CN104601378B - The virtual resource flexible scheduling implementation method of connected applications performance indicator monitoring data - Google Patents
The virtual resource flexible scheduling implementation method of connected applications performance indicator monitoring data Download PDFInfo
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Abstract
The present invention discloses the virtual resource flexible scheduling implementation method of connected applications performance indicator monitoring data, includes the following steps：1）Temporally scheduling and/or the configuration by the elastic pond scheduling rule of operation system index scheduling needs progress；2）It is scheduled based on elastic pond scheduling rule；2‑1）It declares virtual machine queue to be launched and stops queue；2‑2）Inquire available elastic pond；2‑3）Circular treatment；2‑4）Judge scheduling rule, when for temporally scheduling rule, perform 241）Time scheduling submethod；When for operation system index scheduling rule, 242 are performed）Operation system index dispatches submethod；2‑5）Start all virtual machines of queue to be launched；2‑6）Stop all virtual machines of queue to be stopped；2‑7）Finishing scheduling, using flexible scheduling rule, reduces waste of the operation system to hardware resource, effectively reduces cost the drawbacks of solving the hardware resource waste present in the prior art.
Description
Technical field
The present invention relates to information technology fields, are the virtual resources of connected applications performance indicator monitoring data specifically
Flexible scheduling implementation method.
Background technology
Cloud resource manages system：Cloud resource management system can in multiple provinces, city's cloud computing resource pool computing resource, deposit
Storage resource, Internet resources are managed concentratedly.Management platform is disposed using level-one, and the traffic control of resource is all in each province and city resource
Pond carries out, and cloud resource management service system general plan framework is provided with resource management platform and provincial company as shown in Figure 1
Resource pool is provided with resource management platform database server and resource management platform application service in resource management platform
Device is provided with the hardware structures such as X86 resource control services and minicomputer resource control service, using money in provincial company resource pool
Dispatch adapter connection resource management platform and provincial company resource pool in source.
Cloud resource management system, which provides, pacifies the resource bid of cloud computing resource pool, resource operation, monitoring resource, resource
Entirely, the management functions such as resource backup, resource distribution.The centralized watch of enterprise data center's resource service condition can be carried simultaneously
It rises the management and control precision of Enterprise Information Resources construction plan and resource increases quantization level of decision-making, it can be achieved that resource pool growth trend is pre-
The analytic functions such as survey.
Cloud resource management system can receive the server resource of pipe isomery, including：X86 server families, IBM minicomputers system
Row, HP minicomputers machine series.Different cloud computing resources scheduling controlling software can also be integrated, including：
CloudController, vCenter etc..
IMS systems：IMS is the information O＆M comprehensive monitoring system for covering full company, using the technology path of " five one ",
The operation management technical platform of up/down perforation is formed, covering is whole comprising network, host, service application, safety equipment, desktop
The IT infrastructure monitoring at end etc. and standard O＆M flow.
In traditional IT Implementation of Information System Project, usual a set of operation system is deployed in a server or a set of collection
In the server environment of group, this traditional deployment way has following shortcoming：
1st, the waste of hardware is generated：A set of information system may need several servers in the peak value that user accesses,
And when user's visit capacity is at a low ebb, the resources such as cpu, memory of server are all in idle state, and which results in services
The waste of device hardware resource.
2nd, server expansion is inconvenient：General information system can do server resource certain planning before implementation,
But with the popularization of information system, when access user is more and more, server hardware dilatation is relatively complicated, if planning is indefinite
Also result in the hardware resource waste of bigger.
3rd, can not elastic calculation user access situation can generate machine risk of delaying：User's visit capacity is not unalterable, if because
Certain accidents cause user to increase the visit capacity of certain information system, then have certain generation due to hardware resource deficiency
The risk of system failure, although having done planning to this substantially in the project implementation and calamity is standby, such case is in current item
It is still difficult to avoid that under part.
