CN115756861A - Distributed service processing method, device, electronic device and storage medium - Google Patents

Abstract

The disclosure provides a distributed service processing method and device, electronic equipment and a storage medium, and relates to the technical field of cloud computing, in particular to the technical fields of distributed cloud computing, elastic networks and the like. The implementation scheme is as follows: obtaining resource declaration information for a set of physical machines, the resource declaration information indicating at least resources currently owned by each physical machine in the set of physical machines; obtaining service declaration information of a service to be deployed, wherein the service declaration information comprises a plurality of instances of the service and resource demand information corresponding to each instance of the plurality of instances and used for indicating that physical machine resources are occupied when deployment is completed; determining a target physical machine corresponding to each of the plurality of instances from the set of physical machines based on the resource declaration information and the service declaration information; and deploying each instance in the plurality of instances on a target physical machine in the plurality of target physical machines corresponding to the instance.

Description

Distributed service processing method, device, electronic device and storage medium

technical field

The present disclosure relates to the technical field of cloud computing, in particular to the technical fields of distributed cloud computing, elastic network, and cloud storage, and in particular to a distributed service processing method, device, electronic equipment, computer-readable storage medium, and computer program product.

Background technique

Cloud computing refers to accessing elastic and scalable shared physical or virtual resource pools through the network. Resources can include servers, operating systems, networks, software, applications, and storage devices, etc. A technical system that deploys and manages resources in the form of services. Through cloud computing technology, it can provide efficient and powerful data processing capabilities for artificial intelligence, blockchain and other technical applications and model training.

In the distributed cloud computing platform, there will be multiple products, such as cloud servers, elastic networks, and cloud storage. Each cloud product generally consists of multiple services working together based on tree dependencies to implement related functions. Typical features are: many services, many instances, and complex connection relationships. How to manage the entire life cycle of distributed services is the core problem that needs to be solved in the process of distributed service management.

The approaches described in this section are not necessarily approaches that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any approaches described in this section are admitted to be prior art solely by virtue of their inclusion in this section. Similarly, issues mentioned in this section should not be considered to have been recognized in any prior art unless otherwise indicated.

Contents of the invention

The present disclosure provides a distributed service processing method, device, electronic equipment, computer readable storage medium and computer program product.

According to an aspect of the present disclosure, a distributed service processing method is provided, including: obtaining resource declaration information of a set of physical machines, the resource claim information at least indicating the current resources of each physical machine in the set of physical machines resource; obtain the service declaration information of the service to be deployed, the service declaration information includes multiple instances of the service and each instance of the multiple instances corresponding to indicate the physical machine resources required to complete the deployment resource requirement information; based on the resource declaration information and the service declaration information, determine a target physical machine corresponding to each instance in the plurality of instances from the set of physical machines; and combine the plurality of instances Each instance of is respectively deployed on a target physical machine corresponding to the instance among the plurality of target physical machines.

According to another aspect of the present disclosure, a distributed service processing apparatus is provided, including: obtaining resource declaration information of a physical machine set, where the resource declaration information at least indicates the current location of each physical machine in the physical machine set Have resources; obtain the service declaration information of the service to be deployed, the service declaration information includes multiple instances of the service and each instance in the multiple instances corresponds to an indication of the physical machine required to complete the deployment resource requirement information of resources; based on the resource declaration information and the service declaration information, determine a target physical machine corresponding to each instance in the plurality of instances from the set of physical machines; Each of the instances is respectively deployed on a target physical machine corresponding to the instance among the plurality of target physical machines.

According to another aspect of the present disclosure, there is provided an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores information executable by the at least one processor. instructions, the instructions are executed by the at least one processor, so that the at least one processor can execute the method according to the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program, wherein the computer program implements the method according to the embodiments of the present disclosure when executed by a processor.

According to one or more embodiments of the present disclosure, balanced deployment of distributed services can be realized, so that after services are deployed on multiple physical machines, resources on each physical machine are evenly distributed.

It should be understood that what is described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will be readily understood through the following description.

Description of drawings

The drawings exemplarily illustrate the embodiment and constitute a part of the specification, and together with the text description of the specification, serve to explain the exemplary implementation of the embodiment. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. Throughout the drawings, like reference numbers designate similar, but not necessarily identical, elements.

