CN110661827A - Elastic expansion method, device, equipment and computer readable storage medium - Google Patents
Elastic expansion method, device, equipment and computer readable storage medium Download PDFInfo
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1095—Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
Abstract
The embodiment of the application discloses an elastic stretching method, an elastic stretching device, elastic stretching equipment and a computer readable storage medium, wherein the method comprises the following steps: determining key indexes in a network resource planning set; collecting corresponding key index data in a service network according to the key indexes in the network resource planning set; and under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set, synchronously performing elastic expansion and contraction processing on a plurality of micro services in the service network according to the micro service network resource planning data. According to the method and the device, all micro services in the service network are synchronously elastically stretched through the key indexes, so that the purpose of safely elastically stretching the service network under a complex networking scene is achieved, and the flexibility and the reliability of the service network are improved.
Description
Technical Field
The embodiment of the application relates to the technical field of communication, in particular to an elastic stretching method, an elastic stretching device, elastic stretching equipment and a computer readable storage medium.
Background
With the rise of containers, more and more applications are operated in a container form, and the appearance of container clusters stimulates the high-speed development of container clouds.
Elastic Scaling (Auto Scaling) is to automatically adjust the relevant resources serving an application according to specific needs and known policies, thereby ensuring the healthy operation of a service and improving the utilization rate of the resources under the condition that the operation load of the application is constantly changed.
Microservice (Microservice) is a group of independent resource entities for running specific function software, and is beneficial to improving the expansibility, the release speed and the deployment efficiency of products.
In the prior art, elastic scaling is based on resource changes such as a Central Processing Unit (CPU) and a memory when a virtual machine or a container runs, and the number of virtual machines or containers is determined by setting a threshold. For a complex networking scenario, especially in the field of communication technologies, a service is often composed of many network elements or functional entities, and the service is completed for users together. In order to ensure the reliability and stability of the user service, the flexible expansion and contraction mode is decided by only depending on the load of the computing resources, which cannot meet the requirements of operators, so that the service quality of the network cannot be guaranteed.
Disclosure of Invention
In view of this, an object of the embodiments of the present application is to provide an elastic scaling method, an apparatus, a device, and a computer-readable storage medium, so as to solve the problem that, in a complex networking scenario, the existing elastic scaling method cannot meet the requirements of an operator, so that the service quality of a network cannot be guaranteed.
The technical scheme adopted by the embodiment of the application for solving the technical problems is as follows:
according to an aspect of an embodiment of the present application, there is provided an elastic expansion method, including:
determining key indexes in a network resource planning set; wherein the network resource planning set comprises key indicator data and micro-service network resource planning data;
collecting data of corresponding key indexes in a service network according to the key indexes in the network resource planning set;
and under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set, synchronously performing elastic expansion and contraction processing on a plurality of micro services in the service network according to the micro service network resource planning data.
According to another aspect of the embodiments of the present application, there is provided an elastic telescopic device, including a determining module, a collecting module, and a processing module;
the determining module is used for determining key indexes in the network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data;
the collection module is used for collecting corresponding key index data in a service network according to the key indexes in the network resource planning set;
and the processing module is used for synchronously performing elastic expansion processing on a plurality of micro services in the service network according to the micro service network resource planning data under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set.
According to another aspect of the embodiments of the present application, there is provided an elastic stretching device, the device includes a memory, a processor, and an elastic stretching program stored in the memory and executable on the processor, and the elastic stretching program, when executed by the processor, implements the steps of the elastic stretching method described above.
According to another aspect of the embodiments of the present application, there is provided a computer readable storage medium having stored thereon an elastic stretching program, which when executed by a processor, implements the steps of the elastic stretching method described above.
According to the elastic expansion method, the elastic expansion device, the elastic expansion equipment and the computer readable storage medium, all micro services in the service network are synchronously elastically expanded through key indexes, so that the purpose of safely elastically expanding the service network in a complex networking scene is achieved, and the flexibility and the reliability of the service network are improved.