Invention content
The drawbacks of it is an object of the invention to solve the hardware resource waste present in the prior art, utilize cloud computing technology
The management platform being combined with IMS systems is right based on elastic calculation technology by IMS systems to the real time monitoring of information system
Each application system carries out rational hardware distribution, and provides a kind of connected applications performance indicator monitoring number based on this management platform
According to virtual resource flexible scheduling implementation method, using flexible scheduling rule, can be significantly reduced operation system to hardware provide
The waste in source, effectively reduces cost, and system can be managed collectively by cloud computing basic platform, greatly alleviates fortune
The workload of dimension personnel, effectively saves human cost.
The present invention is achieved through the following technical solutions：The virtual resource flexible scheduling of connected applications performance indicator monitoring data
Implementation method includes the following steps：
1) temporally scheduling and the configuration by the elastic pond scheduling rule of operation system index scheduling needs progress；
2) it is scheduled based on elastic pond scheduling rule；
The step 2) includes step in detail below：
It 2-1) declares virtual machine queue to be launched and stops queue；
2-2) inquire available elastic pond；
2-3) judge scheduling rule, when for temporally scheduling rule, perform 2-3-1) time scheduling submethod；When to press
During operation system index scheduling rule, 2-3-2 is performed) operation system index scheduling submethod；
2-4) circular treatment step 2-3) the judgement scheduling rule；
2-5) start all virtual machines of queue to be launched；
2-6) stop all virtual machines of queue to be stopped；
2-7) finishing scheduling.
The drawbacks of solving the hardware resource waste present in the prior art, is combined using cloud computing technology and IMS systems
Management platform, by IMS systems to the real time monitoring of information system, based on elastic calculation technology, to each application system into
The rational hardware distribution of row, and the present invention is provided based on this management platform, using flexible scheduling rule, industry can be significantly reduced
Waste of the business system to hardware resource, effectively reduces cost, and system can be managed collectively by cloud computing basic platform,
The workload of operation maintenance personnel is greatly alleviated, effectively saves human cost.
Further, to better implement the present invention, the step 2-3-1) including step in detail below：
2-3-1-1) the virtual machine operation number of units of rule searching configuration；
The virtual machine in elastic pond 2-3-1-2) is inquired in a manner that start and stop ascending order arranges；
2-3-1-3) virtual machine is classified as stopping list and runs list；
2-3-1-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, is put into list to be stopped；When the virtual machine operation number of units of rule configuration and the operation of practical virtual machine
When number of units is identical, it will not dispatch；When the virtual machine operation number of units of rule configuration, which is more than practical virtual machine, runs number of units, from stopping
Number of units virtual machine obtained by only taking out the difference between rule configuration and reality in list in turn, is put into list to be launched；
It 2-3-1-5) returns and performs step 2-4).
Further, to better implement the present invention, the step 2-3-2) including step in detail below：
2-3-2-1) the virtual machine operation number of units of rule searching configuration；
2-3-2-2) inquire the virtual machine in elastic pond；
2-3-2-3) virtual machine is classified as stopping list and runs list；
2-3-2-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into list to be stopped；When
When the virtual machine operation number of units of rule configuration is identical with practical virtual machine operation number of units, it will not dispatch；When the void of rule configuration
Plan machine operation number of units takes out in turn between rule configuration and reality when being more than practical virtual machine operation number of units from stopping list
Difference obtained by number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into row to be launched
Table；
It 2-3-2-5) returns and performs step 2-4).
Further, to better implement the present invention, the step 1) includes step in detail below：
1-1) configuration starts, and increases elasticity pond newly；
Scheduling rule 1-2) is specified, divides 1-2-1) by the scheduling of operation system index and 1-2-2) temporally dispatch；
The step 1-2-1) including step in detail below：
1-2-1-1) specified services system；
1-2-1-2) specify the resource pool of extraction service system monitoring data；
The virtual machine of elastic pond schedulable 1-2-1-3) is configured；
1-2-1-4) distribu-tion index scheduling rule；
The step 1-2-2) including step in detail below：
The virtual machine of elastic pond schedulable 1-2-2-1) is configured；
1-2-2-2) configuration virtual machine start and stop sequence；
1-2-2-3) setup time scheduling rule；
1-3) configuration terminates.