FIG. 1 shows a flowchart of a service processing method according to an embodiment of the present disclosure;

Fig. 2 shows a scene diagram of implementing distributed service management in a service processing method according to an embodiment of the present disclosure;

FIG. 3 shows a flowchart of a process of obtaining a target physical machine corresponding to each of multiple instances from a physical machine set based on resource declaration information and service declaration information in a service processing method according to an embodiment of the present disclosure;

Fig. 4 shows a flow chart of the process of deploying multiple instances on multiple target physical machines respectively in the service processing method according to an embodiment of the present disclosure;

FIG. 5 shows a flowchart of a service processing method according to an embodiment of the present disclosure;

FIG. 6 shows a flowchart of a service processing method according to an embodiment of the present disclosure;

FIG. 7 shows a flowchart of a service processing method according to an embodiment of the present disclosure;

Fig. 8 shows a structural block diagram of a service processing device according to an embodiment of the present disclosure; and

FIG. 9 shows a structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure.

Detailed ways

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In the present disclosure, unless otherwise stated, using the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, temporal relationship or importance relationship of these elements, and such terms are only used for Distinguishes one feature from another. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, they may also refer to different instances based on contextual description.

The terminology used in describing the various described examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, there may be one or more elements. In addition, the term "and/or" used in the present disclosure covers any one and all possible combinations of the listed items.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

According to an aspect of the present disclosure, a distributed service processing method is provided. As shown in Figure 1, the method 100 includes:

Step S110: Obtain resource declaration information of a physical machine set, where the resource declaration information at least indicates the current resources of each physical machine in the physical machine set;

Step S120: Obtain the service declaration information of the service to be deployed, the service declaration information includes multiple instances of the service and each of the multiple instances corresponds to an indication of the physical machine resources required to complete the deployment information on resource requirements;

Step S130: Based on the resource declaration information and the service declaration information, determine a target physical machine corresponding to each of the multiple instances from the physical machine set; and

Step S140: Deploy each of the multiple instances on a target physical machine corresponding to the instance among the multiple target physical machines.

In related technologies, when deploying services on a physical machine, only the problem of insufficient resources on the physical machine is considered, and the problem of whether the resources are balanced is not considered. For example, when deploying services including instances that consume 30G, 20G, and 100G on physical machines with 128G and 50G resources, the resources consumed by each instance are often considered separately, so that instances that consume 30G are prioritized Deployed on a physical machine with 128G resources, it will need to consume 20G to deploy on a physical machine with 50G resources, and the remaining instances that need to consume 100G need to find a suitable physical machine for deployment, so that the resources on the physical machine are not effectively utilized .

According to an embodiment of the present disclosure, by obtaining the resource declaration information of the physical machine set and the service name information of the service, multiple target physical machines for deploying services are determined from the physical machine set, because in the process of determining multiple target physical machines In this method, the current resources of each physical machine and the physical machine resources required by each instance to complete the deployment are considered, so that the determined target physical machine is a comprehensive consideration of the physical machine resources required by each instance to complete the deployment and each instance. After the current resources of the physical machine are determined, after the deployment of each instance is completed, the resource distribution among each target physical machine is balanced, so that the resources on each physical machine can be effectively used.

For example, when deploying services including instances that consume 30G, 20G, and 100G on physical machines with 128G resources, give priority to deploying instances that consume 20G and 100G on physical machines with 128G resources, and for the remaining The instance that consumes 30G is deployed on a physical machine with 50G resources, so that the resources on each physical machine are effectively utilized, and the resource distribution on each physical machine is relatively balanced.

According to the embodiments of the present disclosure, resource declaration information and service name information are used to declaratively configure the resources required for service deployment and the information of the resources possessed by the physical machine, so as to implement the resources required for service deployment and the resources possessed by the physical machine. The quantification of resources makes all the information in the service deployment process (including the resource demand information in the service deployment process and the resource information of the physical machine) be configured and structured. According to the configured and structured information, the Automatic allocation and planning facilitates service management and expansion.

In some embodiments, the resource declaration information includes data in json format, which describes the resources owned by each physical machine. For example, resource declaration information includes physical machine identification, name, ip address, type, region to which it belongs, central processing unit (CPU, Central Processing Unit), memory, common disk mount point and size, solid state drive (SSD, SolidState Drives) ) disk mount point and size etc.

In some embodiments, in step S110, resource declaration information is obtained by receiving information periodically sent by an agent (agent) on each physical machine.

In some embodiments, the service declaration information includes data in json (JavaScriptObjectNotation, JS Object Notation) format, which describes the service. It specifically includes: the service includes multiple instances, and the physical machine resources that each instance needs to occupy when completing deployment, the physical machine resources include basic hardware resources such as CPU, memory, disk, and SSD.

In some embodiments, in step S120, in response to receiving a service deployment request from a user, service declaration information of the service to be deployed is obtained.

