CN105939371A - Load balancing method and load balancing system for cloud computing - Google Patents
Load balancing method and load balancing system for cloud computing Download PDFInfo
- Publication number
- CN105939371A CN105939371A CN201510822344.5A CN201510822344A CN105939371A CN 105939371 A CN105939371 A CN 105939371A CN 201510822344 A CN201510822344 A CN 201510822344A CN 105939371 A CN105939371 A CN 105939371A
- Authority
- CN
- China
- Prior art keywords
- load
- load equalizer
- flexible
- monitoring information
- node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
-
- 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
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1038—Load balancing arrangements to avoid a single path through a load balancer
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer And Data Communications (AREA)
Abstract
The invention discloses a load balancing method and a load balancing system for cloud computing. The method comprises the following steps that: each monitoring node in a load balancer cluster sends monitoring information to a scalable service node, wherein the load balancer cluster comprises at least one load balancer, and the load balancer is in one-to-one correspondence with the monitoring node; the load balancer receives a scalable control instruction returned back by the scalable service node; and the load balancer controls own on or off according to the scalable control instruction. Precision management and control for a load balancing service are realized, consequently, the load balancer is enabled to serve applications better, operation and maintenance cost of the applications and platforms is saved greatly, utilization rate of resources is improved, and bottleneck of the load balancing service provided by a cloud platform is avoided.
Description
Technical field
The present invention relates to load balancing field, particularly relate to load-balancing method and the system of a kind of cloud computing.
Background technology
Becoming increasingly popular a large amount of industrial applications with cloud computing along with cloud computing technology, cloud computing is realizing the height of service
Availability, the advantage of the aspect such as extensibility of disposal ability are approved by industry more and more.Platform i.e. services
(Platform as a Service, referred to as PaaS), as a kind of important form of cloud computing, grow with each passing day in its status.
Paas enables to apply and quickly develops, disposes, tests, reaches the standard grade, and has effectively saved cost, also improves simultaneously
Efficiency.
Load balancing service be PaaS platform be supplied to application a kernel service so that apply development period the most not
Load when must consider on-line running this how to process.Load balancing service can detect the loading condition of application, and adopts
Take the load strategy of optimum.Under non-cloud computing environment, the general load-balancing device using hardware, but due to hardware
Load-balancing device expensive, be difficult to extension, therefore under cloud computing environment, more use software bear
Carry equilibrium, such as nginx, haproxy etc..
The load equipment used under cloud computing environment is often software form, and such as haproxy, its load capacity is wanted
Far it is weaker than the load equipment of hardware.Meanwhile, under cloud computing environment application can dynamic retractility, when applying spy
After being extended under fixed condition stretching, when having exceeded the maximum load threshold value that its corresponding load equalizer can bear,
May result in application and access situation about even cannot access slowly.Under cloud computing environment, traditional soft load balancing framework is such as
Shown in Fig. 1, load balancing service uses active-standby mode, such as, uses active and standby haproxy to take as load balancing
Business, the application that each haproxy can load has certain quantity to limit, the when that active-standby mode making real work
Only having main load balancing service and providing service, this pattern can solve the problem that certain High Availabitity problem, but cannot solve
Problem after number of applications reaches the load services upper limit.
Therefore, when using traditional software load equalization framework as shown in Figure 1, load balancing refers to application layer and bears
Carry, if number of applications reaches the upper limit of load equalizer, then normal load balancing service can have been affected, i.e.
Do not account for the loading condition of load equalizer itself.For the problems referred to above, effective solution is the most not yet proposed.
Summary of the invention
The invention provides load-balancing method and the system of a kind of cloud computing, equal at least to solve current software load
Weighing apparatus framework, the bottleneck problem that the application of a large amount of clouds causes when using load balancing service.