Compared with prior art, the present invention haing the following advantages and advantageous effect：
(1) present invention solves the drawbacks of hardware resource waste present in the prior art, utilizes cloud computing technology and IMS systems
The management platform that system is combined by IMS systems to the real time monitoring of information system, based on elastic calculation technology, is answered each
Rational hardware distribution is carried out with system, using flexible scheduling rule, operation system can be significantly reduced to hardware resource
Waste, effectively reduces cost, system can be managed collectively by cloud computing basic platform, greatly alleviate O＆M people
The workload of member, effectively saves human cost.
(2) present invention realizes the combination of elastic calculation and operation system, effectively save hardware cost.
(3) present invention can be managed collectively the resilient expansion of operation system by cloud computing management platform, facilitate fortune
(4) present invention is tieed up using cloud computing technology mode, compare conventional deployment mode extend it is more flexible, conveniently.
Description of the drawings
Fig. 1 manages service system general plan framework for cloud resource of the present invention.
Fig. 2 disposes configuration diagram for IMS of the present invention.
Resource bid and visioning procedure figure when Fig. 3 is present invention application.
Fig. 4 is the configuration method flow chart of elastic pond scheduling rule of the present invention.
Fig. 5 is the method flow diagram of the present invention being scheduled based on elastic pond scheduling rule.
Fig. 6 is time scheduling submethod flow chart of the present invention.
Fig. 7 is operation system index scheduling sublayer method flow diagram of the present invention.
Specific embodiment
The present invention is described in further detail, but the implementation of the present invention is not limited to this with reference to embodiment.
Physical server：Dedicated for supporting the computer hardware equipment of enterprise application software system operation.
IT infrastructure devices：The hardware device of information system operation is used to support, is mainly included herein：It physical server and deposits
Store up equipment.
Virtual resource：One physical server is invented by more virtual servers by virtualization software, herein by this
The virtual server of sample is referred to as virtual resource.
Cloud computing：Cloud computing (Cloud Computing) is the tune of the related services such as network-based resource, operational capability
It spends, use and delivers, be usually directed to and provide the service that dynamic easily extends, and the often resource of virtualization by network.
IaaS：(Infrastructure as a Service) infrastructure services, and is service-oriented computing model
Development, the shared computing resource that service user is made to be concentrated by network access, computing resource include computing capability, store energy
Power, delivery capability be all it is dynamic, it is telescopic, can virtualize, and provided in a manner of service, make ISP only
Minimum management interworking is needed to realize flexible supply and the release quickly of computing resource.
Resouce controller：The core control engine of structure IaaS cloud platform, such as CloudController, vCenter are soft
Part just belongs to resouce controller.
Dispatch adapter：Between cloud resource Tomcat-AdminPortal and resouce controller, to the interface and letter of the two
Breath carries out adaptation integration, makes the two that can interact.
Resource group：In physical entity environment, each resource group, which corresponds to one group, has that CPU architecture is identical, similar nature
(CPU frequency, caching), which shares the physical server of same storage and the set of storage, a virtual machine, can only belong to a resource
Group.
Resource pool：All computing resources and its collection of relevant storage resource managed by a resouce controller example
It closes, each resource pool can be made of multiple resource groups, and a resource pool can also include multiple resource pools.
Secure group：One or more virtual machines are patrolled and are divided in different secure groups, the virtual machine between secure group can not
By network communication, the virtual machine in only same secure group could normal communication.
Elastic pond：Multiple virtual machines are patrolled and are divided in an elastic pond, user can pre-set scheduling rule, elasticity
After pond function is opened, virtual machine will be scheduled by specified rule in pond.
SAG：The remote connection request that (Secure Access Gateway) can initiate client is authenticated analyzing,
And connection is relayed on corresponding physical host by certain routing rule.
SOAP：Simple Object Application Protocol, simple object application protocol is Web service
Standard communication protocol.
Web Service：Web service is a kind of standardized service component based on XML, is the bottom branch of SOA framework
One of support technology.