Drawings
FIG. 1 is a schematic flow chart of a method for elastic stretching according to a first embodiment of the present application;
FIG. 2 is another schematic flow chart illustrating a method of elastic stretching according to the first embodiment of the present application;
FIG. 3 is a schematic view of an elastic telescopic device according to a second embodiment of the present application;
fig. 4 is a schematic structural view of an elastic expansion device according to a third embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present application clearer and clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
First embodiment
As shown in fig. 1, a first embodiment of the present application provides an elastic expansion and contraction method, including:
step S11: determining key indexes in a network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data.
In this embodiment, the key indicator in the network resource planning set is source data for analyzing and optimizing the network resource planning set, including but not limited to at least one of the number of users accessing the service network and user data traffic.
The micro-service network resource planning data includes, but is not limited to, at least one of the number of copies of the run container of the micro-service, and the range of the number of copies of the run container of the micro-service.
By way of example, the network resource projection set may include { network capacity X, network capacity Y, network capacity Z }, specifically as follows:
the network capacity X is planned to support 1 to 1.5 million online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 2, the number of the container copies required by the micro service B is 3, and the number of the container copies required by the micro service C is 4;
the network capacity Y is planned to support 1.5 to 2 million online users, the resource specification of the network is that the number of the container copies required by the micro service A is 4, the number of the container copies required by the micro service B is 4, and the number of the container copies required by the micro service C is 7;
and the network capacity Z is planned to support 2 ten thousand or more online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 5, the number of the container copies required by the micro service B is 5, and the number of the container copies required by the micro service C is 10.
In this example, the number of online users is a key indicator, and the key indicator data may be 1 ten thousand to 1.5 ten thousand, 1.5 ten thousand to 2 ten thousand, or more. A complete service network consists of a micro service A, a micro service B and a micro service C, the services provided for users are jointly completed by the micro services, and the micro service A, the micro service B and the micro service C are deployed on a container cluster in a plurality of copies.
Referring to fig. 2, in an embodiment, the determining the key indicator in the network resource planning set further includes:
step S10: and acquiring the network resource planning set.
In this embodiment, the network resource planning set may be stored on the elastic expansion device after being configured in advance, and the network resource planning set may be obtained by reading the storage device. The acquisition method is not limited herein.
Step S12: and collecting corresponding key index data in the service network according to the key indexes in the network resource planning set.
In the above example, the key indicator in the network resource planning set is the number of online users, so data of the number of online users in the service network can be collected, and when the number of online users in the service network is 2 ten thousand or more, the service network is deployed with the network capacity Z.
Step S13: and under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set, synchronously performing elastic expansion and contraction processing on a plurality of micro services in the service network according to the micro service network resource planning data.
In this embodiment, the elastic scaling processing may be performed on a plurality of microservices in the service network in a container cluster interactive manner.
Referring to fig. 2 again, in an embodiment, after performing synchronous elastic scaling processing on a plurality of micro services in the service network according to the micro service network resource planning data, the method further includes:
step S14: operational data is collected for a plurality of microservices in the services network.
In this embodiment, by collecting the operational data of the plurality of micro-services in the services network, it is ensured that the operational data of the plurality of micro-services in the services network is consistent with the micro-services network resource planning data.
In another embodiment, the network resource planning set further includes microservice elastic scaling setting information; wherein the micro-service elastic stretching setting information comprises micro-service elastic stretching setting parameters;
after the synchronous elastic scaling processing is performed on the multiple micro services in the service network according to the micro service network resource planning data, the method further includes:
acquiring a value of a corresponding micro-service elastic stretching setting parameter in the service network according to the micro-service elastic stretching setting parameter;
and performing elastic scaling processing on the micro-services in the service network according to the values of the corresponding micro-service elastic scaling setting parameters in the service network and the micro-service elastic scaling setting information.
In this embodiment, the micro-service elastic scaling setting parameter is CPU utilization, i.e. resource load.
