CN111124669A - Operation method, system, terminal and storage medium of distributed SaaS software - Google Patents
Operation method, system, terminal and storage medium of distributed SaaS software Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
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Abstract
The invention provides an operation method, a system, a terminal and a storage medium of distributed SaaS software, comprising the following steps: deploying SaaS software on a cloud host group with elastic scaling service; collecting the resource utilization rate of the cloud host group; judging whether the resource utilization rate is within a preset range: and if not, controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group. The invention utilizes services such as strong cloud infrastructure management, rich performance index monitoring, flexible elastic scaling calculation and the like provided by OpenStack to realize rapid online deployment of SaaS application, low load, high stable operation, low cost, easy management and maintenance and high-performance operation under large-scale concurrent users.
Description
Technical Field
The invention relates to the technical field of cloud platforms, in particular to an operation method, a system, a terminal and a storage medium of distributed SaaS software.
Background
The OpenStack is an open source project aiming at providing software for the construction and management of public and private clouds, and is formed by combining several main components such as computing, storage, network and the like to complete cloud computing management work, and the OpenStack aims to provide a cloud computing management platform which is simple to implement, can be expanded in a large scale, is rich and has a unified standard for hundreds of millions of users all over the world.
In recent years, the SaaS mode is rapidly popularized and widely applied in various industries due to the advantages of short deployment time, low risk, convenient use, multiple renting, customization and the like, and the upgrading of the IT industry and the development of electronic commerce economy are greatly promoted. Nowadays, SaaS application software is built and operated based on a specific cloud environment, and is extremely popularized and popularized in the industry due to the characteristics of easiness in deployment, scalability, mobility, easiness in management and the like, so that the cost input of SaaS application operation is greatly reduced, and the profit and the income of a SaaS service provider are improved.
Currently, with the continuous expansion of the user scale and the service content of the SaaS application software, the requirements and consumption of running resources are increasing. How to realize the rapid integration and deployment of the SaaS application under the condition of meeting the resource requirement, how to ensure the stable and smooth operation of the SaaS application under the condition of meeting the large-scale concurrent user request, and how to improve the flexible adaptability of the SaaS application under different loads becomes the key points of accelerating the online speed of the SaaS application, ensuring the stable performance of the SaaS application, reducing the cost input of the SaaS application and improving the user experience.
Disclosure of Invention
In view of the above-mentioned deficiencies in the prior art, the present invention provides an operating method, system, terminal and storage medium for distributed SaaS software, so as to solve the above-mentioned technical problems.
In a first aspect, the present invention provides an operation method of distributed SaaS software, including:
deploying SaaS software on a cloud host group with elastic scaling service;
collecting the resource utilization rate of the cloud host group;
judging whether the resource utilization rate is within a preset range:
and if not, controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group.
Further, the method further comprises:
acquiring the type and scale of a service request, and setting the application type and required resource parameters of the SaaS software;
setting a corresponding number of cloud host groups according to the number of the application types;
setting specification types and configuration parameters of the cloud hosts in the group according to the application types corresponding to the cloud host group;
and setting the number of the cloud hosts of the corresponding cloud host group according to the resource parameters corresponding to the application types.
Further, the acquiring the resource utilization rate of the cloud host group includes:
collecting the CPU utilization rates of all cloud hosts in a cloud host group;
and calculating the average CPU utilization rate of the cloud host group according to the CPU utilization rates of all the cloud hosts in the group.
Further, the controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group includes:
if the resource utilization rate of the cloud host group exceeds the upper limit of the preset range, adding cloud hosts in the cloud host group;
and if the resource utilization rate of the cloud host group exceeds the lower limit of the preset range, deleting the cloud hosts in the cloud host group.
In a second aspect, the present invention provides an operation system of distributed SaaS software, including:
the software deployment unit is configured for deploying SaaS software on the cloud host group with the elastic expansion service;
the resource acquisition unit is configured to acquire the resource utilization rate of the cloud host group;
a resource judging unit configured to judge whether the resource usage rate is within a preset range:
and the quantity adjusting unit is configured to control the resource utilization rate within a preset range by adjusting the quantity of the cloud hosts in the cloud host group if the resource utilization rate is not within the preset range.