According to an aspect of the invention, it is provided the load-balancing method of a kind of cloud computing, including: load equalizer
Each monitor node in cluster sends monitoring information to flexible service node, and wherein, described load equalizer cluster includes
At least one load equalizer, described load equalizer and described monitor node one_to_one corresponding；Described load equalizer connects
Receive the extension and contraction control instruction that described flexible service node returns；Described load equalizer is according to the instruction control of described extension and contraction control
Make being turned on and off of self.
In one embodiment, receive, at described load equalizer, the extension and contraction control instruction that described flexible service node returns
Before, described method also includes: described flexible service node receives described monitoring information；Described flexible service node pair
Described monitoring information filters；Described flexible service node according to the monitoring information after presetting flexible strategy and filtering,
Generate the instruction of described extension and contraction control.
In one embodiment, the described strategy that stretches of presetting includes: in preset time period, described load equalizer works as
Front session number exceedes default maximum number of sessions, then increase load balancing service；Or institute in described preset time period
The current request number stating load equalizer reaches the predetermined threshold value of queue restriction size, then increase load balancing service.
In one embodiment, after generating the instruction of described extension and contraction control, described method also includes: store described prison
Control information.
In one embodiment, each monitor node in load equalizer cluster sends monitoring letter to flexible service node
Before breath, described method also includes: flexible strategy is preset in cloud platform configuration.
In one embodiment, unlatching or the pass of self is controlled at described load equalizer according to the instruction of described extension and contraction control
After closing, described method also includes: each load equalizer in load equalizer cluster described in configuration management node updates
Status information.
In one embodiment, described monitoring information includes: the current sessions of load equalizer, max-session, service
Device weight, queue limit.
According to another aspect of the present invention, it is provided that the SiteServer LBS of a kind of cloud computing, including load balancing
Device cluster and flexible service node, wherein, described load equalizer cluster includes at least one load equalizer and at least
One monitor node, described load equalizer and described monitor node one_to_one corresponding；Described monitor node, for institute
State flexible service node and send monitoring information；Described flexible service node, is used for returning extension and contraction control instruction；Described negative
Carry equalizer, be used for receiving the instruction of described extension and contraction control, and control the unlatching of self according to the instruction of described extension and contraction control
Or close.
In one embodiment, described flexible service node specifically for: receive described monitoring information, to described monitoring
Information filters, and generates the instruction of described extension and contraction control according to the monitoring information after presetting flexible strategy and filtering.
In one embodiment, described system also includes: memory element, is used for storing described monitoring information.
By load-balancing method and the system of the cloud computing of the present invention, gather the monitoring information of load equalizer, according to
Monitoring information obtains extension and contraction control instruction, determines that load equalizer is the need of flexible, it is achieved that to load balancing service
Precision management and control so that load balancing service is preferably for application service, greatly saved application and
The O&M cost of platform, improve the utilization rate of resource, it is to avoid the bottleneck of the load balancing service that cloud platform provides.
Accompanying drawing explanation
Accompanying drawing described herein is used for providing a further understanding of the present invention, constitutes the part of the application, this
Bright schematic description and description is used for explaining the present invention, is not intended that limitation of the invention.In the accompanying drawings:
Fig. 1 is soft load balancing Organization Chart traditional under the cloud computing environment of the embodiment of the present invention；
Fig. 2 is the flow chart of the load-balancing method of the cloud computing of the embodiment of the present invention；
Fig. 3 is the structured flowchart of the SiteServer LBS of the cloud computing of the embodiment of the present invention；
Fig. 4 is another structured flowchart of the SiteServer LBS of the cloud computing of the embodiment of the present invention；
Fig. 5 is the Organization Chart of the SiteServer LBS of the cloud computing of the embodiment of the present invention；
Fig. 6 is the intermodule call relation schematic diagram of the SiteServer LBS of the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.
Based on embodiments of the invention, the institute that those of ordinary skill in the art are obtained under not making creative work premise
There are other embodiments, broadly fall into protection scope of the present invention.