To better illustrate the present embodiment, the following describes the elastic scaling process with reference to different micro-service network resource planning data:
1) first micro-service network resource planning data
A complete service network consists of a micro service A, a micro service B and a micro service C, and services provided for users are jointly completed by the micro services. Operators plan a variety of network capacities, including:
the network capacity X is planned to support 1 to 1.5 million online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 2, the number of the container copies required by the micro service B is 3, and the number of the container copies required by the micro service C is 4;
the network capacity Y is planned to support 1.5 to 2 million online users, the resource specification of the network is that the number of the container copies required by the micro service A is 4, the number of the container copies required by the micro service B is 4, and the number of the container copies required by the micro service C is 7;
and the network capacity Z is planned to support 2 ten thousand or more online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 5, the number of the container copies required by the micro service B is 5, and the number of the container copies required by the micro service C is 10.
Initially, deploying the network at a network capacity X based on an expectation of a number of user accesses; in this case, the number of container copies run by the microservice a is 2, the number of container copies run by the microservice B is 3, and the number of container copies run by the microservice C is 4.
Then, collect the online user data in the service network, when the number of online users reaches 1.5 ten thousand, the network needs to be capacity adjusted. Elastic scaling processing of the micro-service A, the micro-service B and the micro-service C is finished interactively and synchronously with the container cluster, namely, a network is deployed according to the network capacity Y; in this case, the number of container copies operated by the microservice a is 4, the number of container copies operated by the microservice B is 4, and the number of container copies operated by the microservice C is 7.
And finally, periodically collecting the running copy number information of each micro service to ensure that the running copy number information is consistent with the container copy number corresponding to the network capacity Y.
2) And second micro-service network resource planning data
A complete service network consists of a micro service A, a micro service B and a micro service C, and services provided for users are jointly completed by the micro services. Operators plan a variety of network capacities, including:
the network capacity X is planned to support 100 GB-150 GB user data flow per second, the resource specification of the network is that the number of the container copies required by the micro service A is 1-2, the number of the container copies required by the micro service B is 3-4, and the number of the container copies required by the micro service C is 4-6;
the network capacity Y supports 150GB to 200GB user data flow per second in planning, the resource specification of the network is that the number of the container copies required by the micro service A is 2 to 3, the number of the container copies required by the micro service B is 4 to 5, and the number of the container copies required by the micro service C is 8 to 10;
and the network capacity Z supports user data flow of 200GB and higher per second in planning, and the resource specification of the network is that the number of the container copies required by the micro service A is 5-7, the number of the container copies required by the micro service B is 6-7, and the number of the container copies required by the micro service C is 15-20.
Meanwhile, elastic expansion strategies are set for the micro service A, the micro service B and the micro service C, and elastic expansion of the micro service is judged based on whether the CPU utilization rate is higher than a threshold value or lower than the threshold value.
Initially, the network is in the operation process with the network capacity Z, the number of the operation container copies of the micro service a is 5, the number of the operation container copies of the micro service B is 6, and the number of the operation container copies of the micro service C is 15.
Then, collecting user data traffic in the service network; when detecting that the user data flow per second is stably less than 200GB, the capacity of the network needs to be adjusted, and if the user data flow is between 150GB and 200GB per second, the network capacity Y should be adopted according to the micro-service network resource planning data, and the network needs to be elastically stretched to meet the requirement of the network capacity Y. Elastic expansion and contraction processing of the micro service A, the micro service B and the micro service C is finished interactively and synchronously with the container cluster, so that the number of running copies of the micro service A is 3, the number of running container copies of the micro service B is 5, and the number of running container copies of the micro service C is 10.
And then, detecting that the CPU utilization rate of the micro-service C is reduced to be below a threshold value, and modifying the running copy number of the micro-service C to be 9 by an elastic scaling strategy set for the micro-service C.
