CN109933501A - A kind of capacity evaluating method and device of application system - Google Patents
A kind of capacity evaluating method and device of application system Download PDFInfo
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Abstract
The embodiment of the present invention provides the capacity evaluating method and device of a kind of application system.The described method includes: acquiring the corresponding capacity parameter of multiple application levels that application system to be assessed includes；According to the capacity parameter, the capacity performance index of each application level is calculated according to preset capacity computation model；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；The capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level.Described device is for executing the above method.The capacity evaluating method and device of application system provided by the invention improve the accuracy of the Capacity Assessment of application system.
Description
Technical field
The present embodiments relate to the capacity evaluating methods and dress of field of computer technology more particularly to a kind of application system
It sets
Background technique
With IT system from traditional leveling style gradually to internet type impingement evolution, and virtualization and container is extensive
It uses, more acute challenge is proposed to funnel-shaped back-end system, support the control ability phase of background application system capacity
To weakness, easily occurs causing significant trouble because of capacity problem and resource divides unreasonable waste, therefore for application
The Capacity Assessment problem of system has been to be concerned by more and more people.
Under the conditions of the prior art, there is following two for the capacity evaluating method of application system at present: (1) being taken based on physics
The method that device composite performance index of being engaged in carries out Capacity Assessment, i.e., by the maximum performance index of each logic unit of calculating, or
Calculate at least any one index in the composite performance index value of separate unit physical server or physical server group, for pair
The whole volume of application system is assessed；(2) the Capacity Assessment monitoring of model on the capacity line of prediction is established based on real time capacity data
Method establishes model on the capacity line of prediction according to the real time capacity data of application system, according to model on the capacity line of prediction and
Preset pressure surveys capacity data under policy-simulative line, answers according to capacity data determination under the real time capacity data and line of application system
With the capacity deviant of system, and determine according to the real time capacity value and deviant of current time application system the line of application system
Upper capability value.But method (1) and method (2) are all to the Capacity Assessment in application system entirety level, Capacity Assessment standard
It is excessively macroscopical, and only focus on the capacity parameter of physics class, in addition existing capacity evaluating method is when carrying out capacity pressure and surveying one
As use traditional artificial pressure survey mode, will also result in certain hysteresis effect to Capacity Assessment.In conclusion existing capacity
Appraisal procedure exerts a certain influence to the accuracy of Capacity Assessment.
It is therefore proposed that a kind of method is that current industry is urgently to be resolved come the accuracy for improving the Capacity Assessment of application system
Important topic.
Summary of the invention
For the defects in the prior art, the embodiment of the present invention provides the capacity evaluating method and dress of a kind of application system
It sets.
On the one hand, the embodiment of the present invention provides a kind of capacity evaluating method of application system, comprising:
Acquire the corresponding capacity parameter of multiple application levels that application system to be assessed includes；
According to the capacity parameter, the capacity performance index of each application level is calculated according to preset capacity computation model；Institute
Stating preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；
The capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level.
On the other hand, the embodiment of the present invention provides a kind of Capacity Assessment device of application system, including acquisition unit, calculating
Unit and assessment unit, in which:
Acquisition unit is for acquiring the corresponding capacity parameter of multiple application levels that application system to be assessed includes；
Computing unit is used to calculate each application level according to preset capacity computation model according to the capacity parameter
Capacity performance index；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；
Assessment unit is used to calculate the capacity of the application system to be assessed according to the capacity performance index of each application level
Index.
Another aspect, the embodiment of the present invention provide a kind of electronic equipment, including processor, memory and bus, in which:
The processor, the memory complete mutual communication by bus；
The processor can call the computer program in memory, the step of to execute the above method.
In another aspect, the embodiment of the present invention provides a kind of computer readable storage medium, it is stored thereon with computer program,
The step of above method is realized when the program is executed by processor.
The capacity evaluating method and device of application system provided in an embodiment of the present invention, by according to collected to be assessed
The corresponding capacity parameter of multiple application levels that application system includes calculates each application layer according to preset capacity computation model
The capacity performance index of grade, and the capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level,
Improve the accuracy of the Capacity Assessment of application system.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the flow diagram of the capacity evaluating method of application system provided in an embodiment of the present invention；
Fig. 2 is the structural schematic diagram of the Capacity Assessment device of application system provided in an embodiment of the present invention；
Fig. 3 is electronic equipment entity apparatus structural schematic diagram provided in an embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical solution in the embodiment of the present invention is explicitly described, it is clear that described embodiment is the present invention
A part of the embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not having
Every other embodiment obtained under the premise of creative work is made, shall fall within the protection scope of the present invention.