Embodiments providing the load-balancing method of a kind of cloud computing, Fig. 2 is the cloud computing of the embodiment of the present invention
The flow chart of load-balancing method, as in figure 2 it is shown, the method comprises the steps:
Step S201, each monitor node in load equalizer cluster sends monitoring information to flexible service node, its
In, load equalizer cluster includes at least one load equalizer, load equalizer and monitor node one_to_one corresponding；
Step S202, load equalizer receives the extension and contraction control instruction that flexible service node returns；
Step S203, load equalizer controls being turned on and off of self according to extension and contraction control instruction.
The method of above-described embodiment, by gathering the monitoring information of load equalizer, obtains flexible control according to monitoring information
System instruction, determines that load equalizer is the need of flexible, it is achieved that precision management and the control to load balancing service,
So that load balancing service is preferably application service, greatly saves the O&M cost of application and platform, carried
The high utilization rate of resource, it is to avoid the bottleneck of the load balancing service that cloud platform provides.
Above-mentioned monitoring information may include that the current sessions of load equalizer, max-session, server weight, queue
Limit.
Before step S201, said method can also include: flexible strategy is preset in cloud platform configuration.
In one embodiment, before step S202, said method can also include: flexible service node receives
Monitoring information；Monitoring information is filtered by flexible service node；Flexible service node is according to presetting flexible strategy and mistake
Monitoring information after filter, generates extension and contraction control instruction.Concrete, by Complex event processing, monitoring information can be entered
Row filters, and such as, uses Esper engine to analyze and filter real-time monitoring information.Above-mentioned default flexible strategy can
To include: in preset time period, the current sessions number of load equalizer exceedes default maximum number of sessions, then increase negative
Carry balancing service；Or the current request number of load equalizer reaches presetting of queue restriction size in preset time period
Threshold value, then increase load balancing service.
In the present embodiment, flexible service node gathers the monitoring information of load equalizer, through answering of flexible policy service
Miscellaneous event handling, in combination with the flexible strategy independently defined by cloud platform, finally determines whether load equalizer needs
Stretch, greatly saved the O&M cost of application and platform, improve the utilization rate of resource, it is to avoid cloud is put down
The bottleneck of the load balancing service that platform provides.
After generating extension and contraction control instruction, said method can also include: storage monitoring information.Facilitate follow-up checking.
After step S203, said method can also include: in configuration management node updates load equalizer cluster
The status information of each load equalizer.Upgrade in time the state of load equalizer, it is possible to preferably carries out load balancing clothes
Stretching of business.
Based on same inventive concept, the embodiment of the present invention additionally provides the SiteServer LBS of a kind of cloud computing, Ke Yiyong
In realizing the method described by above-described embodiment, as described in the following examples.Owing to this system solves the principle of problem
Similar to said method, therefore the enforcement of this system may refer to the enforcement of said method, repeats no more in place of repetition.
Used below, term " unit " or " module " can realize the software of predetermined function and/or the group of hardware
Close.Although the system described by following example preferably realizes with software, but hardware, or software and hardware
The realization of combination also may and be contemplated.
Fig. 3 is the structured flowchart of the SiteServer LBS of the cloud computing of the embodiment of the present invention, as it is shown on figure 3, this system
Including: load equalizer cluster 10 and flexible service node 20, wherein, load equalizer cluster 10 includes at least
One load equalizer 11 and at least one monitor node 12, load equalizer 11 and monitor node 12 one_to_one corresponding.
Monitor node 12, for sending monitoring information to flexible service node 20；
Described flexible service node 20, is used for returning extension and contraction control instruction；
Load equalizer 11, is used for receiving extension and contraction control instruction, and controls opening of self according to extension and contraction control instruction
Open or close.