And finally, periodically collecting the running copy number information of each micro service, and ensuring that the running copy number information of each micro service is always in the container copy number range corresponding to the network capacity Y.
3) And the third micro-service network resource planning data
A complete service network consists of a micro service A, a micro service B and a micro service C, and services provided for users are jointly completed by the micro services. The operator plans the corresponding relation between the network capacity and the network resources, and the corresponding relation is defined as:
the resource planning required by 100GB user data flow per second is that the number of the micro-service A container copies is 1, the number of the micro-service B container copies is 3, and the number of the micro-service C container copies is 4.
When the user data flow exceeds 100GB per second, the number of copies of each micro service in the network is increased in proportion, namely when the user data flow is N x 100GB/s, the number of container copies required by the micro service A in the network is 1 x N, the number of container copies required by the micro service B in the network is 3 x N, and the number of container copies required by the micro service C in the network is 4 x N.
Initially, when the user data flow in the network is lower than 100GB/s, the number of copies of the operation container of the microservice a is 1, the number of copies of the operation container of the microservice B is 3, and the number of copies of the operation container of the microservice C is 4.
Then, collecting user data traffic in the service network; when it is detected that the user data traffic per second steadily exceeds 100GB/s but is below 200GB/s, a capacity adjustment of the network is required. And elastic expansion and contraction processing of the micro service A, the micro service B and the micro service C is finished interactively and synchronously with the container cluster, so that the number of the running copies of the micro service A is 2, the number of the running container copies of the micro service B is 6, and the number of the running container copies of the micro service C is 8.
And finally, periodically collecting the running copy number information of each micro service to ensure that the running copy number information is consistent with the container copy number.
According to the elastic expansion method, all micro services in the service network are synchronously elastically expanded through key indexes, so that the purpose of safely elastically expanding the service network in a complex networking scene is achieved, and the flexibility and the reliability of the service network are improved.
Second embodiment
As shown in fig. 3, a second embodiment of the present application provides an elastic telescopic apparatus, including: a memory 21, a processor 22 and a flexible stretch program stored in the memory 21 and executable on the processor 22, wherein the flexible stretch program when executed by the processor 22 is configured to implement the following flexible stretch method steps:
determining key indexes in a network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data;
collecting corresponding key index data in a service network according to the key indexes in the network resource planning set;
and under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set, synchronously performing elastic expansion and contraction processing on a plurality of micro services in the service network according to the micro service network resource planning data.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
the network resource planning set also comprises micro-service elastic expansion setting information; wherein the micro-service elastic stretching setting information comprises micro-service elastic stretching setting parameters;
after the synchronous elastic scaling processing is performed on the multiple micro services in the service network according to the micro service network resource planning data, the method further includes:
acquiring a value of a corresponding micro-service elastic stretching setting parameter in the service network according to the micro-service elastic stretching setting parameter;
and performing elastic scaling processing on the micro-services in the service network according to the values of the corresponding micro-service elastic scaling setting parameters in the service network and the micro-service elastic scaling setting information.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
the micro-service elastic expansion setting parameter is the CPU utilization rate.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
operational data is collected for a plurality of microservices in the services network.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
and acquiring the network resource planning set.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
the micro-service network resource planning data comprises at least one of the number of copies of the running container of the micro-service and the number range of copies of the running container of the micro-service.
The elastic expansion program, when executed by the processor 22, is further configured to implement the following steps of the elastic expansion method:
the key indexes in the network resource planning set comprise at least one of the number of users accessing the service network and the data flow of the users.
The elastic telescopic equipment provided by the embodiment of the application performs synchronous elastic telescopic on all micro services in the service network through the key indexes, so that the aim of safely performing elastic telescopic on the service network under a complex networking scene is fulfilled, and the flexibility and the reliability of the service network are improved.
Third embodiment
As shown in fig. 4, a third embodiment of the present application provides an elastic expansion device, which includes a determination module 31, a first collection module 32, and a first processing module 33;
the determining module 31 is configured to determine a key indicator in a network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data.