Fig. 1 is the flow diagram of the capacity evaluating method of application system provided in an embodiment of the present invention, as shown in Figure 1,
The present embodiment provides a kind of capacity evaluating methods of application system, comprising:
The corresponding capacity parameter of multiple application levels that S101, acquisition application system to be assessed include；
Specifically, the Capacity Assessment device of application system is respectively from the infrastructure services of the application system to be assessed
(Infrastructure as a service, SaaS) platform, platform service (Platform as a service, PaaS) are flat
Platform and software service (Software as a service, IaaS) platform, acquire multiple applications that application system to be assessed includes
The corresponding capacity parameter of level；Wherein, the application level may include WWW (WEB) service layer, cache layer, database company
Layer and multiple common layers are connect, can also include multiple physical layers, specifically can be configured and adjust according to the actual situation, herein
It is not specifically limited；The capacity parameter may include instance number, and the connection of the Thread Count, database connection pool of each example is joined
Several and physical parameter (such as memory size, CPU ability) etc. can also include other capacity parameters, specifically can be according to reality
Situation is configured and adjusts, and is not specifically limited herein；It should be noted that the corresponding capacity parameter of different application level can
Cannot it not had to identical yet.
S102, according to the capacity parameter, refer to according to the capacity that preset capacity computation model calculates each application level
Mark；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；
Specifically, described device calculates each application layer according to preset capacity computation model according to the capacity parameter
The capacity performance index of grade；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level.Its
In, the capacity parameter includes dynamic capacity parameter and static capacity parameter, and correspondingly, the capacity performance index includes using in real time
Capacity and intrinsic capacity.
S103, the capacity performance index that the application system to be assessed is calculated according to the capacity performance index of each application level.
Specifically, described device calculates multiplying for the corresponding capacity weighted value of capacity performance index of each application level
Product, using the corresponding capacity performance index of the maximum value of the product as the capacity performance index of the application system to be assessed, described device
The capacity performance index for the application system to be assessed being calculated can also be shown by display device.The capacity power
Weight values are configured according to influence degree of each application level to the capacity of the application system to be assessed, specifically may be used
To be configured and adjust according to the actual situation, it is not specifically limited herein.
The capacity evaluating method of application system provided in an embodiment of the present invention, by according to collected application system to be assessed
The corresponding capacity parameter of multiple application levels that system includes, the appearance of each application level is calculated according to preset capacity computation model
Figureofmerit, and the capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level, it improves
The accuracy of the Capacity Assessment of application system.
On the basis of the above embodiments, further, the capacity parameter includes dynamic capacity parameter and static capacity
Parameter；Correspondingly, described according to the capacity parameter, the capacity of each application level is calculated according to preset capacity computation model
Index, comprising:
According to the corresponding dynamic capacity parameter of each application level, calculated according to the preset capacity computation model
The real-time of each application level uses capacity；
According to the corresponding static capacity parameter of each application level, calculated according to the preset capacity computation model
The intrinsic capacity of each application level.
Specifically, described device is according to the corresponding dynamic capacity parameter of each application level, according to described default
Calculation of capacity model calculates the real-time of each application level and uses capacity, and corresponding described quiet according to each application level
State capacity parameter calculates the intrinsic capacity of each application level according to the preset capacity computation model.It is understood that
The static capacity parameter refers to the deployment parameters of each application level of application system to be assessed, instance number including deployment,
The Thread Count of the example of each deployment, the Connecting quantity of the database connection pool of deployment, physical parameter of deployment etc., usually
With 24 hours or to carry out capacity pressure survey acquisition for the period within one week and be stored in static database, described device passes through access institute
State the corresponding static capacity parameter of each application level that static database acquires the application system to be assessed；The dynamic
Capacity parameter refers to the currently used situation of each application level of application system to be assessed, including real time traffic, and thread is real
When use number, the real-time Connecting quantity of database connection pool, the real-time usage amount of memory, real-time utilization rate of CPU etc., these indexs
It is fluctuating always at any time, is needing to acquire in real time.
On the basis of the above embodiments, further, the method also includes:
Survey mechanism is pressed according to the corresponding preconfigured capacity of each application level of application system to be assessed, respectively to institute
It states each application level and carries out capacity pressure survey, obtain the static capacity parameter of each application level；The capacity presses survey mechanism packet
It includes capacity pressure and surveys time window and capacity pressure survey strategy.
Specifically, week of the described device previously according to the historical capacity of the different application level of the application system to be assessed
Phase property fluctuation pattern, the capacity pressure being respectively configured for different application level surveys time window and capacity pressure survey strategy, so that institute
It states device and executes the corresponding capacity pressure survey strategy of the application level in the corresponding capacity pressure survey time window of each application level, constantly
It initiates to access the impact of the application level, generates the peak traffic in the short time, to realize to the application level capacity
The bottleneck of parameter is known the real situation, and can be obtained the static capacity parameter of the application level.Wherein, capacity is pressed and surveys matching for time window
Set principle and be mainly to try to the trough period that selection application level is called and is accessed by the user, and the trough period have the time it is long,
The strong feature of periodic feature avoids the normal use to the application level to realize while carrying out capacity pressure survey as far as possible
Influence produced；The equipping rules that the capacity pressure surveys strategy are the particularity for considering each application level and locating application ring
Border factor, selection is suitble to the corresponding capacity pressure of different application levels to survey strategy, for example, with conventional browser/server mode
For the application system of (Browser/Server, B/S) framework, it can mainly be initiated by pressure survey tool to core at WEB layers
The access of service URL utilizes the business conduct of the form simulation actual user of class browser；In Enterprise Service Bus
(Enterprise Service Bus, ESB) layer can directly initiate the calling to ESB interface by tool, utilize test work
Number send batch ESB request message, realize ESB layer directly press survey.