Further, the system further comprises:
the SaaS software application type acquisition unit is used for acquiring the type and the scale of the service request and setting the type and the required resource parameters of the SaaS software application;
the grouping setting unit is configured to set the corresponding number of cloud host groups according to the number of the application types;
the host setting unit is configured and used for setting specification types and configuration parameters of the cloud hosts in the group according to the application types corresponding to the cloud host group;
and the quantity setting unit is configured to set the quantity of the cloud hosts of the corresponding cloud host group according to the resource parameters corresponding to the application types.
Further, the resource collecting unit includes:
the CPU utilization rate acquisition module is configured for acquiring the CPU utilization rates of all cloud hosts in the cloud host group;
and the average value calculating module is configured to calculate the average CPU utilization rate of the cloud host group according to the CPU utilization rates of all the cloud hosts in the group.
Further, the number adjusting unit includes:
the host increasing module is configured to increase the cloud hosts in the cloud host group if the resource utilization rate of the cloud host group exceeds the upper limit of the preset range;
and the host deleting module is configured to delete the cloud host in the cloud host group if the resource utilization rate of the cloud host group exceeds the lower limit of the preset range.
In a third aspect, a terminal is provided, including:
a processor, a memory, wherein,
the memory is used for storing a computer program which,
the processor is used for calling and running the computer program from the memory so as to make the terminal execute the method of the terminal.
In a fourth aspect, a computer storage medium is provided having stored therein instructions that, when executed on a computer, cause the computer to perform the method of the above aspects.
The beneficial effect of the invention is that,
according to the operation method, the system, the terminal and the storage medium of the distributed SaaS software, the cloud host group with the elastic telescopic service corresponding to the SaaS software is established by utilizing the elastic telescopic service of the cloud platform, the SaaS software is deployed on the corresponding cloud host group, the resource utilization rate of the cloud host group where the SaaS software is located is monitored in real time, and if the resource utilization rate is not within a preset range, the number of cloud hosts in the cloud host group is immediately adjusted so as to deal with the high concurrency condition of service requests or dynamically adjust the number of the cloud hosts when the service requests are less, so that the computing resources of the cloud platform are saved. The invention utilizes services such as strong cloud infrastructure management, rich performance index monitoring, flexible elastic scaling calculation and the like provided by OpenStack to realize rapid online deployment of SaaS application, low load, high stable operation, low cost, easy management and maintenance and high-performance operation under large-scale concurrent users.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention.
Fig. 2 is a schematic diagram of an initial SaaS software deployment of the method according to an embodiment of the present invention.
FIG. 3 is a schematic diagram of dynamic adjustment of a method according to one embodiment of the invention.
FIG. 4 is a schematic block diagram of a system of one embodiment of the present invention.
Fig. 5 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The following explains key terms appearing in the present invention.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention. The execution subject in fig. 1 may be an operation system of distributed SaaS software.
As shown in fig. 1, the method 100 includes:
and if not, controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group.
In order to facilitate understanding of the present invention, the operation method of the distributed SaaS software provided in the present invention is further described below with reference to the principle of the operation method of the distributed SaaS software of the present invention and the process of performing operation management on the distributed SaaS software in the embodiment.
Specifically, the operation method of the distributed SaaS software includes:
and S1, deploying SaaS software on the cloud host group with the elastic scaling service.
(1) The method comprises the steps of analyzing the requirements of users on SaaS application software, collecting service request types of different user groups, determining the types of required SaaS applications, and calculating the expected service request scale in the initial deployment online stage. As shown in fig. 2, there are 5 service requests for 4 user groups, corresponding to 2 SaaS applications, SaaS1 and SaaS 2. The service requests T1 and T2 are received and implemented by SaaS1 applications, and the service requests T3, T4 and T5 are received and implemented by SaaS2 applications.