The system of above-described embodiment, by gathering the monitoring information of load equalizer, obtains flexible control according to monitoring information
System instruction, determines that load equalizer is the need of flexible, it is achieved that precision management and the control to load balancing service,
So that load balancing service is preferably application service, greatly saves the O&M cost of application and platform, carried
The high utilization rate of resource, it is to avoid the bottleneck of the load balancing service that cloud platform provides.
Above-mentioned monitoring information may include that the current sessions of load equalizer, max-session, server weight, queue
Limit.
As shown in Figure 4, said system can also include: cloud platform 30, is used for configuring and presets flexible strategy.Preset
Flexible strategy may include that the current sessions number of load equalizer in preset time period exceedes default max-session
Number, then increase load balancing service；Or the current request number of load equalizer reaches queue limit in preset time period
The predetermined threshold value of size processed, then increase load balancing service.
Flexible service node 20 specifically for: receive monitoring information, monitoring information filtered, and according to presetting
Monitoring information after flexible strategy and filtration generates extension and contraction control instruction.
Said system can also include: memory element 40, is used for storing monitoring information.
Said system can also include: configuration management node 50, is used for updating in load equalizer cluster each load all
The status information of weighing apparatus.
Certainly, the simply one signal of above-mentioned Module Division divides, and the invention is not limited in this.As long as this can be realized
The Module Division of bright purpose, all should belong to protection scope of the present invention.
In order to the load-balancing method of above-mentioned cloud computing and system are carried out apparent explanation, below in conjunction with concrete
Embodiment illustrates, however, it should be noted that this embodiment is merely to be better described the present invention, and not structure
The present invention limits improperly in pairs.
The Organization Chart of the SiteServer LBS of cloud computing is as it is shown in figure 5, compared with traditional framework, use cluster load
Balanced mode, improves the high availability of application；Add flexible policy service for load balancing service simultaneously so that
Load balancing service can be according to the loading condition applied currently judging whether, needing to carry out load in cluster takes
Flexible (i.e. add or delete) of business.
Fig. 6 is the intermodule call relation schematic diagram of the SiteServer LBS of the embodiment of the present invention, and this framework includes: negative
Carry equalizer cluster (including load equalizer and monitor node), flexible policy service, Uniform Name service and disappear
Breath queue service.It is capable of the precision management to load balancing service and control, so that load is all based on this framework
Weighing apparatus service is preferably application service, saves O&M cost greatly, improves resource utilization.Say separately below
Bright.
The management control station of the i.e. PaaS platform of cloud platform, maintain platform each service and each application operation with
Monitoring, is mainly used to the dynamic retractility strategy of configuration load balancing service herein.
Flexible policy service is to control the actual flexible node of load balancing service, and it can receive from load balancing service
These data are filtered by various monitoring data that monitor node is sent or information by Complex event processing, coordinate
The flexible strategy of cloud platform sends concrete instruction to the most flexible.Such as, concrete flexible strategy can be at a certain section
In time, the current sessions number of a certain load equalizer has exceeded the maximum number of sessions set or current request number reaches
Queue limits the 80% of size.Complex event processing can use Esper engine to analyze and filter real-time monitoring
Data, mate monitoring data queue according to the flexible strategy of cloud platform configuration, such as number of request in lasting 10 minutes
Reach the 80% of queue restriction, then needed to increase load balancing service.The monitoring data analyzed and filtered can be protected
It is stored in data base.
Load equalizer cluster is that the cluster of load balancing service realizes, and is used for providing load balancing to concrete cloud application
Service.
Uniform Name service (configuration management) is equal for flexible strategy and the load at runtime change load equalizer
The configuration information of weighing apparatus cluster.Configuration object is put on the configuration node of ZooKeeper cluster, by stretching by configuration information
Contracting policy service monitors configuration node, when load balancing service carries out flexible, dynamically updates in ZooKeeper cluster
Load configuration node.The configuration information of load cluster is identical with monitoring information, the predominantly current meeting of load equalizer
Words, max-session, server weight, queue restriction etc..