On the basis of the above embodiments, further, the application level includes WEB service layer, the WEB service layer
Corresponding capacity parameter includes the example sum of the WEB service layer, the Thread Count of each example of the WEB service layer；Accordingly
Ground, described that the capacity performance index of each application level is calculated according to preset capacity computation model according to the capacity parameter, packet
It includes:
According to formula: CWEB=NWEB-ins×NWEB-thr×PW×QW, calculate the capacity performance index of the WEB service layer；Wherein,
CWEBFor the capacity performance index of the WEB service layer, NWEB-insFor the example sum of the WEB service layer, NWEB-thrFor WEB clothes
The Thread Count of each example of business layer, PWThreshold value, Q are protected for threadWFor High Availabitity baseline threshold.
Specifically, the application level includes WEB service layer, may include Web Logic server (for developing, collecting
At, dispose and manage the Java application server of large-scale distributed Web application, network application and database application), tom cat clothes
The WEB servers such as business device (Tomcat), specifically can be configured and adjust according to the actual situation, be not specifically limited herein；
The corresponding capacity parameter of the WEB service layer includes the example sum of the WEB service layer, each example of the WEB service layer
Thread Count, can also include other capacity parameters, specifically can be configured and adjust according to the actual situation, not do and have herein
Body limits.Described device is according to formula: CWEB=NWEB-ins×NWEB-thr×PW×QW, the capacity for calculating the WEB service layer refers to
Mark；Wherein, CWEBFor the capacity performance index of the WEB service layer, NWEB-insFor the example sum of the WEB service layer, NWEB-thrFor
The Thread Count of each example of the WEB service layer, PWThreshold value, Q are protected for threadWFor High Availabitity baseline threshold.Wherein, the line
Journey protection threshold value and High Availabitity baseline threshold be it is rule of thumb pre-set, can specifically be configured according to the actual situation and
Adjustment, is not specifically limited herein.It should be noted that the corresponding capacity parameter of the WEB service layer can be static capacity
Parameter is also possible to dynamic capacity parameter, when the static capacity parameter (portion that the capacity parameter of input is the WEB service layer
The Thread Count of total, deployment each example of the example of administration) when, the capacity performance index for calculating acquisition is the intrinsic of the WEB service layer
Capacity；When dynamic capacity parameter that the capacity parameter of input is the WEB service layer (currently used example sum, when
The Thread Count of the preceding each example used) when, the capacity performance index for calculating acquisition is that the real-time of the WEB service layer uses capacity.
On the basis of the above embodiments, further, the application level includes cache layer, and the cache layer is corresponding
Capacity parameter includes the example sum of the cache layer, the Thread Count of each example of the cache layer；Correspondingly, described
According to the capacity parameter, the capacity performance index of each application level is calculated according to preset capacity computation model, comprising:
According to formula: Ccac=Ncac-ins×Ncac-thr×Pc, calculate the capacity performance index of the cache layer；Wherein, CcacFor institute
State the capacity performance index of cache layer, Ncac-insFor the example sum of the cache layer, Ncac-thrFor the line of each example of the cache layer
Number of passes, PcFor the concurrent threshold value of single interface of the cache layer.
Specifically, the application level includes cache layer, and the cache layer may include Coherence permission caching mould
Block, distributed memory target cache system (Memcached), ActiveMQ storage module, Redis storage module etc., specifically may be used
To be configured and adjust according to the actual situation, it is not specifically limited herein；The corresponding capacity parameter of the cache layer includes institute
The example sum of cache layer is stated, the Thread Count of each example of the cache layer can also include other capacity parameters, specifically
It can be configured and adjust according to the actual situation, be not specifically limited herein.Described device is according to formula: Ccac=Ncac-ins
×Ncac-thr×Pc, calculate the capacity performance index of the cache layer；Wherein, CcacFor the capacity performance index of the cache layer, Ncac-insFor
The example sum of the cache layer, Ncac-thrFor the Thread Count of each example of the cache layer, PcFor single interface of the cache layer
Concurrent threshold value.Wherein, the concurrent threshold value of single interface of the cache layer is the number of threads of the cache layer concurrent invocation list interface
Maximum value, be it is rule of thumb pre-set, specifically can be configured and adjust according to the actual situation, not do herein specific
It limits.It should be noted that the corresponding capacity parameter of the cache layer can be static capacity parameter and be also possible to dynamic capacity
Parameter, when input the capacity parameter be the cache layer static capacity parameter (deployment example sum, deployment each reality
The Thread Count of example) when, the capacity performance index for calculating acquisition is the intrinsic capacity of the cache layer；When the capacity parameter of input is
When dynamic capacity parameter (Thread Count of currently used example sum, currently used each example) of the cache layer, calculate
The capacity performance index of acquisition is that the real-time of the cache layer uses capacity.