(2) According to the type and scale of the service request, the type of the SaaS application, and the requirements and consumption of resources (such as cpu, memory, hard disk, and network bandwidth) of the SaaS application in step 1, determining the scale of the elastic expansion group (i.e., determining initialization information such as initial, maximum, and minimum numbers of cloud hosts), the specification type of the cloud hosts, the specifications of the load balancer and the listener, network configuration, monitoring indexes, and expansion strategies, that is, determining the corresponding relationship (1 to 1) between the elastic expansion group and the SaaS application.
(3) And determining the deployment relationship of the initialization of the SaaS application according to the step 1 and the step 2. According to a deployment relationship, basic cloud host images of SaaS applications and running environments thereof are uploaded and packaged through each service component of OpenStack in a cloud environment, basic cloud resources (such as networks, load balancers, monitors and the like) adapted to each SaaS application are configured, corresponding elastic telescopic group resources are created, and performance index monitoring thresholds of each elastic telescopic group are set. AS for the initialized deployment relationship in fig. 2, the service requests T1 and T2 are received and implemented by 2 SaaS1 applications, and the 2 SaaS1 applications are deployed in 2 cloud hosts VM2 initialized and constructed by the elastic stretching group AS 2; the service requests T3, T4, and T5 are received and implemented by 3 SaaS2 applications, respectively, and the 3 SaaS2 applications are deployed in 3 cloud hosts VM3 initially constructed by the elastic stretching group AS3, respectively.
And S2, collecting the resource utilization rate of the cloud host group.
And collecting all the CPU utilization rates of the cloud hosts of each cloud host group in real time, and calculating the average CPU utilization rate of the cloud host group. In this embodiment, the average CPU utilization of the cloud host group is collected, and in other embodiments of the present invention, the average memory utilization may also be collected, and the memory is used as a factor for regulating and controlling the cloud host group.
S3, judging whether the resource utilization rate is within a preset range: and if not, controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group.
In an elastic expansion group where the SaaS application is deployed, a threshold (such as an upper limit value and a lower limit value of the CPU utilization rate of cloud hosts in the group) and an elastic expansion strategy are monitored according to a performance index set during deployment (such as an expansion strategy is triggered when the CPU utilization rate in the group reaches the upper limit value in a fixed period, one cloud host is added to reduce the load, a contraction strategy is triggered when the CPU utilization rate reaches the lower limit value, one cloud host is reduced to save resources), when the concurrent service request scale of a user is increased rapidly, so that the resource consumption of the SaaS application in the elastic expansion group is higher than the upper limit value of the threshold set by the performance index, a dynamic expansion strategy in the elastic expansion group is triggered, and the number of cloud hosts in the elastic expansion group is increased to reduce the overall load below the upper limit value of the. As shown in fig. 3, the elastic scaling group 2 in which the SaaS2 is applied is higher than the upper threshold of performance index monitoring, which triggers the scaling policy to dynamically add one cloud host 2.
When the scale of the concurrent service request of the user is reduced, so that the resource consumption of the SaaS application in the elastic telescopic group is lower than the lower limit of the threshold set by the performance index, triggering a dynamic telescopic strategy in the elastic telescopic group, and reducing the number of cloud hosts in the elastic telescopic group to enable the whole load to be increased to the upper limit of the threshold. As shown in fig. 3, the elastic scaling group 1 in which SaaS1 is applied is lower than the lower threshold of performance index monitoring, which triggers the scaling policy to dynamically reduce one cloud host 1.
As shown in fig. 4, the system 400 includes:
a software deployment unit 410 configured to deploy SaaS software on a cloud host group having an elastic scaling service;
a resource collection unit 420 configured to collect resource utilization rates of the cloud host group;
the resource determining unit 430 is configured to determine whether the resource usage rate is within a preset range:
the quantity adjusting unit 440 is configured to control the resource utilization rate within a preset range by adjusting the quantity of the cloud hosts in the cloud host group if the resource utilization rate is not within the preset range.