Embodiment 1：
The present invention is mainly based upon cloud computing technology and its theory is mutually tied with IMS (information O＆M comprehensive monitoring system) system
It closes, realizes real time monitoring, the resilient expansion scheduling feature of information system.
Resilient expansion：The concept of resilient expansion earliest by the Amazon Company in the U.S. propose, in the present invention mainly for
Be the dynamic extension of the one kind for (virtual machine, disk space etc. being referred mainly in this invention) on service application hardware itself,
The dynamic of the virtual machine instance number of supporting business application is realized during service application is run to be increased or reduces.Operation system
It can start more example automatically when loading higher, load relatively low situation and be then automatically stopped some examples.Elasticity
It is extended to the distribution according to need for the resource that service application realizes truly.Resilient expansion is not simple multiple without foundation
System, for application service, increasing server number only increases Resource Calculation ability, it is also necessary to traditional " collection
It is unified into an entirety and externally provides service by group " technology.For cloud computing application, it will not be because of special business
Rule limits application, causes using corresponding change is done, this has violated the original idea that it is generated, it is more that concern is whole
Body behavior, whatsoever application can be in its operation, and enjoys its consistent various service.It is it can be seen that corresponding in resilient expansion
It is pre-created with the virtual machine needed for deployment, and one cluster, these virtual machines is set up by Intranet by application implementation person
It is put into a resource pool, strategically carries out starting required virtual machine instance, the management service of elastic calculation only focuses on
Then how many virtual machine inside resource pool is stopped or is started these virtual machines by strategy.
IMS disposes architecture mode using two-stage, as shown in Fig. 2, deploying the acquisition of some data in prefecture-level company simultaneously
Software and by data pick-up to provincial company, such as the data of webmaster, An Guan, desktop etc..The IMS of provincial company deployment passes through Socket
Partial key index is synchronized to general headquarters by mode, to carry out system operation examination and uniformly to show.
IMS realizes the acquisition of various monitoring datas, as shown in table 1：
Table 1
A built-in single two ticket flows in IMS, to data center, daily O＆M carries out workflow management, and major function includes：
Overhaul management is formulated including repair schedule, overhauls task management, defect management, two tickets (work ticket, operation order) pipe
The contents such as reason；
Operational management, including making an inspection tour the contents such as management, duty management；
Management and running mainly include equipment and stop multiple labour management with application system.Stop multiple labour management process and originate from maintenance meter
Draw examination ＆ approval activity after the completion of；
Customer service management, including consulting management, complaints and denunciation management, incident management and IT resource bid management.Wherein IT is provided
Application that source applications management includes Intranet networking application, outer net networks, the application of information system working relation, takes E-mail address application
Business device put into operation application, information equipment repair application, standby redundancy apply to purchase, equipment loan application, middleware application, data storage Shen
Please, database application, virtual machine application, the application of DNS domain name, operation system service request, inside ADSL networkings application, information are set
The contents such as standby application, data backup application.
In the present invention, cloud platform is responsible for pushing physical machine monitoring data, and virtual machine monitoring information is acquired by IMS, is based on
Cloud resource manages the innovative usage of system and IMS systems, the virtual resource flexible scheduling of connected applications performance indicator monitoring data
Implementation method includes the following steps：
1) temporally scheduling and the configuration by the elastic pond scheduling rule of operation system index scheduling needs progress；
2) it is scheduled based on elastic pond scheduling rule；
The step 2) includes step in detail below：
It 2-1) declares virtual machine queue to be launched and stops queue；
2-2) inquire available elastic pond；
2-3) judge scheduling rule, when for temporally scheduling rule, perform 2-3-1) time scheduling submethod；When to press
During operation system index scheduling rule, 2-3-2 is performed) operation system index scheduling submethod；
2-4) circular treatment step 2-3) the judgement scheduling rule；
2-5) start all virtual machines of queue to be launched；
2-6) stop all virtual machines of queue to be stopped；
2-7) finishing scheduling.