On the basis of the above embodiments, further, the application level includes database articulamentum, the database
The corresponding capacity parameter of articulamentum includes the physical connection number of the corresponding connection pool of the database articulamentum, and the database connects
Connect the maximum activity connection number of the corresponding connection pool of layer；Correspondingly, described according to the capacity parameter, it is calculated according to preset capacity
Model calculates the capacity performance index of each application level, comprising:
According to formula: Cdb=max { Nphy,Npool-max, calculate the capacity performance index of the database articulamentum；Wherein, Cdb
For the capacity performance index of the database articulamentum, NphyFor the physical connection number of the corresponding connection pool of the database articulamentum,
Npool-maxFor the maximum activity connection number of the corresponding connection pool of the database articulamentum.
Specifically, the application level includes database articulamentum, the database articulamentum include DACP connection pool and
C3P0 connection pool etc. specifically can be configured and adjust according to the actual situation, be not specifically limited herein；The database connects
Connect the physical connection number that the corresponding capacity parameter of layer includes the corresponding connection pool of the database articulamentum, the database connection
The maximum activity connection number of the corresponding connection pool of layer can also include other capacity parameters, specifically can according to the actual situation into
Row setting and adjustment, are not specifically limited herein.Described device is according to formula: Cdb=max { Nphy,Npool-max, described in calculating
The capacity performance index of database articulamentum；Wherein, CdbFor the capacity performance index of the database articulamentum, NphyFor database company
Meet the physical connection number of the corresponding connection pool of layer, Npool-maxFor the maximum activity of the corresponding connection pool of the database articulamentum
Connection number.It should be noted that the corresponding capacity parameter of the database articulamentum can be static capacity parameter and be also possible to
Dynamic capacity parameter, when the static capacity parameter (connection of deployment that the capacity parameter of input is the database articulamentum
The maximum activity connection number of the physical connection number in pond, the connection pool of deployment) when, the capacity performance index for calculating acquisition is the database
The intrinsic capacity of articulamentum；When the dynamic capacity parameter that the capacity parameter of input is the database articulamentum (currently makes
The maximum activity connection number of the physical connection number of connection pool, currently used connection pool) when, calculate the capacity performance index of acquisition
Real-time for the database articulamentum uses capacity.
On the basis of the above embodiments, further, the application level includes multiple common layers, each common layer
Corresponding capacity parameter includes the example sum of each common layer, the Thread Count of each example of each common layer；Phase
Ying Di, described that the capacity performance index of each application level is calculated according to preset capacity computation model according to the capacity parameter, packet
It includes:
According to formula:The capacity for calculating i-th of common layer refers to
Mark；Wherein,For the capacity performance index of i-th of common layer,It is total for the example of i-th of common layer,For the Thread Count of each example of i-th of common layer,Single interface for i-th of common layer line journey is concurrent
Threshold value,For the High Availabitity baseline threshold of i-th of common layer line journey,Capacity for i-th of common layer line journey refers to
Deviation ratio is marked, 1≤i≤n, n are the number of the common layer.
Specifically, the application level includes multiple common layers, and the corresponding capacity parameter of each common layer includes each institute
The example sum of common layer is stated, the Thread Count of each example of each common layer can also include other capacity parameters, tool
Body can be configured and adjust according to the actual situation, be not specifically limited herein.Described device is according to formula:Calculate the capacity performance index of i-th of common layer；Wherein,It is i-th
The capacity performance index of the common layer,It is total for the example of i-th of common layer,For i-th of common layer
Each example Thread Count,For the concurrent threshold value of single interface of i-th of common layer line journey,It is described common for i-th
The High Availabitity baseline threshold of layer line journey,For the capacity performance index deviation ratio of i-th of common layer line journey, 1≤i≤n, n are institute
State the number of common layer.Wherein,It is obtained to be calculated according to the corresponding deviation ratio function formula of each common layer, for example,
For HTTP layers, deviation ratio function formula using Euler's function as the common layer,Institute
The concurrent threshold value of single interface of cache layer is stated as the maximum value of the number of threads of the common layer concurrent invocation list interface, is according to warp
It tests pre-set, specifically can be configured and adjust according to the actual situation, be not specifically limited herein.It should illustrate
It is that the corresponding capacity parameter of each common layer can be static capacity parameter and be also possible to dynamic capacity parameter, when input
The capacity parameter is the static capacity parameter (Thread Count of total, deployment each example of the example of deployment) of the common layer
When, the capacity performance index for calculating acquisition is the intrinsic capacity of the common layer；When the capacity parameter of input is the common layer
Dynamic capacity parameter (Thread Count of currently used example sum, currently used each example) when, calculate the capacity of acquisition
Index is that the real-time of the common layer uses capacity.
On the basis of the above embodiments, further, described that institute is calculated according to the capacity performance index of each application level
State the capacity performance index of application system to be assessed, comprising:
According to formula:Calculate the capacity performance index of the application system to be assessed；Wherein, C is described
The capacity performance index of application system to be assessed, CjFor the capacity performance index of j-th of application level of the application system to be assessed, wjFor
The corresponding capacity weighted value of j-th of application level, 1≤j≤m, m are the number of the application level.