In some embodiments, the service name information and resource declaration information are obtained through an Application Program Interface (API, Application Program Interface) server, and the service name information and resource declaration information are stored in the data storage server.

Referring to FIG. 2 , it shows a scene diagram of implementing distributed service management in a distributed service processing method according to some embodiments of the present disclosure. in,

The user sends a service deployment request to the API server 210 through the client 200, so that the API server 210 obtains service name information, and at the same time, each physical machine 220 sends information to the API server 210 through a wired or wireless network, so that the API server 210 obtains resource declaration information. The API server 210 stores the obtained service name information and resource declaration information in the data storage server 230 . At the same time, each physical machine 220 can also obtain information in the data storage server 230 via the API server 210 through a wired or wireless network.

In some embodiments, in step S130, the target physical machines corresponding to the multiple instances determined from the set of physical machines are the multiple target physical machines after the multiple instances are deployed on the multiple target physical machines The resource uniformity is better than the resource uniformity of the multiple other physical machines in the physical machine set after the multiple instances are deployed on the other multiple physical machines.

For example, after the multiple instances are deployed on the multiple target physical machines, the difference between the remaining resources on the multiple target physical machines is within a preset range, or after the multiple instances are deployed on the multiple target physical machines, The difference among the remaining resources on the multiple target physical machines is smaller than the difference among the remaining resources on the other multiple physical machines after the multiple instances are deployed on the other multiple physical machines.

In some embodiments, the resource declaration information also indicates the corresponding type of each physical machine in the set of physical machines among multiple types, and the service declaration information also includes each instance in the multiple instances Corresponding label information, the label information indicates the first type of physical machine with the highest affinity with the corresponding instance among multiple types of physical machines, and, as shown in FIG. 3 , step S130, based on the resource declaration information and the service declaration information, determining from the set of physical machines a target physical machine corresponding to each of the multiple instances includes:

Step 310: For each of the multiple instances, based on the tag information corresponding to the instance and the resource name information, obtain one or more candidate physical machines corresponding to the instance from the set of physical machines; and

Step 320: For each of the multiple instances, based on the resource requirement information corresponding to the instance and the one or more candidate physical machines, obtain a target physical machine corresponding to the instance.

Different instances have different affinity for different types of physical machines. For example, instances running on a certain type of CPU are more likely to run for as long as possible without being migrated to other processors than other instances running on this type. If the tendency to run for as long as possible without being migrated to other processors is high, the instance has a high affinity for this type of physical machine compared to other instances.

During the deployment process, the affinity of the instance to the physical machine is also considered during the deployment process, so that the obtained target physical machine is a physical machine with good affinity corresponding to each instance, and the running of the instance on the physical machine is improved. efficiency and quality.

For example, in step S310, for each instance, according to the label information of the instance, select one or more candidate physical machines with the highest information from the physical machine set, and in step S420, the one or more candidate physical machines The physical machine that currently has the largest resource among the physical machines is used as the target physical machine corresponding to the instance.

In some embodiments, the resource declaration information also indicates the availability zone to which each physical machine in the physical machine set belongs in multiple availability zones, and the service declaration information also includes the zones corresponding to the multiple instances distribution information, the area distribution information indicates the number of instances among the multiple instances to be deployed on physical machines in each of the multiple availability zones, and wherein, step S310 further includes: based on the instance The corresponding label information, obtaining one or more candidate physical machines corresponding to the instance from the set of physical machines includes:

Based on the one or more availability zones and label information corresponding to the instance, one or more candidate physical machines corresponding to the instance are obtained from the set of physical machines.

By partitioning and deploying multiple instances of the service, multiple instances are deployed in physically isolated multiple availability zones (Availability Zones), making full use of multiple availability zones to achieve high-availability solutions and avoid interruptions during service operation.

In some embodiments, the regional distribution information in the service name information is described by the replications field. A service can deploy different numbers of instances in different available regions. The corresponding declaration method is as follows: {replications:{"az1":10," az2":20}}.

In some embodiments, a generator is used to obtain a target physical machine corresponding to each instance in the multiple instances from one or more candidate physical machines through a knapsack algorithm.

Continuing to refer to FIG. 2, the generator 240 obtains the service name information and resource declaration information in the data storage server 230 through the API server 210, and according to the service name information and resource declaration information, obtains the target corresponding to each instance in the multiple instances of the service Physical machines for instance deployment.

In some embodiments, for each of the multiple instances, the target physical machine corresponding to the instance is the candidate that currently has the most resources among the one or more candidate physical machines corresponding to the instance physical machine.

