation, and compare the deployment path with the recorded historical deployment path (specifically, it may refer to the historical deployment path at the same time point as the current one); if the similarity between the deployment path and the historical deployment path meets the similarity requirement, maintain the deployment nodes included in the deployment path to run the S deployment services; if the similarity between the deployment path and the historical deployment path does not meet the similarity requirement, migrate the S deployment services on the deployment nodes in the deployment path to the historical deployment path.

[0085] For example, suppose the deployment path at the current time point and the deployment path at the same time point in history are recorded as a set C(t1){N{n1,n2,n2..nn}M{n1,n2,n3..nn}}, where N is the deployment path of the current S deployment services during operation and M is the recorded historical deployment path; calculate the similarity of the set C(t1) Among them, x and y represent the node data at the corresponding position of the deployment path at the current time point and the historical deployment path, respectively. Furthermore, in order to control the similarity within the range of (0,1], It is determined that the closer the similarity is to 0.5, the greater the similarity of the two deployment paths; then, when the similarity of a certain time node set C belongs to (0, 0.2) or (0.8, 1), the similarity result can be reported to facilitate the subsequent preparation of service migration. For example, it is determined whether there is a business request detection at present. If there is no business request detection at the current time point, the service migration process is carried out.

[0086] Furthermore, when migrating S deployment services on the deployment nodes in the deployment path to the historical deployment path, specifically: the deployment services on the deployment nodes where there are differences between the current deployment path and the historical deployment path will be migrated, and a deployment service can be started on the deployment path to make a request call first, and then when the migrated historical deployment path runs normally, the deployment services on the deployment nodes in the deployment path will be stopped, thereby achieving seamless service migration.

[0087] In an embodiment of the present application, a metadata set of at least one time node is obtained, and the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, so as to facilitate the subsequent selection of the optimal deployment node based on this, and avoid deploying the deployment service to the abnormal deployment node. The path data set of at least one time point is divided according to the division rule to obtain at least one path data combination set, and the at least one path data combination set represents the path data corresponding to at least one time node included in the set time period; according to the at least one path data combination set, the service data set, and the node data set, the deployment strategy of the S deployment services is determined, and a comprehensive analysis can be performed from the data sets of multiple dimensions to improve the efficiency and applicability of service deployment.

[0088] Based on the above Figure 1 The method shown, Figure 3 A logical diagram of service deployment provided in an embodiment of the present application.

[0089] First, through the constructed node topology map, the path data set is collected in real time, and the abnormal nodes in the node topology map are determined and recorded in the node data set. At the same time, the path data set, the node data set, and the service data set containing the deployed service are assembled into a metadata set and cached in the monitoring pool; the metadata set of at least one time node is obtained from the monitoring pool in real time, and the metadata set of at least one time node is divided according to the division rule to obtain at least one path data combination set; finally, the deployment strategy of the deployment service is determined according to at least one path data combination set, the service data set, and the node data set; during the operation of the deployment service, the deployment path of the current deployment service during the operation process can be obtained, and the recorded historical deployment path can be compared. If the similarity between the deployment path and the historical deployment path does not meet the similarity requirement, the service migration operation is performed (the relevant description of the previous operation can be performed and will not be repeated here), so as to achieve efficient, flexible, intelligent and effective service deployment.

[0090] Based on the same technical concept, a service deployment device is also provided in an embodiment of the present application, which can implement the above-mentioned service deployment method process in the embodiment of the present application.

[0091] Figure 4 The schematic diagram of the structure of a service deployment device provided in an embodiment of the present application includes an acquisition module 401 , a decomposition module 402 , a deployment module 403 , and may further include a metadata extraction module 404 .

[0092] The acquisition module 401 is used to obtain a metadata set of at least one time node; wherein the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, wherein N is an integer greater than 1, and M and S are both integers greater than 0.

[0093] The decomposition module 402 is used to divide the path data set of the at least one time point according to the division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents the path data corresponding to at least one time node included in the set time period.

[0094] The deployment module 403 is used to determine the deployment strategies of the S deployment services according to the at least one path data combination set, the service data set, and the node data set.