Specifically, described device is according to formula:The capacity for calculating the application system to be assessed refers to
Mark；Wherein, C is the capacity performance index of the application system to be assessed, CjFor j-th of application level of the application system to be assessed
Capacity performance index, wjFor the corresponding capacity weighted value of j-th of application level, 1≤j≤m, m are of the application level
Number.It is understood that the capacity weighted value is the capacity according to each application level to the application system to be assessed
Influence degree be configured, specifically can be configured and adjust according to the actual situation, be not specifically limited herein.
On the basis of the above embodiments, further, the method also includes:
Multiple capacity risk assessment parameters are chosen from the capacity parameter, and according to preset capacity risk computation model meter
Calculate the capacity risk score of each capacity risk assessment parameter；The capacity risk computation model includes each capacity risk
Assess the corresponding capacity risk score strategy of parameter；
The capacity of the application system to be assessed is calculated according to the capacity risk score of each capacity risk assessment parameter
Risk score；
If judgement knows that the capacity risk score of the application system to be assessed is greater than preset threshold, warning note is issued
Signal.
Specifically, described device chooses multiple capacity risk assessment parameters from the capacity parameter, and according to default appearance
The corresponding capacity risk score strategy of each capacity risk assessment parameter that amount risk computation model includes, calculates each appearance
The capacity risk score of risk assessment parameter is measured, and institute is calculated according to the capacity risk score of each capacity risk assessment parameter
The capacity risk score for stating application system to be assessed knows that the capacity risk score of the application system to be assessed is greater than in judgement
Alarm alert signal is issued when preset threshold, so that staff is handled in time.It is understood that the capacity risk
Assessment parameter can be the selection from the capacity parameter to the biggish capacity parameter of capacity venture influence, be also possible to complete
The capacity parameter in portion specifically can be configured and adjust according to the actual situation, be not specifically limited herein；The preset threshold
It can also be configured and adjust according to the actual situation, be not specifically limited herein.
On the basis of the above embodiments, further, described each described according to the calculating of preset capacity risk computation model
The capacity risk score of capacity risk assessment parameter, comprising:
According to formula:Calculate each capacity risk assessment parameter
Capacity risk score；Wherein, f (xk) be k-th of capacity risk assessment parameter capacity risk score, xkFor k-th of capacity risk
Assess the value of parameter, R1And R2For preset fraction fragmentation threshold, λ is preset fraction growth rate,WithFor k-th of capacity
The corresponding parameter preset fragmentation threshold of risk assessment parameter, R1< R2,1≤k≤K, K are the capacity risk
Assess the number of parameter.
Specifically, described device is according to formula:Calculate each appearance
Measure the capacity risk score of risk assessment parameter；Wherein, f (xk) be k-th of capacity risk assessment parameter capacity risk score,
xkFor the value of k-th of capacity risk assessment parameter, R1And R2For preset fraction fragmentation threshold, λ is preset fraction growth rate,WithFor the corresponding parameter preset fragmentation threshold of k-th of capacity risk assessment parameter, R1< R2, 1
≤ k≤K, K are the number of the capacity risk assessment parameter.It is understood that the preset fraction fragmentation threshold, default point
Number growth rate and parameter preset fragmentation threshold are pre-set, and be can be adjusted according to the actual situation, and are not done herein
It is specific to limit；The corresponding parameter preset fragmentation threshold of different capacity risk assessment parameters is different.
On the basis of the above embodiments, further, the capacity wind according to each capacity risk assessment parameter
Dangerous score calculates the capacity risk score of the application system to be assessed, comprising:
According to formula:Calculate the capacity risk score of the application system to be assessed；Wherein, F is
The capacity risk score of the application system to be assessed, xkFor the value of k-th of capacity risk assessment parameter, f (xk) it is k-th of appearance
Measure the capacity risk score of risk assessment parameter, ηkFor the Risk rated ratio value of k-th of capacity risk assessment parameter, K is the appearance
Measure the number of risk assessment parameter.
Specifically, described device is according to formula:Calculate the capacity wind of the application system to be assessed
Dangerous score；Wherein, F is the capacity risk score of the application system to be assessed, xkFor k-th capacity risk assessment parameter
Value, f (xk) be k-th of capacity risk assessment parameter capacity risk score, ηkFor the risk of k-th of capacity risk assessment parameter
Weighted value, K are the number of the capacity risk assessment parameter.It is understood that the Risk rated ratio value is according to the appearance
Amount risk assessment parameter is configured the influence degree of the capacity of the application system to be assessed, specifically can be according to reality
Situation is configured and adjusts, and is not specifically limited herein.
The capacity evaluating method of application system provided in an embodiment of the present invention, by according to collected application system to be assessed
The corresponding capacity parameter of multiple application levels that system includes, the appearance of each application level is calculated according to preset capacity computation model
Figureofmerit, and the capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level, and calculate
The capacity risk score of the application system to be assessed issues warning note when the capacity risk score is greater than preset threshold
Signal improves the accuracy of the Capacity Assessment of application system.
Fig. 2 is the structural schematic diagram of the Capacity Assessment device of application system provided in an embodiment of the present invention, as shown in Fig. 2,
The embodiment of the present invention provides a kind of Capacity Assessment device of application system, comprising: acquisition unit 201, computing unit 202 and assessment
Unit 203, in which:
Acquisition unit 201 is for acquiring the corresponding capacity parameter of multiple application levels that application system to be assessed includes；Meter
Unit 202 is calculated to be used to be referred to according to the capacity parameter according to the capacity that preset capacity computation model calculates each application level
Mark；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；Assessment unit 203 is used
In the capacity performance index for calculating the application system to be assessed according to the capacity performance index of each application level.