In this embodiment, the key indicator in the network resource planning set is source data for analyzing and optimizing the network resource planning set, including but not limited to at least one of the number of users accessing the service network and user data traffic.
The micro-service network resource planning data includes, but is not limited to, at least one of the number of copies of the run container of the micro-service, and the range of the number of copies of the run container of the micro-service.
By way of example, the network resource projection set may include { network capacity X, network capacity Y, network capacity Z }, specifically as follows:
the network capacity X is planned to support 1 to 1.5 million online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 2, the number of the container copies required by the micro service B is 3, and the number of the container copies required by the micro service C is 4;
the network capacity Y is planned to support 1.5 to 2 million online users, the resource specification of the network is that the number of the container copies required by the micro service A is 4, the number of the container copies required by the micro service B is 4, and the number of the container copies required by the micro service C is 7;
and the network capacity Z is planned to support 2 ten thousand or more online users, and the resource specification of the network is that the number of the container copies required by the micro service A is 5, the number of the container copies required by the micro service B is 5, and the number of the container copies required by the micro service C is 10.
In this example, the number of online users is a key indicator, and the key indicator data may be 1 ten thousand to 1.5 ten thousand, 1.5 ten thousand to 2 ten thousand, or more. A complete service network consists of a micro service A, a micro service B and a micro service C, the services provided for users are jointly completed by the micro services, and the micro service A, the micro service B and the micro service C are deployed on a container cluster in a plurality of copies.
In one embodiment, the apparatus may further include a first acquisition module (not shown in the figures);
the first obtaining module is configured to obtain the network resource planning set.
In this embodiment, the network resource planning set may be stored on the elastic expansion device after being configured in advance, and the network resource planning set may be obtained by reading the storage device. The acquisition method is not limited herein.
The first collecting module 32 is configured to collect corresponding key index data in the service network according to the key index in the network resource planning set.
In the above example, the key indicator in the network resource planning set is the number of online users, so data of the number of online users in the service network can be collected, and when the number of online users in the service network is 2 ten thousand or more, the service network is deployed with the network capacity Z.
The first processing module 33 is configured to, when the collected key index data in the service network is successfully matched with the key index data in the network resource planning set, perform elastic scaling processing on a plurality of micro services in the service network synchronously according to the micro service network resource planning data.
In this embodiment, the elastic scaling processing may be performed on a plurality of microservices in the service network in a container cluster interactive manner.
In one embodiment, the apparatus further comprises a second collection module (not shown in the figures);
the second collection module is configured to collect operation data of a plurality of microservices in the service network.
In this embodiment, by collecting the operational data of the plurality of micro-services in the services network, it is ensured that the operational data of the plurality of micro-services in the services network is consistent with the micro-services network resource planning data.
In another embodiment, the network resource planning set further includes microservice elastic scaling setting information; wherein the micro-service elastic stretching setting information comprises micro-service elastic stretching setting parameters;
the device further comprises a second acquisition module and a second processing module (not shown in the figure);
the second obtaining module is used for obtaining the corresponding value of the micro-service elastic stretching setting parameter in the service network according to the micro-service elastic stretching setting parameter;
and the second processing module is used for performing elastic expansion processing on the micro-service in the service network according to the value of the corresponding micro-service elastic expansion setting parameter in the service network and the micro-service elastic expansion setting information.
In this embodiment, the micro-service elastic scaling setting parameter is CPU utilization, i.e. resource load.
The elastic expansion device provided by the embodiment of the application performs synchronous elastic expansion on all micro services in the service network through the key indexes, so that the aim of performing safe elastic expansion on the service network under a complex networking scene is fulfilled, and the flexibility and the reliability of the service network are improved.
Fourth embodiment
A fourth embodiment of the present application provides a computer-readable storage medium, which stores an elastic expansion program, and the elastic expansion program is used for implementing the steps of the elastic expansion method according to the first embodiment when being executed by a processor.