Monitor node can be to act on behalf of Agent, continuous service in load equalizer, performs the task of management node also
Feedback result is given flexible policy service.The content (i.e. monitoring information) of monitoring is mainly the current meeting of load equalizer
Words, max-session, server weight, queue restriction etc., be a dynamic content information.
Message Queuing Services (information transmission) is used for realizing message interface, complete flexible policy service and monitor node it
Between interacting message.When the static state in flexible policy service is stretched the dynamic content that strategy matching sends to monitor node
Time, trigger flexible.
The internal database of data base's (information warehouse-in) i.e. PaaS platform, is used for depositing the prison of load equalizer herein
Control information.
The unified entrance that in unified entrance i.e. PaaS platform, application accesses, can be made up of F5+Nginx, is interconnection
The sole inlet of net access platform application, after external request is via F5 and Nginx, is distributed to each load balancing
On device.
By above-mentioned modules, it is possible to accomplish the dynamic retractility of load balancing service, flexible strategy can be by cloud platform
Self-defined, improve the motility of application load service, too increase high availability simultaneously.
In sum, the present invention proposes a kind of use feelings by monitoring load equalizer under cloud computing PaaS environment
Condition, the method that load equalizer is carried out dynamic retractility, the load balancing service in cloud computing environment is unified
Runtime management and cluster stretch, and overcome the defect of conventional architectures, solve the application of a large amount of cloud and use load balancing service
The bottleneck problem being likely encountered, it is ensured that the stable operation of PaaS platform.
In flow chart or at this, any process described otherwise above or method description are construed as, and expression includes
One or more is for realizing the module of code of executable instruction of step of specific logical function or process, fragment
Or part, and the scope of the preferred embodiment of the present invention includes other realization, wherein can not by shown or
The order discussed, including according to involved function by basic mode simultaneously or in the opposite order, performs function,
This should be understood by embodiments of the invention person of ordinary skill in the field.
In the description of this specification, reference term " embodiment ", " some embodiments ", " example ", " specifically show
Example " or the description of " some examples " etc. means to combine this embodiment or example describes specific features, structure, material
Or feature is contained at least one embodiment or the example of the present invention.In this manual, above-mentioned term is shown
The statement of meaning property is not necessarily referring to identical embodiment or example.And, the specific features of description, structure, material or
Person's feature can combine in any one or more embodiments or example in an appropriate manner.
Particular embodiments described above, has been carried out the purpose of the present invention, technical scheme and beneficial effect the most in detail
Describe in detail bright, be it should be understood that the specific embodiment that the foregoing is only the present invention, be not used to limit this
Bright protection domain, all within the spirit and principles in the present invention, any modification, equivalent substitution and improvement etc. done,
Should be included within the scope of the present invention.
Claims (10)
1. the load-balancing method of a cloud computing, it is characterised in that including:
Each monitor node in load equalizer cluster sends monitoring information, wherein, described load to flexible service node
Equalizer cluster includes at least one load equalizer, described load equalizer and described monitor node one_to_one corresponding；
Described load equalizer receives the extension and contraction control instruction that described flexible service node returns；
Described load equalizer controls being turned on and off of self according to the instruction of described extension and contraction control.
Method the most according to claim 1, it is characterised in that receive described flexible at described load equalizer
Before the extension and contraction control instruction that service node returns, described method also includes:
Described flexible service node receives described monitoring information；
Described monitoring information is filtered by described flexible service node；
Described flexible service node, according to the monitoring information after presetting flexible strategy and filtering, generates described extension and contraction control and refers to
Order.
Method the most according to claim 2, it is characterised in that the described strategy that stretches of presetting includes:
In preset time period, the current sessions number of described load equalizer exceedes default maximum number of sessions, then increase negative
Carry balancing service；Or
In described preset time period, the current request number of described load equalizer reaches the default threshold of queue restriction size
Value, then increase load balancing service.