Optionally, as an embodiment of the present invention, the system further includes:
the SaaS software application type acquisition unit is used for acquiring the type and the scale of the service request and setting the type and the required resource parameters of the SaaS software application;
the grouping setting unit is configured to set the corresponding number of cloud host groups according to the number of the application types;
the host setting unit is configured and used for setting specification types and configuration parameters of the cloud hosts in the group according to the application types corresponding to the cloud host group;
and the quantity setting unit is configured to set the quantity of the cloud hosts of the corresponding cloud host group according to the resource parameters corresponding to the application types.
Optionally, as an embodiment of the present invention, the resource collecting unit includes:
the CPU utilization rate acquisition module is configured for acquiring the CPU utilization rates of all cloud hosts in the cloud host group;
and the average value calculating module is configured to calculate the average CPU utilization rate of the cloud host group according to the CPU utilization rates of all the cloud hosts in the group.
Optionally, as an embodiment of the present invention, the number adjusting unit includes:
the host increasing module is configured to increase the cloud hosts in the cloud host group if the resource utilization rate of the cloud host group exceeds the upper limit of the preset range;
and the host deleting module is configured to delete the cloud host in the cloud host group if the resource utilization rate of the cloud host group exceeds the lower limit of the preset range.
Fig. 5 is a schematic structural diagram of a terminal system 500 according to an embodiment of the present invention, where the terminal system 500 may be used to execute an operation method of distributed SaaS software according to the embodiment of the present invention.
The terminal system 500 may include: a processor 510, a memory 520, and a communication unit 530. The components communicate via one or more buses, and those skilled in the art will appreciate that the architecture of the servers shown in the figures is not intended to be limiting, and may be a bus architecture, a star architecture, a combination of more or less components than those shown, or a different arrangement of components.
The memory 520 may be used for storing instructions executed by the processor 510, and the memory 520 may be implemented by any type of volatile or non-volatile storage terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The executable instructions in memory 520, when executed by processor 510, enable terminal 500 to perform some or all of the steps in the method embodiments described below.
The processor 510 is a control center of the storage terminal, connects various parts of the entire electronic terminal using various interfaces and lines, and performs various functions of the electronic terminal and/or processes data by operating or executing software programs and/or modules stored in the memory 520 and calling data stored in the memory. The processor may be composed of an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs connected with the same or different functions. For example, processor 510 may include only a Central Processing Unit (CPU). In the embodiment of the present invention, the CPU may be a single operation core, or may include multiple operation cores.
A communication unit 530 for establishing a communication channel so that the storage terminal can communicate with other terminals. And receiving user data sent by other terminals or sending the user data to other terminals.
The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and the program may include some or all of the steps in the embodiments provided by the present invention when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
Therefore, the cloud host group with the elastic telescopic service corresponding to the SaaS software is created by utilizing the elastic telescopic service of the cloud platform, the SaaS software is deployed on the corresponding cloud host group, the resource utilization rate of the cloud host group where the SaaS software is located is monitored in real time, and if the resource utilization rate is not within a preset range, the number of cloud hosts in the cloud host group is immediately adjusted so as to deal with the high concurrency condition of service requests or dynamically adjust the number of the cloud hosts when the service requests are less, so that the computing resources of the cloud platform are saved. According to the invention, services such as strong cloud infrastructure management, rich performance index monitoring, flexible elastic scaling calculation and the like provided by OpenStack are utilized to realize rapid online deployment, low-load high-stability operation, low-cost easy management and maintenance and high-performance operation under large-scale concurrent users, and the technical effect achieved by the embodiment can be seen in the description above, and is not repeated here.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in the form of a software product, where the computer software product is stored in a storage medium, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, and the storage medium can store program codes, and includes instructions for enabling a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, and the like) to perform all or part of the steps of the method in the embodiments of the present invention.
The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant points can be referred to the description in the method embodiment.
In the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An operation method of distributed SaaS software is characterized by comprising the following steps:
deploying SaaS software on a cloud host group with elastic scaling service;
collecting the resource utilization rate of the cloud host group;
judging whether the resource utilization rate is within a preset range:
and if not, controlling the resource utilization rate within a preset range by adjusting the number of the cloud hosts in the cloud host group.