The drawbacks of solving the hardware resource waste present in the prior art, is combined using cloud computing technology and IMS systems
Management platform, by IMS systems to the real time monitoring of information system, based on elastic calculation technology, to each application system into
The rational hardware distribution of row, and the present invention is provided based on this management platform, using flexible scheduling rule, industry can be significantly reduced
Waste of the business system to hardware resource, effectively reduces cost, and system can be managed collectively by cloud computing basic platform,
The workload of operation maintenance personnel is greatly alleviated, effectively saves human cost.
Embodiment 2：
The present embodiment is further optimized based on the above embodiments, further, to better implement the present invention,
The step 2-3-1) including step in detail below：
2-3-1-1) the virtual machine operation number of units of rule searching configuration；
The virtual machine in elastic pond 2-3-1-2) is inquired in a manner that start and stop ascending order arranges；
2-3-1-3) virtual machine is classified as stopping list and runs list；
2-3-1-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, is put into list to be stopped；When the virtual machine operation number of units of rule configuration and the operation of practical virtual machine
When number of units is identical, it will not dispatch；When the virtual machine operation number of units of rule configuration, which is more than practical virtual machine, runs number of units, from stopping
Number of units virtual machine obtained by only taking out the difference between rule configuration and reality in list in turn, is put into list to be launched；
It 2-3-1-5) returns and performs step 2-4).
Embodiment 3：
The present embodiment is advanced optimized on the basis of any of the above-described embodiment, further, preferably to realize this
Invention, the step 2-3-2) including step in detail below：
2-3-2-1) the virtual machine operation number of units of rule searching configuration；
2-3-2-2) inquire the virtual machine in elastic pond；
2-3-2-3) virtual machine is classified as stopping list and runs list；
2-3-2-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into list to be stopped；When
When the virtual machine operation number of units of rule configuration is identical with practical virtual machine operation number of units, it will not dispatch；When the void of rule configuration
Plan machine operation number of units takes out in turn between rule configuration and reality when being more than practical virtual machine operation number of units from stopping list
Difference obtained by number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into row to be launched
Table；
It 2-3-2-5) returns and performs step 2-4).
Embodiment 4：
The present embodiment is further optimized based on the above embodiments, further, to better implement the present invention,
The step 1) includes step in detail below：
1-1) configuration starts, and increases elasticity pond newly；
Scheduling rule 1-2) is specified, divides 1-2-1) by the scheduling of operation system index and 1-2-2) temporally dispatch；
The step 1-2-1) including step in detail below：
1-2-1-1) specified services system；
1-2-1-2) specify the resource pool of extraction service system monitoring data；
The virtual machine of elastic pond schedulable 1-2-1-3) is configured；
1-2-1-4) distribu-tion index scheduling rule；
The step 1-2-2) including step in detail below：
The virtual machine of elastic pond schedulable 1-2-2-1) is configured；
1-2-2-2) configuration virtual machine start and stop sequence；
1-2-2-3) setup time scheduling rule；
1-3) configuration terminates.
Embodiment 5：
The present embodiment is advanced optimized on the basis of embodiment 1 or 2, further, to better implement the present invention,
The step 1) includes step in detail below：
1-1) configuration starts, and increases elasticity pond newly；
Scheduling rule 1-2) is specified, is divided by 1-2-1) operation system index is dispatched and 1-2-2) temporally dispatch；
The step 1-2-1) including step in detail below：
1-2-1-1) specified services system；
1-2-1-2) specify the resource pool of extraction service system monitoring data；
The virtual machine of elastic pond schedulable 1-2-1-3) is configured；
1-2-1-4) distribu-tion index scheduling rule；
The step 1-2-2) including step in detail below：
The virtual machine of elastic pond schedulable 1-2-2-1) is configured；
1-2-2-2) configuration virtual machine start and stop sequence；
1-2-2-3) setup time scheduling rule；
1-3) configuration terminates.