Method the most according to claim 2, it is characterised in that after generating the instruction of described extension and contraction control,
Described method also includes: store described monitoring information.
Method the most according to claim 1, it is characterised in that respectively monitor joint in load equalizer cluster
Before point sends monitoring information to flexible service node, described method also includes: flexible strategy is preset in cloud platform configuration.
Method the most according to claim 1, it is characterised in that at described load equalizer according to described flexible
After control instruction controls self be turned on and off, described method also includes:
The status information of each load equalizer in load equalizer cluster described in configuration management node updates.
Method the most according to any one of claim 1 to 6, it is characterised in that described monitoring information includes:
The current sessions of load equalizer, max-session, server weight, queue limit.
8. the SiteServer LBS of a cloud computing, it is characterised in that including: load equalizer cluster and flexible clothes
Business node, wherein, described load equalizer cluster includes at least one load equalizer and at least one monitor node,
Described load equalizer and described monitor node one_to_one corresponding；
Described monitor node, for sending monitoring information to described flexible service node；
Described flexible service node, is used for returning extension and contraction control instruction；
Described load equalizer, is used for receiving the instruction of described extension and contraction control, and controls according to the instruction of described extension and contraction control
Being turned on and off of self.
System the most according to claim 8, it is characterised in that described flexible service node specifically for: connect
Receive described monitoring information, described monitoring information is filtered, and according to the monitoring letter after presetting flexible strategy and filtering
Breath generates the instruction of described extension and contraction control.
System the most according to claim 9, it is characterised in that described system also includes: memory element, uses
In storing described monitoring information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510822344.5A CN105939371A (en) | 2015-11-24 | 2015-11-24 | Load balancing method and load balancing system for cloud computing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510822344.5A CN105939371A (en) | 2015-11-24 | 2015-11-24 | Load balancing method and load balancing system for cloud computing |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105939371A true CN105939371A (en) | 2016-09-14 |
Family
ID=57153048
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510822344.5A Pending CN105939371A (en) | 2015-11-24 | 2015-11-24 | Load balancing method and load balancing system for cloud computing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105939371A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106230992A (en) * | 2016-09-28 | 2016-12-14 | 中国银联股份有限公司 | A kind of load-balancing method and load balancing node |
| CN107018197A (en) * | 2017-04-13 | 2017-08-04 | 南京大学 | A kind of holding load dynamic retractility mobile awareness Complex event processing method in a balanced way |
| CN108108204A (en) * | 2016-11-23 | 2018-06-01 | 湖北省楚天云有限公司 | The application program collocation method and device of cloud computing platform |
| CN109766188A (en) * | 2019-01-14 | 2019-05-17 | 长春理工大学 | A kind of load equilibration scheduling method and system |
| CN112532687A (en) * | 2020-11-03 | 2021-03-19 | 杭州朗澈科技有限公司 | Method and system for capacity expansion of kubernets load balancer |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060075101A1 (en) * | 2004-09-29 | 2006-04-06 | International Business Machines Corporation | Method, system, and computer program product for supporting a large number of intermittently used application clusters |
| WO2011075899A1 (en) * | 2009-12-24 | 2011-06-30 | 华为技术有限公司 | Method, apparatus and system for implementing multiple web application requests scheduling |
| CN102143046A (en) * | 2010-08-25 | 2011-08-03 | 华为技术有限公司 | Load balancing method, equipment and system |
| CN104243537A (en) * | 2013-06-24 | 2014-12-24 | 中国银联股份有限公司 | Automatic retractable method and system used under cloud computing environment |