By obtaining the candidate physical machine that currently has the most resources among the one or more candidate physical machines corresponding to the instance as the target physical machine corresponding to the instance, the candidate physical machines with more resources are allocated with priority to deploy the instance, After the instance is deployed on the physical machine, the speed of running the service is faster, and at the same time, the resource utilization rate of each physical machine in the physical machine set is higher.

In some embodiments, the service name information also includes service port information. For example, the service may start multiple ports, and different ports may include TCP (Transmission Control Protocol, Transmission Control Protocol), UDP (UserDatagram Protocol, User Datagram Protocol) ports. In the service declaration information, the service port information includes the number of TCP ports and UDP ports required to deploy the service, and each port is described in the form of a character string. For example, {"main_port":{"portal":"TCP","value":""},"api_port":{"portal":"TCP","value":""}}

In the process of deploying the instance, the physical machine obtains the port information of the corresponding instance by reading the service port information in the resource name information from the data storage server, so as to implement the deployment of the corresponding instance.

In some embodiments, the service name information includes installation files corresponding to each instance.

In some embodiments, in step S140, by sending the installation file of each instance to the corresponding target physical machine, the target physical machine is made to install the installation file of the corresponding instance, so as to realize the deployment of the instance.

In some embodiments, the installation files corresponding to each instance are stored in a distributed manner. Wherein, the service declaration information also includes the instance address corresponding to each instance in the plurality of instances, and the instance address is the address of the installation file used to deploy the instance, as shown in FIG. 4, step S140, the Multiple instances deployed on the multiple target physical machines include:

Step S410: Associating each of the multiple instances with a corresponding target physical machine among the multiple target physical machines, so as to generate instance deployment information corresponding to the instance; and

Step S420: Send the instance deployment information of each of the multiple instances to the corresponding target physical machine of the instance, so that the target physical machine can obtain the instance address of the instance based on the instance deployment information, and based on the Instance address, download the installation file of the instance to deploy the instance.

By decoupling the installation file of the instance from the service declaration information, introducing a distributed storage system, the installation file of the instance is stored in a distributed manner, so that the deployment of the service is easy to expand, and it can be realized in the scenario of large-scale concurrent deployment. Efficient deployment of services.

Continue referring to FIG. 2 , store the installation file of each instance in the multiple instances in the distributed storage system 250, and after obtaining the target physical machine corresponding to each instance, generate a relationship between each instance and the corresponding target physical machine Instance deployment information. After the physical machine periodically sends acquisition information to the API server 210 , in response to determining that the data storage server 230 has its corresponding instance and the instance deployment information of the instance, instance deployment is performed. During the process of deploying each instance on each physical machine 220, the instance address of each instance is obtained from the data storage server 230 via the API server 210, and the installation file of the corresponding instance is downloaded from the distributed storage system 250 based on the instance address to perform Installation, and thus instance deployment.

In some embodiments, as shown in Figure 5, the method also includes:

Step S510: After each of the multiple target physical machines deploys a corresponding instance in the multiple instances, obtain a port corresponding to the corresponding instance on the target physical machine;

Step S520: Obtain the mapping relationship between the multiple instances and multiple corresponding ports in the multiple target physical machines; and

Step S530: Send the mapping relationship to each of the multiple target physical machines, so that each of the multiple target physical machines responds to the execution instruction for obtaining the service , based on the mapping relationship, run the service.

In the prior art, the connection relationship management of each instance in the service is complicated, and it is necessary to maintain the configuration related to the connection relationship manually or by peripheral tools. In this case, by obtaining the mapping relationship between multiple instances and the corresponding ports in multiple target physical machines, and sending the mapping relationship to each physical machine, during the service running process, the mapping relationship can be obtained during the service running process. The connection relationship of each instance simplifies the management of the connection relationship.

In some embodiments, after each instance is deployed, as shown in FIG. 2 , register with the name server 260 through an agent on the physical machine 220, so that the name server 260 obtains all instances of the service and the corresponding port information. During the running of the service, through the mapping relationship between the ports, the calls between the instances are made, so as to realize the connection between the instances.

In some embodiments, in the service declaration information, the service name (app-name) is used as the unique index ID of the service. After the service deployment is completed, the ip and corresponding port information of each instance of the service will be registered in the name server (naming-server) 250 using the service name as a secret key. During the running process of the service, other dependent services will obtain all instance information of the corresponding service from the name server 260 according to the key, thereby initializing their own connection relationship configuration.

In some embodiments, the format of the ip and the corresponding port information of the service instance stored by the name server 260 is: {"app-name-1":{"instance1":{"ip":"1.1.1.1" , "ports":{"main_port":{"value":8080,"portal":"TCP"}}}}}.

