CN107092544A - monitoring method and device - Google Patents
monitoring method and device Download PDFInfo
- Publication number
- CN107092544A CN107092544A CN201610349960.8A CN201610349960A CN107092544A CN 107092544 A CN107092544 A CN 107092544A CN 201610349960 A CN201610349960 A CN 201610349960A CN 107092544 A CN107092544 A CN 107092544A
- Authority
- CN
- China
- Prior art keywords
- node
- user
- monitoring
- information
- log information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 222
- 238000000034 method Methods 0.000 title claims abstract description 41
- 230000003542 behavioural effect Effects 0.000 claims abstract description 51
- 238000001514 detection method Methods 0.000 claims description 52
- 230000005540 biological transmission Effects 0.000 claims description 5
- 206010016256 fatigue Diseases 0.000 claims 1
- 230000000875 corresponding effect Effects 0.000 description 125
- 230000006399 behavior Effects 0.000 description 60
- 235000013311 vegetables Nutrition 0.000 description 9
- 238000004590 computer program Methods 0.000 description 8
- 238000012545 processing Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000008447 perception Effects 0.000 description 5
- 230000008901 benefit Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 2
- 125000004122 cyclic group Chemical group 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 230000002688 persistence Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 241000270322 Lepidosauria Species 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3017—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is implementing multitasking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
Landscapes
- Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Debugging And Monitoring (AREA)
Abstract
This application discloses a kind of monitoring method and device, it is related to service monitoring technical field, the precision of service monitoring can be improved.The main technical schemes of the application are：When receiving the behavioral data of user, the user identity information of the user is obtained；Detect whether to exist and different nodes are included in monitoring model corresponding with the user identity information, the monitoring model, and binding has preset rules on node；If in the presence of according to the behavioral data, configuring node corresponding with the behavioral data in the monitoring model；According to the preset rules, configuration result is monitored.
Description
Technical field
The application is related to service monitoring technical field, more particularly to a kind of monitoring method and device.
Background technology
Service monitoring is the monitoring to system service interface, is provided particularly directed to system to caller
Service related information is monitored, for example, to time-consuming, input parameter, return information, whether report an error,
The information such as call number are monitored.The result of service monitoring can be exported by console, can also
Journal file is write, or persistence (Persistence) arrives database, and business is performed for system
Situation carries out on-line analysis and off-line analysis.
At present, existing service monitoring is all horizontal based on service dimension itself, concrete implementation
Mode is：Background monitoring system will belong to same type of user behavior and be counted, during by unit
In statistical information weigh the correlated performance of service system, and make the alarm of correlation, i.e., it is just sharp
Pinpointed the problems with statistical information macroscopical in the unit interval, and make feedback.For example, background monitoring
System all takes together the request of access interface a in one minute, occurs during these requests of detection process
Error number whether be more than alarm threshold, if so, then make correlation alarm.
However, for the horizontal monitoring based on service dimension, when not touching corresponding alert if,
For unique user the correlation circumstance of service can not be called to make targetedly to feed back, can cause to occur
The hidden danger of service system failure, and then the precision of service monitoring can be caused relatively low.For example, user is in net
On when making a reservation, only there are many vegetables in one or two shop, when vegetable is loaded, looks into accordingly
Service is ask time-consuming very high or cause time-out, when there is a large number of users while accessing the shop and loading vegetable
When, service system failure can be caused, but if temporarily only having a small amount of user to trigger this problem, its
Quantity is not less than alarm threshold, then existing service monitoring mode be monitoring less than.
The content of the invention
In view of this, the embodiment of the present application provides a kind of monitoring method and device, and main purpose is solution
Certainly the service monitoring mode based on service dimension itself horizontal at present, can cause the precision of service monitoring
Relatively low the problem of.