[0095] The metadata extraction module 404 is used to construct a node topology map of the N deployment nodes, and generate a path data set of the at least one time node based on the round-trip delay of all path data between the N deployment nodes under at least one time node in the node topology map; determine the node data set according to the resource utilization rate of each of the N deployment nodes; assemble the path data set of the at least one time node with the node data set and the service data set to be deployed, respectively, to obtain the metadata set of the at least one time node, and cache the metadata set of the at least one time node to the monitoring pool.

[0096] In some embodiments, the deployment module 403 is specifically configured to:

[0097] Normalizing the at least one path data combination set respectively, and calculating a stability coefficient of the at least one path data combination set after the processing;

[0098] determining a target path data set from the path data combination set according to the respective stability coefficients and the node data set;

[0099] Mapping the target path data set to the node topology map to determine at least one target deployment node;

[0100] Determine deployment strategies for the S services to be deployed according to the at least one target deployment node and the service data set.

[0101] In some embodiments, the deployment module 403 is specifically configured to:

[0102] According to the respective stability coefficients, screening out a candidate path data combination set that meets a stability coefficient threshold from the at least one path data combination set;

[0103] According to the node data set, the M abnormal deployment nodes are removed from the candidate path data combination set to obtain the target path data set.

[0104] In some embodiments, the deployment module 403 is further configured to:

[0105] Obtaining the current deployment paths of the S deployment services during operation, and comparing the deployment paths with the recorded historical deployment paths;

[0106] If the similarity between the deployment path and the historical deployment path meets the similarity requirement, maintaining the deployment nodes included in the deployment path to run the S deployment services;

[0107] If the similarity between the deployment path and the historical deployment path does not meet the similarity requirement, the S deployment services on the deployment nodes in the deployment path are migrated to the historical deployment path.

[0108] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0109] Based on the same technical concept, an electronic device is also provided in an embodiment of the present application, and the electronic device can realize the functions of the aforementioned service deployment device.

[0110] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0111] At least one processor 501, and a memory 502 connected to the at least one processor 501. The specific connection medium between the processor 501 and the memory 502 is not limited in the embodiment of the present application. Figure 5 In the example, the processor 501 and the memory 502 are connected via a bus 500. The bus 500 is Figure 5 The connections between other components are shown in bold lines, and are not intended to be limiting. The bus 500 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 501 can also be called a controller, and there is no limitation on the name.

[0112] In the embodiment of the present application, the memory 502 stores instructions that can be executed by at least one processor 501. The at least one processor 501 can execute a service deployment method discussed above by executing the instructions stored in the memory 502. The processor 501 can implement Figure 4 The functions of each module in the device shown.

[0113] Among them, the processor 501 is the control center of the device, and can use various interfaces and lines to connect the various parts of the entire control device. By running or executing instructions stored in the memory 502 and calling data stored in the memory 502, the various functions of the device and processing data, the device can be monitored as a whole.

[0114] In the embodiment of the present application, the processor 501 may include one or more processing units, and the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 501. In some embodiments, the processor 501 and the memory 502 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0115] Processor 501 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of a service deployment method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0116] The memory 502 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 502 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 502 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 502 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0117] By designing and programming the processor 501, the code corresponding to the service deployment method described in the above embodiment can be fixed into the chip, so that the chip can execute the code when running. Figure 1The embodiment shown is a service deployment method. How to design and program the processor 501 is a technology well known to those skilled in the art and will not be described in detail here.

[0118] It should be noted here that the above-mentioned electronic device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0119] Based on the same technical concept, an embodiment of the present application provides a computer storage medium, the computer storage medium includes: a computer program code, when the computer program code is executed on a computer, the computer executes any one of the service deployment methods discussed above. Since the principle of solving the problem by the above-mentioned computer storage medium is similar to that of a service deployment method, the implementation of the above-mentioned computer storage medium can refer to the implementation of the method, and the repeated parts will not be repeated.

[0120] In the specific implementation process, the computer storage medium may include: Universal Serial Bus Flash Drive (USB), mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, and other storage media that can store program codes.

[0121] Based on the same technical concept, the embodiment of the present application also provides a computer program product, which includes: computer program code, when the computer program code is run on a computer, the computer executes any one of the service deployment methods discussed above. Since the principle of solving the problem by the above computer program product is similar to that of a service deployment method, the implementation of the above computer program product can refer to the implementation of the method, and the repeated parts will not be repeated.