In some embodiments, as shown in FIG. 6, the distributed service processing method according to the present disclosure further includes:

Step S610: Obtain resource consumption information from each of the multiple target physical machines, where the resource consumption information indicates that when a corresponding instance of the multiple instances is deployed on the target physical machine, the physical machine resources consumed; and

Step S620: Update the resource declaration information based on the resource consumption information of each target physical machine in the multiple target physical machines.

By obtaining the resource consumption information of each target physical machine from multiple target physical machines, the actual resources consumed by the physical machine after deploying the instance are obtained, and the feedback correction mechanism of the physical machine is introduced to avoid inaccurate manual estimation of resource requirements. For example, when the resource requirement information corresponding to each instance in the service name information indicates that the physical machine resources required to complete the deployment are less than the resources actually consumed by the physical machine when deploying the corresponding instance, it can be corrected by introducing feedback from the physical machine The mechanism makes it possible to ensure the optimal distribution of each instance of the next service when deploying each instance of the next service, and further improve resource utilization.

Continuing to refer to FIG. 2, the agent (agent) on the physical machine 220 periodically sends information to the API server 210, so that the API server obtains resource consumption information on it, and stores the resource consumption information in the data storage server 230, to update the resource declaration information.

In some embodiments, as shown in FIG. 7, the distributed service processing method according to the present disclosure further includes:

Step S710: updating the service declaration information in response to the service receiving an instance update operation, the instance update operation being used to update the first instance of the plurality of instances;

Step S720: Obtain first instance update information based on the updated service declaration information, the first instance update information is used to instruct the corresponding target physical machine to update the first instance; and

Step S730: Send the first instance update information to the target physical machine corresponding to the first instance, so that the target physical machine updates the first instance based on the first instance update information.

By updating the service name information, the full life cycle management of the service is realized.

In some embodiments, the instance update operation may be an operation for the user to modify or delete the first instance. For example, update the full installation file of the first instance, delete the installation file of the first instance, and so on.

For example, when the version of the instance needs to be updated, update the service name information so that the physical machine can download the new version of the instance installation file from the corresponding instance address of the instance according to the updated service name information. The instance installation file of the new version implements the instance update, and the instance is run to complete the instance update.

For another example, when deleting a certain instance, by updating the service name information, the relevant information of the instance in the updated service name information is deleted, so that the physical machine triggers the local deletion logic according to the updated service name information, For example, cancel the name service registration, stop the service, and clean up the data.

Through the above process, the management of the whole life cycle of the service can be completed.

According to another aspect of the present disclosure, a distributed service processing device is also provided. As shown in FIG. 8 , the device 800 includes: a resource declaration information acquisition unit 810 configured to obtain resource declaration information of a physical machine set, the The resource declaration information at least indicates the current resources of each physical machine in the set of physical machines; the service declaration information obtaining unit 820 is configured to obtain the service declaration information of the service to be deployed, and the service declaration information includes Multiple instances of the service and resource requirement information corresponding to each of the multiple instances for indicating physical machine resources required to complete the deployment; the physical machine determining unit 830 is configured to The declaration information and the service declaration information are used to determine a target physical machine corresponding to each instance in the plurality of instances from the set of physical machines; and the deployment unit 840 is configured to deploy the Each instance of is deployed on the target physical machine corresponding to the instance among the multiple target physical machines.

In some embodiments, the resource declaration information also indicates the corresponding type of each physical machine in the set of physical machines among multiple types, and the service declaration information also includes each instance in the multiple instances Corresponding label information, the label information indicates the first type of physical machine with the highest affinity with the corresponding instance among multiple types of physical machines, and the physical machine determining unit includes:

The candidate physical machine acquiring unit is configured to, for each of the multiple instances, obtain from the set of physical machines one or a plurality of candidate physical machines; and a physical machine determination subunit configured to obtain, for each of the plurality of instances, the resource requirement information corresponding to the instance and the one or more candidate physical machines corresponding to The target physical machine corresponding to this instance.

In some embodiments, the resource declaration information also indicates the availability zone to which each physical machine in the physical machine set belongs in multiple availability zones, and the service declaration information also includes the zones corresponding to the multiple instances distribution information, the area distribution information indicating the number of instances among the plurality of instances to be deployed on physical machines in each of the plurality of availability areas, and wherein the candidate physical machine acquisition unit includes : a first determining subunit, configured to obtain one or more candidate physical machines corresponding to the instance from the set of physical machines based on the one or more availability zones and label information corresponding to the instance.

In some embodiments, for each of the multiple instances, the target physical machine corresponding to the instance is the candidate physical machine that currently has the most resources among the one or more candidate physical machines corresponding to the instance. machine.