The Capacity Assessment device of application system provided in an embodiment of the present invention, by according to collected application system to be assessed
The corresponding capacity parameter of multiple application levels that system includes, the appearance of each application level is calculated according to preset capacity computation model
Figureofmerit, and the capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level, it improves
The accuracy of the Capacity Assessment of application system.
The embodiment of device provided by the invention specifically can be used for executing the process flow of above-mentioned each method embodiment,
Details are not described herein for function, is referred to the detailed description of above method embodiment.
Fig. 3 is electronic equipment entity apparatus structural schematic diagram provided in an embodiment of the present invention, as shown in figure 3, the electronics is set
Standby may include: processor (processor) 301, memory (memory) 302 and bus 303, wherein processor 301 is deposited
Reservoir 302 completes mutual communication by bus 303.Processor 301 can call the computer program in memory 302,
To execute following method: acquiring the corresponding capacity parameter of multiple application levels that application system to be assessed includes；According to the appearance
Parameter is measured, the capacity performance index of each application level is calculated according to preset capacity computation model；The preset capacity computation model
Including the corresponding capacity performance index calculative strategy of each application level；According to the calculating of the capacity performance index of each application level
The capacity performance index of application system to be assessed.
The embodiment of the present invention discloses a kind of computer program product, and the computer program product is non-transient including being stored in
Computer program on computer readable storage medium, the computer program include program instruction, when described program instructs quilt
When computer executes, computer is able to carry out method provided by above-mentioned each method embodiment, for example, acquisition is to be assessed to answer
The corresponding capacity parameter of multiple application levels for including with system；According to the capacity parameter, according to preset capacity computation model
Calculate the capacity performance index of each application level；The preset capacity computation model includes the corresponding capacity of each application level
Index calculative strategy；The capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level.
The embodiment of the present invention provides a kind of non-transient computer readable storage medium, the non-transient computer readable storage
Medium storing computer program, the computer program make the computer execute side provided by above-mentioned each method embodiment
Method, for example, acquire the corresponding capacity parameter of multiple application levels that application system to be assessed includes；Joined according to the capacity
Number, the capacity performance index of each application level is calculated according to preset capacity computation model；The preset capacity computation model includes
The corresponding capacity performance index calculative strategy of each application level；It is calculated according to the capacity performance index of each application level described to be evaluated
Estimate the capacity performance index of application system.
In addition, the logical order in above-mentioned memory 302 can be realized by way of SFU software functional unit and conduct
Independent product when selling or using, can store in a computer readable storage medium.Based on this understanding, originally
Substantially the part of the part that contributes to existing technology or the technical solution can be in other words for the technical solution of invention
The form of software product embodies, which is stored in a storage medium, including some instructions to
So that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation of the present invention
The all or part of the steps of example the method.And storage medium above-mentioned include: USB flash disk, mobile hard disk, read-only memory (ROM,
Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. it is various
It can store the medium of program code.
The apparatus embodiments described above are merely exemplary, wherein described, unit can as illustrated by the separation member
It is physically separated with being or may not be, component shown as a unit may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case where, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It realizes by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on
Stating technical solution, substantially the part that contributes to existing technology can be embodied in the form of software products in other words, should
Computer software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers
It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation
Method described in certain parts of example or embodiment.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (14)
1. a kind of capacity evaluating method of application system characterized by comprising
Acquire the corresponding capacity parameter of multiple application levels that application system to be assessed includes；
According to the capacity parameter, the capacity performance index of each application level is calculated according to preset capacity computation model；It is described pre-
If calculation of capacity model includes the corresponding capacity performance index calculative strategy of each application level；
The capacity performance index of the application system to be assessed is calculated according to the capacity performance index of each application level.
2. the method according to claim 1, wherein the capacity parameter includes dynamic capacity parameter and static appearance
Measure parameter；Correspondingly, described according to the capacity parameter, the appearance of each application level is calculated according to preset capacity computation model
Figureofmerit, comprising:
According to the corresponding dynamic capacity parameter of each application level, calculate according to the preset capacity computation model described in
The real-time of each application level uses capacity；
According to the corresponding static capacity parameter of each application level, calculate according to the preset capacity computation model described in
The intrinsic capacity of each application level.
3. the method according to claim 1, wherein the method also includes:
Survey mechanism is pressed according to the corresponding preconfigured capacity of each application level of application system to be assessed, respectively to described each
Application level carries out capacity pressure and surveys, and obtains the static capacity parameter of each application level；The capacity pressure survey mechanism includes holding
Amount pressure surveys time window and capacity pressure surveys strategy.