Embodiment 6：
The present embodiment is advanced optimized on the basis of any of the above-described embodiment, as shown in Fig. 3,4,5,6,7, with reference to should
With the virtual resource flexible scheduling implementation method of performance indicator monitoring data, include the following steps：
1) temporally scheduling and the configuration by the elastic pond scheduling rule of operation system index scheduling needs progress；
1-1) configuration starts, and increases elasticity pond newly；
Scheduling rule 1-2) is specified, is divided by 1-2-1) operation system index is dispatched and 1-2-2) temporally dispatch；
The step 1-2-1) scheduling of operation system index, including step in detail below：
1-2-1-1) specified services system；
1-2-1-2) specify the resource pool of extraction service system monitoring data；
The virtual machine of elastic pond schedulable 1-2-1-3) is configured；
1-2-1-4) distribu-tion index scheduling rule；Such as:Such as：SESSION>50 3 nodes of operation；SESSION>100 operation, 5 section
Point.System automatic inquiry can need the elastic pond dispatched every 15 minutes, then to each pond according to rule-based scheduling.
After such configuration method, operational indicator：Such as virtual machine CPU and memory usage, rule can be set such as：When
When virtual machine average CPU utilization reaches 80%, then start the corresponding new void of service application clustered node in flexible scheduling pond
Plan machine is to reduce the utilization rate (such as the rule set as be reduced to 60%) of unit CPU.
The step 1-2-2) temporally dispatch, including step in detail below：
The virtual machine of elastic pond schedulable 1-2-2-1) is configured；
1-2-2-2) configuration virtual machine start and stop sequence；
1-2-2-3) setup time scheduling rule；Such as:8 points of 3 nodes of operation, 13 points of 5 nodes of operation, system can be every 15 points
Clock inquires the elastic pond for needing to dispatch automatically, then to each pond according to rule-based scheduling.
IMS systems can count each operation system at what time section user service condition and operation system to the need of resource
It pleads condition, thus can analyze the resource utilization of virtual machine in elastic pond；According to operation system load to resource requirement when
Between characteristic the start and stop of virtual machine and operation rule in elastic pond be set.
1-3) configuration terminates.
2) it is scheduled based on elastic pond scheduling rule；
The step 2) includes step in detail below：
It 2-1) declares virtual machine queue to be launched and stops queue；
2-2) inquire available elastic pond；
2-3) circular treatment step 2-4) the judgement scheduling rule；
2-4) judge scheduling rule, when for temporally scheduling rule, perform 2-3-1) time scheduling submethod；When to press
During operation system index scheduling rule, 2-3-2 is performed) operation system index scheduling submethod；
2-3-1-1) the virtual machine operation number of units of rule searching configuration；
The virtual machine in elastic pond 2-3-1-2) is inquired in a manner that start and stop ascending order arranges；
2-3-1-3) virtual machine is classified as stopping list and runs list；
2-3-1-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, is put into list to be stopped；When the virtual machine operation number of units of rule configuration and the operation of practical virtual machine
When number of units is identical, it will not dispatch；When the virtual machine operation number of units of rule configuration, which is more than practical virtual machine, runs number of units, from stopping
Number of units virtual machine obtained by only taking out the difference between rule configuration and reality in list in turn, is put into list to be launched；
It 2-3-1-5) returns and performs step 2-4).
2-3-2-1) the virtual machine operation number of units of rule searching configuration；
2-3-2-2) inquire the virtual machine in elastic pond；
2-3-2-3) virtual machine is classified as stopping list and runs list；
2-3-2-4) practical plan operation number and the plan operation number of rule configuration, when the virtual machine of rule configuration
When running number of units less than practical virtual machine operation number of units, inverted order takes out the difference between reality and rule configuration from operation list
Value gained number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into list to be stopped；When
When the virtual machine operation number of units of rule configuration is identical with practical virtual machine operation number of units, it will not dispatch；When the void of rule configuration
Plan machine operation number of units takes out in turn between rule configuration and reality when being more than practical virtual machine operation number of units from stopping list
Difference obtained by number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into row to be launched
Table；
It 2-3-2-5) returns and performs step 2-4).
2-5) start all virtual machines of queue to be launched；
2-6) stop all virtual machines of queue to be stopped；
2-7) finishing scheduling.