In some embodiments, the service declaration information further includes an instance address corresponding to each instance in the plurality of instances, and the instance address is an address of an installation file used to deploy the instance, and the deployment unit includes: An instance deployment information generating unit configured to associate each of the multiple instances with a corresponding target physical machine among the multiple target physical machines, so as to generate instance deployment information corresponding to the instance; and instance deployment An information sending unit configured to send the instance deployment information of each of the multiple instances to the corresponding target physical machine of the instance, so that the target physical machine obtains the instance of the instance based on the instance deployment information address, and download the installation file of the instance based on the instance address to deploy the instance.

In some embodiments, the apparatus 800 further includes: a resource consumption information obtaining unit configured to obtain resource consumption information from each target physical machine among the plurality of target physical machines, the resource consumption information indicating When the corresponding instance is deployed on the target physical machine, resources consumed by the physical machine; and a resource statement information update unit configured to update the resource consumption information of each target physical machine in the multiple target physical machines. Resource declaration information.

In some embodiments, the apparatus 800 further includes: a service declaration information update unit, configured to update the service declaration information in response to the service receiving an instance update operation, and the instance update operation is used to update the multiple The first instance in the instances: the update information obtaining unit is configured to obtain the first instance update information based on the updated service statement information, and the first instance update information is used to instruct the corresponding target physical machine to update the a first instance; and an instance update unit configured to send update information of the first instance to a target physical machine corresponding to the first instance, so that the target physical machine updates information based on the first instance, The first instance is updated.

In some embodiments, the apparatus 800 further includes: a port obtaining unit, configured to obtain the target physical machine after each target physical machine in the multiple target physical machines deploys the corresponding instance in the multiple instances. The machine corresponds to the port of the corresponding instance; the mapping relationship obtaining unit is configured to obtain the mapping relationship between the multiple instances and the multiple corresponding ports in the multiple target physical machines; and the mapping relationship sending unit, configured to send the mapping relationship to each of the plurality of target physical machines, so that each of the plurality of target physical machines responds to obtaining the operation of the service An instruction is used to run the service based on the mapping relationship.

According to the embodiments of the present disclosure, an electronic device, a readable storage medium, and a computer program product are also provided.

Referring to FIG. 9 , a structural block diagram of an electronic device 900 that can serve as a server or a client of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure, will now be described. Electronic device is intended to mean various forms of digital electronic computing equipment, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.

As shown in FIG. 9 , an electronic device 900 includes a computing unit 901, which can perform calculations according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. Various appropriate actions and processes are performed. In the RAM 903, various programs and data necessary for the operation of the electronic device 900 can also be stored. The computing unit 901 , ROM 902 , and RAM 903 are connected to each other through a bus 904 . An input/output (I/O) interface 905 is also connected to the bus 904 .

Multiple components in the electronic device 900 are connected to the I/O interface 905 , including: an input unit 906 , an output unit 907 , a storage unit 908 and a communication unit 909 . The input unit 906 may be any type of device capable of inputting information to the electronic device 900, the input unit 906 may receive input digital or character information, and generate key signal input related to user settings and/or function control of the electronic device, and This may include, but is not limited to, a mouse, keyboard, touch screen, trackpad, trackball, joystick, microphone, and/or remote control. The output unit 907 may be any type of device capable of presenting information, and may include, but is not limited to, a display, a speaker, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 908 may include, but is not limited to, a magnetic disk and an optical disk. The communication unit 909 allows the electronic device 900 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks, and may include but not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver and/or a chip Groups, such as Bluetooth™ devices, 802.11 devices, WiFi devices, WiMax devices, cellular communication devices, and/or the like.

The computing unit 901 may be various general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of computing units 901 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 executes various methods and processes described above, such as the method 100 . For example, in some embodiments, method 100 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 908 . In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 900 via the ROM 902 and/or the communication unit 909 . When the computer program is loaded into RAM 903 and executed by computing unit 901, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to execute the method 100 in any other suitable manner (for example, by means of firmware).

Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips Implemented in a system of systems (SOC), complex programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpreted on a programmable system including at least one programmable processor, the programmable processor Can be special-purpose or general-purpose programmable processor, can receive data and instruction from storage system, at least one input device, and at least one output device, and transmit data and instruction to this storage system, this at least one input device, and this at least one output device an output device.

Program codes for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special purpose computer, or other programmable data processing devices, so that the program codes, when executed by the processor or controller, make the functions/functions specified in the flow diagrams and/or block diagrams Action is implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer discs, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide for interaction with the user, the systems and techniques described herein can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user. ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and can be in any form (including Acoustic input, speech input or, tactile input) to receive input from the user.