4. the WEB takes the method according to claim 1, wherein the application level includes WEB service layer
The corresponding capacity parameter of business layer includes the example sum of the WEB service layer, the Thread Count of each example of the WEB service layer；
It is correspondingly, described that the capacity performance index of each application level is calculated according to preset capacity computation model according to the capacity parameter,
Include:
According to formula: CWEB=NWEB-ins×NWEB-thr×PW×QW, calculate the capacity performance index of the WEB service layer；Wherein, CWEBFor
The capacity performance index of the WEB service layer, NWEB-insFor the example sum of the WEB service layer, NWEB-thrFor the WEB service layer
Each example Thread Count, PWThreshold value, Q are protected for threadWFor High Availabitity baseline threshold.
5. the method according to claim 1, wherein the application level includes cache layer, the cache layer pair
The capacity parameter answered includes the example sum of the cache layer, the Thread Count of each example of the cache layer；Correspondingly, institute
It states according to the capacity parameter, the capacity performance index of each application level is calculated according to preset capacity computation model, comprising:
According to formula: Ccac=Ncac-ins×Ncac-thr×Pc, calculate the capacity performance index of the cache layer；Wherein, CcacIt is described slow
Deposit the capacity performance index of layer, Ncac-insFor the example sum of the cache layer, Ncac-thrFor the thread of each example of the cache layer
Number, PcFor the concurrent threshold value of single interface of the cache layer.
6. the method according to claim 1, wherein the application level includes database articulamentum, the number
It include the physical connection number of the corresponding connection pool of the database articulamentum, the data according to the corresponding capacity parameter of library articulamentum
The maximum activity connection number of the corresponding connection pool of library articulamentum；Correspondingly, described according to the capacity parameter, according to preset capacity
Computation model calculates the capacity performance index of each application level, comprising:
According to formula: Cdb=max { Nphy,Npool-max, calculate the capacity performance index of the database articulamentum；Wherein, CdbFor institute
State the capacity performance index of database articulamentum, NphyFor the physical connection number of the corresponding connection pool of the database articulamentum, Npool-max
For the maximum activity connection number of the corresponding connection pool of the database articulamentum.
7. each described general the method according to claim 1, wherein the application level includes multiple common layers
The logical corresponding capacity parameter of layer includes the example sum of each common layer, the thread of each example of each common layer
Number；Correspondingly, described according to the capacity parameter, refer to according to the capacity that preset capacity computation model calculates each application level
Mark, comprising:
According to formula:Calculate the capacity performance index of i-th of common layer；Its
In,For the capacity performance index of i-th of common layer,It is total for the example of i-th of common layer,It is
The Thread Count of each example of the i common layers,For the concurrent threshold value of single interface of i-th of common layer line journey,For
The High Availabitity baseline threshold of i-th of common layer line journey,For the capacity performance index deviation ratio of i-th of common layer line journey, 1
≤ i≤n, n are the number of the common layer.
8. method described in -7 any one according to claim 1, which is characterized in that the appearance according to each application level
Figureofmerit calculates the capacity performance index of the application system to be assessed, comprising:
According to formula:Calculate the capacity performance index of the application system to be assessed；Wherein, C is described to be evaluated
Estimate the capacity performance index of application system, CjFor the capacity performance index of j-th of application level of the application system to be assessed, wjIt is described
The corresponding capacity weighted value of j-th of application level, 1≤j≤m, m are the number of the application level.
9. the method according to claim 1, wherein the method also includes:
Multiple capacity risk assessment parameters are chosen from the capacity parameter, and are calculated respectively according to preset capacity risk computation model
The capacity risk score of the capacity risk assessment parameter；The capacity risk computation model includes each capacity risk assessment
The corresponding capacity risk score strategy of parameter；
The capacity risk of the application system to be assessed is calculated according to the capacity risk score of each capacity risk assessment parameter
Score；
If judgement knows that the capacity risk score of the application system to be assessed is greater than preset threshold, warning note letter is issued
Number.
10. according to the method described in claim 9, it is characterized in that, described calculate respectively according to preset capacity risk computation model
The capacity risk score of the capacity risk assessment parameter, comprising:
According to formula:Calculate the capacity of each capacity risk assessment parameter
Risk score；Wherein, f (xk) be k-th of capacity risk assessment parameter capacity risk score, xkFor k-th of capacity risk assessment
The value of parameter, R1And R2For preset fraction fragmentation threshold, λ is preset fraction growth rate,WithFor k-th of capacity risk
Assess the corresponding parameter preset fragmentation threshold of parameter, R1< R2,1≤k≤K, K are the capacity risk assessment
The number of parameter.
11. method according to claim 9 or 10, which is characterized in that described according to each capacity risk assessment parameter
Capacity risk score calculate the capacity risk score of the application system to be assessed, comprising:
According to formula:Calculate the capacity risk score of the application system to be assessed；Wherein, F is described
The capacity risk score of application system to be assessed, xkFor the value of k-th of capacity risk assessment parameter, f (xk) it is k-th of capacity wind
The capacity risk score of danger assessment parameter, ηkFor the Risk rated ratio value of k-th of capacity risk assessment parameter, K is the capacity wind
The number of danger assessment parameter.