The present invention realizes the combination of elastic calculation and operation system, effectively save hardware cost；It is put down by cloud computing management
Platform can be managed collectively the resilient expansion of operation system, facilitate O＆M；Using cloud computing technology mode, conventional deployment is compared
Mode extends more flexible, conveniently.
In the present invention, the positioning of IMS systems is system Centralized Monitoring and operation management, and cloud resource manages the positioning of system
It is the unified management, scheduling, control of IT infrastructure resource.From the point of view of operating level, cloud resource management system more focuses on resource
Automatic management and control, IMS more focuses on the system operation of system and the compliance inspection safeguarded.The two is in positioning and function
It is different in range, but there are certain interactions.
IMS systems are based on the synchronous and shared data integration of data：
In data integration level, the scheduling of resource adapter (being deployed in resource pool local) and sheet of system are managed by cloud resource
Ground IMS communicates.Cloud resource manages system and the monitoring information of physical machine and virtual machine is pushed to IMS, and obtains and answer from IMS
Use monitoring information；Cloud resource manages system to IMS system synchronizations physical asset and the information of fictitious assets simultaneously, and realizing two is
Data between system are consistent.The data of physical asset are proofreaded based on IMS using the data of cloud resource management system；
Fictitious assets information is subject to cloud resource management system.
Process integration of the IMS systems based on BPM：
In Process integration level, Process integration is carried out using the unified Process integration platform SoTower BPM of enterprise, will be transported
Flow and automatic flow concatenation are tieed up, realizes resource bid management, using collection such as upper and lower wire management, operational management and change managements
Into function, and then realize that IT infrastructure resource manages end to end.
Cloud resource management platform and general headquarters' BPM direct communications dispose flow using the BPM of general headquarters.Original flow is transformed in IMS
(PI3000 realizations), all flows are all initiated by cloud resource management system, when the activity that IMS systems in need participate in, with
The mode of WebService triggers the flow execution that net saves IMS systems, after waiting the flow that nets save, then with WebService's
Mode returns to handling result, and the remaining step of flow is completed in cloud resource management system.
As shown in figure 3, resource bid and establishment：Cloud resource manages system (BPM flows) level, and user proposes resource Shen
Please, transmission flow, Resource Manager examination ＆ approval, if not passing through, returns to unsanctioned reason, unsanctioned reason is returned to use
Flow is then terminated at family；IMS (PI3000 flows) level is saved in net, when Resource Manager is examined, is passed through according to regional information
The IMS flows that the corresponding net of WebSercie triggerings saves, will automatically generate work ticket, operation order according to user resources application, send
After flow, operation management person's examination ＆ approval, WebSercie is returned the result, and automatically creates resource needed for user, then terminates flow.
Interface of the IMS systems based on integration tools such as portals integrates：
Cloud resource is managed into system and IMS accesses enterprise portal, realizes single-sign-on；All Pending tasks are pushed simultaneously
To portal, the centralized management of Pending tasks is realized.
It when needed, can be by the monitoring information of IMS and the resource pool information and resource scheduling information of cloud resource management system
All be linked into letter tune center shows large-size screen monitors, realizes that the integrated of information shows.
The present invention solves the drawbacks of hardware resource waste present in the prior art, utilizes cloud computing technology and IMS systems
The management platform being combined, by IMS systems to the real time monitoring of information system, based on elastic calculation technology, to each application
System carries out rational hardware distribution, using flexible scheduling rule, can be significantly reduced wave of the operation system to hardware resource
Take, effectively reduce cost, system can be managed collectively by cloud computing basic platform, greatly alleviate operation maintenance personnel
Workload, effectively save human cost.
The above is only presently preferred embodiments of the present invention, not does limitation in any form to the present invention, it is every according to
According to the present invention technical spirit above example is made any simple modification, equivalent variations, each fall within the present invention protection
Within the scope of.