The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., as a a user computer having a graphical user interface or web browser through which a user can interact with embodiments of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system can be interconnected by any form or medium of digital data communication, eg, a communication network. Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN) and the Internet.

A computer system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, each step described in the present disclosure may be executed in parallel, sequentially or in a different order, as long as the desired result of the technical solution disclosed in the present disclosure can be achieved, no limitation is imposed herein.

Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but It is limited only by the appended claims and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by equivalent elements thereof. Also, steps may be performed in an order different from that described in the present disclosure. Further, various elements in the embodiments or examples can be combined in various ways. Importantly, as technology advances, many of the elements described herein may be replaced by equivalent elements appearing after this disclosure.

Claims (19)

1. A distributed service processing method, comprising:

obtaining resource declaration information for a set of physical machines, the resource declaration information indicating at least resources currently owned by each physical machine in the set of physical machines;

obtaining service declaration information of a service to be deployed, wherein the service declaration information indicates a plurality of instances of the service and resource demand information corresponding to each instance of the plurality of instances and used for indicating physical machine resources occupied for completing deployment;

determining a target physical machine corresponding to each of the plurality of instances from the set of physical machines based on the resource declaration information and the service declaration information; and

and deploying each instance in the plurality of instances on a target physical machine corresponding to the instance in the plurality of target physical machines.

2. The method of claim 1, wherein the resource claim information further indicates a corresponding type of each of the set of physical machines in a plurality of types, the service claim information further includes tag information corresponding to each of the plurality of instances, the tag information indicates a first type of physical machine of the plurality of types of physical machines that has a highest affinity to the corresponding instance, and the determining, from the set of physical machines, the target physical machine corresponding to each of the plurality of instances based on the resource claim information and the service claim information comprises:

for each of the plurality of instances,

acquiring one or more candidate physical machines corresponding to the instance from the physical machine set based on the label information corresponding to the instance and the resource sound name information; and

and obtaining a target physical machine corresponding to the instance based on the resource demand information corresponding to the instance and the one or more candidate physical machines.

3. The method of claim 2, wherein the resource declaration information further indicates an available region of a plurality of available regions to which each physical machine of the set of physical machines belongs, the service declaration information further includes region distribution information corresponding to the plurality of instances, the region distribution information indicating a number of instances of the plurality of instances to be deployed on the physical machine of each of the plurality of available regions, and wherein obtaining, from the set of physical machines, one or more candidate physical machines corresponding to the instance based on the label information corresponding to the instance comprises:

and obtaining one or more candidate physical machines corresponding to the instance from the set of physical machines based on the one or more available areas and the label information corresponding to the instance.

4. The method of claim 2 or 3, wherein, for each of the plurality of instances, the target physical machine corresponding to the instance is a candidate physical machine currently having the most resources of the one or more candidate physical machines corresponding to the instance.

5. The method of any of claims 1-4, wherein the service declaration information further includes an instance address corresponding to each of the plurality of instances, the instance address being an address of an installation file used to deploy the instance, and the deploying the plurality of instances on the plurality of target physical machines, respectively, comprises:

associating each instance of the plurality of instances with a respective target physical machine of the plurality of target physical machines to generate instance deployment information corresponding to the instance; and

and sending the instance deployment information of each instance in the multiple instances to a corresponding target physical machine of the instance, so that the target physical machine obtains an instance address of the instance based on the instance deployment information, and downloads an installation file of the instance based on the instance address to deploy the instance.

6. The method of claim 1, further comprising:

obtaining resource consumption information from each of the plurality of target physical machines, the resource consumption information indicating resources consumed by the physical machine when a respective instance of the plurality of instances is deployed on the target physical machine; and

updating the resource declaration information based on resource consumption information for each of the plurality of target physical machines.

7. The method of claim 1, further comprising:

updating the service declaration information in response to the service receiving an instance update operation, the instance update operation to update a first instance of the plurality of instances;

obtaining first instance updating information based on the updated service declaration information, wherein the first instance updating information indicates a corresponding target physical machine to update the first instance; and

and sending the first instance updating information to a target physical machine corresponding to the first instance, so that the target physical machine updates the first instance based on the first instance updating information.

8. The method of claim 1, further comprising:

after each target physical machine in the plurality of target physical machines deploys a corresponding instance in the plurality of instances, obtaining a port of the target physical machine corresponding to the corresponding instance;

obtaining mapping relationships between the plurality of instances and a plurality of corresponding ports in the plurality of target physical machines; and

sending the mapping relationship to each of the plurality of target physical machines to cause each of the plurality of target physical machines to execute the service based on the mapping relationship in response to an execution instruction to obtain the service.