12. a kind of Capacity Assessment device of application system, which is characterized in that including acquisition unit, computing unit and assessment unit,
Wherein:
Acquisition unit is for acquiring the corresponding capacity parameter of multiple application levels that application system to be assessed includes；
Computing unit is used to calculate the capacity of each application level according to preset capacity computation model according to the capacity parameter
Index；The preset capacity computation model includes the corresponding capacity performance index calculative strategy of each application level；
Assessment unit is used to calculate the capacity performance index of the application system to be assessed according to the capacity performance index of each application level.
13. a kind of electronic equipment, which is characterized in that including processor, memory and bus, in which:
The processor, the memory complete mutual communication by bus；
The processor can call the computer program in memory, to execute as described in claim 1-11 any one
The step of method.
14. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
It realizes when execution such as the step of claim 1-11 any one the method.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110443785A (en) * | 2019-07-18 | 2019-11-12 | 太原师范学院 | The feature extracting method of three-dimensional point cloud under a kind of lasting people having the same aspiration and interest |
| CN110502431A (en) * | 2019-07-16 | 2019-11-26 | 阿里巴巴集团控股有限公司 | System service evaluating method, device and electronic equipment |
| CN110737593A (en) * | 2019-09-19 | 2020-01-31 | 平安科技（深圳）有限公司 | Intelligent capacity management method, device and storage medium |
| CN111428266A (en) * | 2019-09-05 | 2020-07-17 | 广州知弘科技有限公司 | Storage node space capacity and security evaluation method based on big data |
| CN113011138A (en) * | 2019-12-19 | 2021-06-22 | 北京懿医云科技有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103985068A (en) * | 2014-05-30 | 2014-08-13 | 湖南智仁科技有限公司 | Online risk evaluation method for power distribution network |
| WO2017000628A1 (en) * | 2015-06-30 | 2017-01-05 | 华为技术有限公司 | Resource scheduling method and apparatus for cloud computing system |
| CN106453549A (en) * | 2016-10-08 | 2017-02-22 | 中国工商银行股份有限公司 | Distributed software version release method and system thereof |
| CN106789955A (en) * | 2016-11-30 | 2017-05-31 | 山东省计算中心（国家超级计算济南中心） | A kind of network security situation evaluating method |
| CN107145995A (en) * | 2017-03-17 | 2017-09-08 | 北京市安全生产科学技术研究院 | Production environment safety prediction methods, devices and systems |
| CN107239907A (en) * | 2017-06-08 | 2017-10-10 | 清华大学 | Cities and towns integrate appraisal procedure, the device and system of Disaster-bearing ability |
-
2017
- 2017-12-15 CN CN201711347432.XA patent/CN109933501B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103985068A (en) * | 2014-05-30 | 2014-08-13 | 湖南智仁科技有限公司 | Online risk evaluation method for power distribution network |
| WO2017000628A1 (en) * | 2015-06-30 | 2017-01-05 | 华为技术有限公司 | Resource scheduling method and apparatus for cloud computing system |
| CN106453549A (en) * | 2016-10-08 | 2017-02-22 | 中国工商银行股份有限公司 | Distributed software version release method and system thereof |
| CN106789955A (en) * | 2016-11-30 | 2017-05-31 | 山东省计算中心（国家超级计算济南中心） | A kind of network security situation evaluating method |
| CN107145995A (en) * | 2017-03-17 | 2017-09-08 | 北京市安全生产科学技术研究院 | Production environment safety prediction methods, devices and systems |
| CN107239907A (en) * | 2017-06-08 | 2017-10-10 | 清华大学 | Cities and towns integrate appraisal procedure, the device and system of Disaster-bearing ability |
Non-Patent Citations (1)
| Title |
|---|
| 陈伟华: ""输电网规划方案的多层级组合模糊综合评价方法研究"", 《中国优秀硕士学位论文全文数据库（输电网规划方案的多层级组合模糊综合评价方法研究）》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110502431A (en) * | 2019-07-16 | 2019-11-26 | 阿里巴巴集团控股有限公司 | System service evaluating method, device and electronic equipment |
| CN110502431B (en) * | 2019-07-16 | 2023-01-17 | 创新先进技术有限公司 | System service evaluation method and device and electronic equipment |
| CN110443785A (en) * | 2019-07-18 | 2019-11-12 | 太原师范学院 | The feature extracting method of three-dimensional point cloud under a kind of lasting people having the same aspiration and interest |
| CN111428266A (en) * | 2019-09-05 | 2020-07-17 | 广州知弘科技有限公司 | Storage node space capacity and security evaluation method based on big data |
| CN111428266B (en) * | 2019-09-05 | 2020-11-27 | 温永宁 | Storage node space capacity and security evaluation method based on big data |
| CN110737593A (en) * | 2019-09-19 | 2020-01-31 | 平安科技（深圳）有限公司 | Intelligent capacity management method, device and storage medium |
| CN110737593B (en) * | 2019-09-19 | 2022-03-29 | 平安科技（深圳）有限公司 | Intelligent capacity management method, device and storage medium |
| CN113011138A (en) * | 2019-12-19 | 2021-06-22 | 北京懿医云科技有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
| CN113011138B (en) * | 2019-12-19 | 2023-09-15 | 北京懿医云科技有限公司 | Information processing method, information processing device, electronic equipment and storage medium |
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