-
2015
- 2015-11-24 CN CN201510822344.5A patent/CN105939371A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060075101A1 (en) * | 2004-09-29 | 2006-04-06 | International Business Machines Corporation | Method, system, and computer program product for supporting a large number of intermittently used application clusters |
| WO2011075899A1 (en) * | 2009-12-24 | 2011-06-30 | 华为技术有限公司 | Method, apparatus and system for implementing multiple web application requests scheduling |
| CN102143046A (en) * | 2010-08-25 | 2011-08-03 | 华为技术有限公司 | Load balancing method, equipment and system |
| CN104243537A (en) * | 2013-06-24 | 2014-12-24 | 中国银联股份有限公司 | Automatic retractable method and system used under cloud computing environment |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106230992A (en) * | 2016-09-28 | 2016-12-14 | 中国银联股份有限公司 | A kind of load-balancing method and load balancing node |
| CN106230992B (en) * | 2016-09-28 | 2019-04-26 | 中国银联股份有限公司 | A kind of load-balancing method and load balancing node |
| CN108108204A (en) * | 2016-11-23 | 2018-06-01 | 湖北省楚天云有限公司 | The application program collocation method and device of cloud computing platform |
| CN107018197A (en) * | 2017-04-13 | 2017-08-04 | 南京大学 | A kind of holding load dynamic retractility mobile awareness Complex event processing method in a balanced way |
| CN109766188A (en) * | 2019-01-14 | 2019-05-17 | 长春理工大学 | A kind of load equilibration scheduling method and system |
| CN112532687A (en) * | 2020-11-03 | 2021-03-19 | 杭州朗澈科技有限公司 | Method and system for capacity expansion of kubernets load balancer |
| CN112532687B (en) * | 2020-11-03 | 2022-07-08 | 杭州朗澈科技有限公司 | Method and system for capacity expansion of kubernets load balancer |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105939371A (en) | Load balancing method and load balancing system for cloud computing | |
| CN104283939B (en) | For flexibly flowing the device of unloading, method and non-transitory computer-readable media | |
| CN110677305B (en) | Automatic scaling method and system in cloud computing environment | |
| CN103916396B (en) | A kind of cloud platform application example automatic telescopic method based on loaded self-adaptive | |
| US9588815B1 (en) | Architecture for data collection and event management supporting automation in service provider cloud environments | |
| CN107395659A (en) | A kind of method and device of service handling and common recognition | |
| DE102021119015A1 (en) | EXTENSIBLE NETWORK TRAFFIC TECHNOLOGY PLATFORM TO INCREASE NETWORK RESILIENCE IN CLOUD APPLICATIONS | |
| US20180109434A1 (en) | Facilitating simulation of network conditions in a hybrid application environment | |
| US9628505B2 (en) | Deploying a security appliance system in a high availability environment without extra network burden | |
| CN103957237A (en) | Architecture of elastic cloud | |
| US10397281B2 (en) | Method, system and server for self-healing of electronic apparatus | |
| US10924412B2 (en) | Distribution of network traffic to software defined network based probes | |
| US11509693B2 (en) | Event-restricted credentials for resource allocation | |
| CN106557444A (en) | The method and apparatus for realizing SR-IOV network interface cards is, the method and apparatus for realizing dynamic migration | |
| US10103959B2 (en) | Scalable software monitoring infrastructure, using parallel task queuing, to operate in elastic cloud environments | |
| US20230126045A1 (en) | Event-Driven Provisioning of an Elastic Orchestration Platform | |
| CN109960579B (en) | Method and device for adjusting service container | |
| Khanna | RAS: A novel approach for dynamic resource allocation | |
| US11461121B2 (en) | Guest-driven virtual machine snapshots | |
| US9535758B2 (en) | Managing data distribution to networked client computing devices | |
| CN107666401A (en) | A kind of configuration information obtaining method and terminal | |
| CN105657009A (en) | Object gateway load balancing system and method, and cross-region object gateway storage system | |
| CN102902593B (en) | Agreement distributing and processing system based on caching mechanism | |
| CN115834668A (en) | Cluster node control method, device, equipment, storage medium and program product | |
| CN106484879B (en) | A kind of polymerization of the Map end data based on MapReduce |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160914 |
|
| RJ01 | Rejection of invention patent application after publication |