Claims (2)
1. the virtual resource flexible scheduling implementation method of connected applications performance indicator monitoring data, it is characterised in that：Including following
Step：
1）Temporally scheduling and the configuration by the elastic pond scheduling rule of operation system index scheduling needs progress；
2）It is scheduled based on elastic pond scheduling rule；
The step 2）Including step in detail below：
2-1）Declare virtual machine queue to be launched and virtual machine queue to be stopped；
2-2）Inquire available elastic pond；
2-3）Judge scheduling rule, when for temporally scheduling rule, perform 2-3-1）Time scheduling submethod；When for the business of pressing
During system index scheduling rule, 2-3-2 is performed）Operation system index dispatches submethod；
2-4）Circular treatment step 2-3）The judgement scheduling rule；
2-5）Start all virtual machines of virtual machine queue to be launched；
2-6）Stop all virtual machines of virtual machine queue to be stopped；
2-7）Finishing scheduling；
The step 2-3-1）Including step in detail below：
2-3-1-1）The operation number of rule searching configuration；
2-3-1-2）The virtual machine in elastic pond is inquired in a manner that start and stop ascending order arranges；
2-3-1-3）Virtual machine is classified as stopping list and runs list；
2-3-1-4）Compare practical plan operation number and the plan operation number of rule configuration, when the virtual machine operation of rule configuration
When number of units is less than practical virtual machine operation number of units, inverted order takes out the practical difference institute between rule configuration from operation list
Number of units virtual machine is obtained, is put into list to be stopped；When the virtual machine operation number of units of rule configuration and practical virtual machine run number of units
When identical, it will not dispatch；When the virtual machine operation number of units that rule is configured, which is more than practical virtual machine, runs number of units, arranged from stopping
Number of units virtual machine obtained by taking out the difference between rule configuration and reality in table in turn, is put into list to be launched；
2-3-1-5）It returns and performs step 2-4）；
The step 2-3-2）Including step in detail below：
2-3-2-1）The virtual machine operation number of units of rule searching configuration；
2-3-2-2）The virtual machine in the elastic pond of inquiry；
2-3-2-3）Virtual machine is classified as stopping list and runs list；
2-3-2-4）Compare practical plan operation number and the plan operation number of rule configuration, when the virtual machine operation of rule configuration
When number of units is less than practical virtual machine operation number of units, inverted order takes out the practical difference institute between rule configuration from operation list
Number of units virtual machine is obtained, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into list to be stopped；Work as rule
When the virtual machine operation number of units of configuration is identical with practical virtual machine operation number of units, it will not dispatch；When the virtual machine of rule configuration
When running number of units more than practical virtual machine operation number of units, take out rule in turn from stopping list and be configured and the difference between reality
Value gained number of units virtual machine, the virtual machine in notebook data center is preferentially selected when selecting virtual machine, is put into list to be launched；
2-3-2-5）It returns and performs step 2-4）.
2. the virtual resource flexible scheduling implementation method of connected applications performance indicator monitoring data according to claim 1,
It is characterized in that：The step 1）Include step in detail below：
1-1）Configuration starts, and increases elasticity pond newly；
1-2）Specified scheduling rule, divides 1-2-1）By the scheduling of operation system index and 1-2-2）Temporally dispatch；
The step 1-2-1）Including step in detail below：
1-2-1-1）Specified services system；
1-2-1-2）The resource pool of specified extraction service system monitoring data；
1-2-1-3）The virtual machine of the elastic pond schedulable of configuration；
1-2-1-4）Distribu-tion index scheduling rule；
The step 1-2-2）Including step in detail below：
1-2-2-1）The virtual machine of the elastic pond schedulable of configuration；
1-2-2-2）Virtual machine start and stop sequence is configured；
1-2-2-3）Setup time scheduling rule；
1-3）Configuration terminates.
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| CN106951564A (en) * | 2017-04-02 | 2017-07-14 | 北京军秀咨询有限公司 | A kind of cloud computing platform analyzed based on data mining and big data and method |
| CN111475217B (en) * | 2020-04-20 | 2021-03-23 | 广州市品高软件股份有限公司 | SDN-based service group start-stop method and system |
| CN112506625B (en) * | 2020-11-16 | 2024-03-12 | 国家卫星气象中心(国家空间天气监测预警中心) | Automatic start-stop control method for business |
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