It should be noted that the computer-readable storage medium of this embodiment belongs to the same concept as the method of the first embodiment, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are all correspondingly applicable in this embodiment, which is not described herein again.
According to the computer-readable storage medium, all micro services in the service network are synchronously elastically stretched through the key indexes, so that the purpose of safely elastically stretching the service network in a complex networking scene is achieved, and the flexibility and the reliability of the service network are improved.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The preferred embodiments of the present application have been described above with reference to the accompanying drawings, and are not intended to limit the scope of the claims of the application accordingly. Any modifications, equivalents and improvements which may occur to those skilled in the art without departing from the scope and spirit of the present application are intended to be within the scope of the claims of the present application.
Claims (10)
1. A method of elastic telescoping, the method comprising:
determining key indexes in a network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data;
collecting corresponding key index data in a service network according to the key indexes in the network resource planning set;
and under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set, synchronously performing elastic expansion and contraction processing on a plurality of micro services in the service network according to the micro service network resource planning data.
2. The method of claim 1, wherein the network resource projection set further comprises microservice elastic scaling setting information; wherein the micro-service elastic stretching setting information comprises micro-service elastic stretching setting parameters;
after the micro service network resource planning data performs synchronous elastic scaling processing on a plurality of micro services in the service network, the method further includes:
acquiring a value of a corresponding micro-service elastic stretching setting parameter in the service network according to the micro-service elastic stretching setting parameter;
and performing elastic scaling processing on the micro-services in the service network according to the values of the corresponding micro-service elastic scaling setting parameters in the service network and the micro-service elastic scaling setting information.
3. The method of claim 2, wherein the microservice elastic stretch setting parameter is Central Processing Unit (CPU) utilization.
4. The method of claim 1, wherein after performing synchronous elastic scaling on the plurality of micro-services in the service network according to the micro-service network resource planning data, further comprising:
operational data is collected for a plurality of microservices in the services network.
5. The method of claim 1, wherein prior to determining the key indicator in the network resource planning set, further comprising:
and acquiring the network resource planning set.
6. The method of claim 1, wherein the microservice network resource projection data comprises at least one of a number of copies of a running container of a microservice, and a range of numbers of copies of a running container of a microservice.
7. The method of claim 1, wherein the key metrics in the set of network resource plans comprise at least one of a number of users accessing a serving network and a user data traffic.
8. An elastic expansion device is characterized by comprising a determining module, a collecting module and a processing module;
the determining module is used for determining key indexes in the network resource planning set; wherein the network resource planning set comprises key index data and micro-service network resource planning data;
the collection module is used for collecting corresponding key index data in a service network according to the key indexes in the network resource planning set;
and the processing module is used for synchronously performing elastic expansion processing on a plurality of micro services in the service network according to the micro service network resource planning data under the condition that the collected corresponding key index data in the service network is successfully matched with the key index data in the network resource planning set.
9. An elastic stretching device, characterized in that the device comprises a memory, a processor and an elastic stretching program stored on the memory and executable on the processor, the elastic stretching program when executed by the processor implementing the steps of the elastic stretching method according to any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon an elastic scaling program which, when executed by a processor, implements the steps of the elastic scaling method according to any of claims 1 to 7.
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| CN201810688809.6A CN110661827B (en) | 2018-06-28 | 2018-06-28 | Elastic expansion method, device, equipment and computer readable storage medium |
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| CN111698301A (en) * | 2020-05-29 | 2020-09-22 | 成都新希望金融信息有限公司 | Service management method, device and storage medium for ensuring service continuation |
| CN113824590A (en) * | 2021-09-18 | 2021-12-21 | 武汉联影医疗科技有限公司 | Method for predicting problem of micro service network, computer device and storage medium |
| CN113824590B (en) * | 2021-09-18 | 2024-04-26 | 武汉联影医疗科技有限公司 | Method for predicting problem in micro service network, computer device, and storage medium |
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