2. The method of claim 1, further comprising:
acquiring the type and scale of a service request, and setting the application type and required resource parameters of the SaaS software;
setting a corresponding number of cloud host groups according to the number of the application types;
setting specification types and configuration parameters of the cloud hosts in the group according to the application types corresponding to the cloud host group;
and setting the number of the cloud hosts of the corresponding cloud host group according to the resource parameters corresponding to the application types.
3. The method of claim 1, wherein the collecting resource usage of the cloud host group comprises:
collecting the CPU utilization rates of all cloud hosts in a cloud host group;
and calculating the average CPU utilization rate of the cloud host group according to the CPU utilization rates of all the cloud hosts in the group.
4. The method according to claim 1, wherein the controlling the resource usage rate within a preset range by adjusting the number of cloud hosts in a cloud host group comprises:
if the resource utilization rate of the cloud host group exceeds the upper limit of the preset range, adding cloud hosts in the cloud host group;
and if the resource utilization rate of the cloud host group exceeds the lower limit of the preset range, deleting the cloud hosts in the cloud host group.
5. An operation system of distributed SaaS software, comprising:
the software deployment unit is configured for deploying SaaS software on the cloud host group with the elastic expansion service;
the resource acquisition unit is configured to acquire the resource utilization rate of the cloud host group;
a resource judging unit configured to judge whether the resource usage rate is within a preset range:
and the quantity adjusting unit is configured to control the resource utilization rate within a preset range by adjusting the quantity of the cloud hosts in the cloud host group if the resource utilization rate is not within the preset range.
6. The system of claim 5, further comprising:
the SaaS software application type acquisition unit is used for acquiring the type and the scale of the service request and setting the type and the required resource parameters of the SaaS software application;
the grouping setting unit is configured to set the corresponding number of cloud host groups according to the number of the application types;
the host setting unit is configured and used for setting specification types and configuration parameters of the cloud hosts in the group according to the application types corresponding to the cloud host group;
and the quantity setting unit is configured to set the quantity of the cloud hosts of the corresponding cloud host group according to the resource parameters corresponding to the application types.
7. The system of claim 5, wherein the resource acquisition unit comprises:
the CPU utilization rate acquisition module is configured for acquiring the CPU utilization rates of all cloud hosts in the cloud host group;
and the average value calculating module is configured to calculate the average CPU utilization rate of the cloud host group according to the CPU utilization rates of all the cloud hosts in the group.
8. The system of claim 5, wherein the quantity adjustment unit comprises:
the host increasing module is configured to increase the cloud hosts in the cloud host group if the resource utilization rate of the cloud host group exceeds the upper limit of the preset range;
and the host deleting module is configured to delete the cloud host in the cloud host group if the resource utilization rate of the cloud host group exceeds the lower limit of the preset range.
9. A terminal, comprising:
a processor;
a memory for storing instructions for execution by the processor;
wherein the processor is configured to perform the method of any one of claims 1-4.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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| CN201911206274.5A CN111124669A (en) | 2019-11-29 | 2019-11-29 | Operation method, system, terminal and storage medium of distributed SaaS software |
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| CN201911206274.5A CN111124669A (en) | 2019-11-29 | 2019-11-29 | Operation method, system, terminal and storage medium of distributed SaaS software |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112817985A (en) * | 2021-02-25 | 2021-05-18 | 紫光云技术有限公司 | Method for establishing flow control management based on cloud host |
| CN113569137A (en) * | 2021-07-06 | 2021-10-29 | 北京汇钧科技有限公司 | Recommendation method and device for cloud host specification, storage medium and electronic device |
-
2019
- 2019-11-29 CN CN201911206274.5A patent/CN111124669A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112817985A (en) * | 2021-02-25 | 2021-05-18 | 紫光云技术有限公司 | Method for establishing flow control management based on cloud host |
| CN113569137A (en) * | 2021-07-06 | 2021-10-29 | 北京汇钧科技有限公司 | Recommendation method and device for cloud host specification, storage medium and electronic device |
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