9. A distributed service processing apparatus, comprising:

a resource declaration information obtaining unit configured to obtain resource declaration information of a set of physical machines, the resource declaration information indicating at least a current resource of each physical machine in the set of physical machines;

the service declaration information obtaining unit is configured to obtain service declaration information of a service to be deployed, where the service declaration information includes multiple instances of the service and resource requirement information corresponding to each of the multiple instances and used for indicating that physical machine resources are occupied for completing deployment;

a physical machine determination unit adapted to determine a target physical machine corresponding to each of the plurality of instances from the set of physical machines based on the resource declaration information and the service declaration information; and

a deployment unit configured to deploy each of the plurality of instances on a target physical machine of the plurality of target physical machines corresponding to the instance.

10. The apparatus of claim 9, wherein the resource declaration information further indicates a corresponding type of each of the set of physical machines among a plurality of types, the service declaration information further includes label information corresponding to each of the plurality of instances, the label information indicating a first type of physical machine among the plurality of types of physical machines having a highest affinity with the corresponding instance, and the physical machine determination unit includes:

a candidate physical machine obtaining unit, configured to, for each of the multiple instances, obtain one or more candidate physical machines corresponding to the instance from the set of physical machines based on the tag information and the resource declaration information corresponding to the instance; and

and the physical machine determining subunit is configured to, for each of the multiple instances, obtain a target physical machine corresponding to the instance based on the resource demand information corresponding to the instance and the one or more candidate physical machines.

11. The apparatus according to claim 10, wherein the resource declaration information further indicates a belonging available area of each physical machine in the set of physical machines in a plurality of available areas, the service declaration information further includes area distribution information corresponding to the plurality of instances, the area distribution information indicating a number of instances of the plurality of instances to be deployed on the physical machine in each of the plurality of available areas, and wherein the candidate physical machine acquisition unit includes:

the first determining subunit is configured to obtain one or more candidate physical machines corresponding to the instance from the set of physical machines based on the one or more available areas and the tag information corresponding to the instance.

12. The apparatus of claim 10 or 11, wherein, for each of the plurality of instances, the target physical machine corresponding to the instance is a candidate physical machine currently having the most resources of the one or more candidate physical machines corresponding to the instance.

13. The apparatus according to any one of claims 9-12, wherein the service declaration information further includes a respective instance address of each of the plurality of instances, the instance address being an address of an installation file for deploying the instance, and the deploying unit includes:

an instance deployment information generating unit configured to associate each of the plurality of instances with a corresponding target physical machine of the plurality of target physical machines to generate instance deployment information corresponding to the instance; and

and the instance deployment information sending unit is configured to send the instance deployment information of each instance in the multiple instances to a corresponding target physical machine of the instance, so that the target physical machine obtains an instance address of the instance based on the instance deployment information, and downloads the installation file of the instance based on the instance address to deploy the instance.

14. The apparatus of claim 9, further comprising:

a resource consumption information obtaining unit configured to obtain resource consumption information from each of the plurality of target physical machines, the resource consumption information indicating resources consumed by the physical machine when the corresponding instance is deployed on the target physical machine; and

a resource declaration information updating unit configured to update the resource declaration information based on resource consumption information of each of the plurality of target physical machines.

15. The apparatus of claim 9, further comprising:

a service declaration information updating unit configured to update the service declaration information in response to the service receiving an instance update operation, the instance update operation being used to update a first instance of the plurality of instances;

an update information obtaining unit, configured to obtain first instance update information based on the updated service declaration information, where the first instance update information is used to instruct a corresponding target physical machine to update the first instance; and

and the instance updating unit is configured to send the first instance updating information to a target physical machine corresponding to the first instance, so that the target physical machine updates the first instance based on the first instance updating information.

16. The apparatus of claim 9, further comprising:

a port obtaining unit configured to obtain, after each of the plurality of target physical machines deploys a corresponding instance of the plurality of instances, a port of the target physical machine corresponding to the corresponding instance;

a mapping relation obtaining unit configured to obtain mapping relations between the plurality of instances and a plurality of corresponding ports in the plurality of target physical machines; and

a mapping relation sending unit configured to send the mapping relation to each of the plurality of target physical machines, so that each of the plurality of target physical machines responds to an execution instruction for obtaining the service, and executes the service based on the mapping relation.

17. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.

19. A computer program product comprising a computer program, wherein the computer program realizes the method of any one of claims 1-8 when executed by a processor.

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