[0122] The computer program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more conductors, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0123] The method in the present application can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the present application is executed in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device, a core network device, an OAM or other programmable device.

[0124] The computer program or instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it may also be an optical medium, such as a digital video disk; it may also be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0125] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0126] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the instructions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A service deployment method, characterized in that: include: Obtain a metadata set of at least one time node; wherein the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, where N is an integer greater than 1, and both M and S are integers greater than 0; Divide the path data set of the at least one time point according to the division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents the path data corresponding to at least one time node included in the set time period; Determine deployment strategies for the S deployment services based on the at least one path data combination set, the service data set, and the node data set.

2. The method according to claim 1, characterized in that Before obtaining the metadata set of at least one time point, the method further includes: Constructing a node topology graph of the N deployment nodes, and generating a path data set of at least one time node based on the round-trip delay of all path data between the N deployment nodes at at least one time node in the node topology graph; Determining the node data set according to resource utilization rates of each of the N deployment nodes; The path data set of the at least one time node is respectively assembled with the node data set and the service data set to be deployed to obtain a metadata set of the at least one time node, and the metadata set of the at least one time node is cached in a monitoring pool.

3. The method according to claim 2, characterized in that The determining, according to the at least one path data combination set, the service data set, and the node data set, the deployment strategies of the S deployment services comprises: Normalizing the at least one path data combination set respectively, and calculating a stability coefficient of the at least one path data combination set after the processing; determining a target path data set from the path data combination set according to the respective stability coefficients and the node data set; Mapping the target path data set to the node topology map to determine at least one target deployment node; Determine deployment strategies for the S services to be deployed according to the at least one target deployment node and the service data set.

4. The method according to claim 3, characterized in that The stability coefficient satisfies the following expression: Among them, the δ i Characterizes the stability coefficient of the i-th path data combination set, the RTT j represents the round trip delay corresponding to the jth path data in the i-th path data combination set, the S RTT (avg) represents the normalized value of the i-th path data combination set.

5. The method according to claim 3, characterized in that The step of determining a target path data set from the path data set according to the respective stability coefficients and the node data set comprises: According to the respective stability coefficients, screening out a candidate path data combination set that meets a stability coefficient threshold from the at least one path data combination set; According to the node data set, the M abnormal deployment nodes are removed from the candidate path data combination set to obtain the target path data set.

6. The method according to claim 1, characterized in that After determining the deployment strategies of the S deployment services according to the path data set, the service data set, and the node data set, the method further includes: Obtaining the current deployment paths of the S deployment services during operation, and comparing the deployment paths with the recorded historical deployment paths; If the similarity between the deployment path and the historical deployment path meets the similarity requirement, maintaining the deployment nodes included in the deployment path to run the S deployment services; If the similarity between the deployment path and the historical deployment path does not meet the similarity requirement, the S deployment services on the deployment nodes in the deployment path are migrated to the historical deployment path.

7. A service deployment device, characterized in that: include: An acquisition module is used to acquire a metadata set of at least one time node; wherein the metadata set includes a path data set of N deployment nodes, a service data set of S deployment services, and a node data set of M abnormal deployment nodes among the N deployment nodes, wherein N is an integer greater than 1, and both M and S are integers greater than 0; A decomposition module, used to divide the path data set of the at least one time point according to a division rule to obtain at least one path data combination set; wherein the at least one path data combination set represents the path data corresponding to at least one time node included in a set time period; A deployment module is used to determine the deployment strategy of the S deployment services according to the at least one path data combination set, the service data set, and the node data set.

8. The device according to claim 7, characterized in that The device also includes a metadata extraction module; The metadata extraction module is used to construct a node topology graph of the N deployment nodes, and generate a path data set of at least one time node based on the round-trip delay of all path data between the N deployment nodes at at least one time node in the node topology graph; Determining the node data set according to resource utilization rates of each of the N deployment nodes; The path data set of the at least one time node is respectively assembled with the node data set and the service data set to be deployed to obtain a metadata set of the at least one time node, and the metadata set of the at least one time node is cached in a monitoring pool.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to implement the method according to any one of claims 1 to 6 when executing a computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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