To reach above-mentioned purpose, the application provides following technical scheme：
On the one hand, this application provides a kind of monitoring method, including：
When receiving the behavioral data of user, the user identity information of the user is obtained；
Detect whether exist in monitoring model corresponding with the user identity information, the monitoring model
Comprising different nodes, and on node, binding has preset rules；
If in the presence of, according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；
According to the preset rules, configuration result is monitored.
On the other hand, this application provides a kind of supervising device, including：
Acquiring unit, user's mark for when receiving the behavioral data of user, obtaining the user
Know information；
Detection unit, for detecting whether in the presence of monitoring model corresponding with the user identity information,
Different nodes are included in the monitoring model, and binding has preset rules on node；
Dispensing unit, if being detected for the detection unit in the presence of corresponding with the user identity information
Monitoring model, then according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；
Monitoring unit, for according to the preset rules, being monitored to configuration result.
By above-mentioned technical proposal, the technical scheme that the embodiment of the present application is provided at least has following advantages：
A kind of monitoring method and device that the embodiment of the present application is provided, when the behavioral data for receiving user
When, the user identity information of the user is obtained first；Then detect whether to exist and marked with the user
Know and different nodes are included in the corresponding monitoring model of information, the monitoring model, and there be binding on node
Preset rules；If in the presence of, according to the behavioral data, configure in the monitoring model with the row
For the corresponding node of data；Finally according to the preset rules, configuration result is monitored.With
The service monitoring mode based on service dimension itself horizontal at present is compared, the application can by user and
The behavior expression of system service, which is built into one and bound, the monitoring models of preset rules, and by with
The preset rules bound on the corresponding monitoring model interior joint of user identity information, can detect that user adjusts
With the correlation circumstance of service, and then it can realize and call the correlation circumstance of service to make for unique user
Targetedly feed back, so as to accomplish the real-time monitoring based on user's dimension, improve service system
Unite to the perception of unique user behavior, completed by the quality and state of monitoring model pair
User and the monitoring of respective service, improve the precision of service monitoring.
Described above is only the general introduction of technical scheme, in order to better understand the application's
Technological means, and being practiced according to the content of specification, and in order to allow the above-mentioned of the application and
Other objects, features and advantages can become apparent, below especially exemplified by the embodiment of the application.
Brief description of the drawings
By reading the detailed description of hereafter preferred embodiment, various other advantage and benefit for
Those of ordinary skill in the art will be clear understanding.Accompanying drawing is only used for showing the mesh of preferred embodiment
, and it is not considered as the limitation to the application.And in whole accompanying drawing, with identical with reference to symbol
Number represent identical part.In the accompanying drawings：
Fig. 1 shows a kind of flow chart for monitoring method that the embodiment of the present application is provided；
Fig. 2 shows the flow chart for another monitoring method that the embodiment of the present application is provided；
Fig. 3 shows a kind of example schematic for directed cyclic graph model that the embodiment of the present application is provided；
Fig. 4 shows a kind of monitoring system example schematic that the embodiment of the present application is provided；
Fig. 5 shows a kind of structural representation for supervising device that the embodiment of the present application is provided；
Fig. 6 shows the structural representation for another supervising device that the embodiment of the present application is provided.
Embodiment
The exemplary embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing in accompanying drawing
The exemplary embodiment of the disclosure is shown, it being understood, however, that may be realized in various forms the disclosure
Without that should be limited by embodiments set forth here.Conversely it is able to more there is provided these embodiments
Thoroughly understand the disclosure, and can be by the technology for conveying to this area of the scope of the present disclosure completely
Personnel.
The embodiment of the present application provides a kind of monitoring method, as shown in figure 1, methods described includes：
101st, when receiving the behavioral data of user, the user identity information of user is obtained.
Wherein, the user identity information can be user's name information, ID (Identity, identity mark
Know number) number, IP address etc..The data about user behavior can be included in the behavioral data,
It can specifically be acquired according to the corresponding log information of server, can also be collected and obtained by client
Obtain, when user behavior data is acquired according to the corresponding log information of server, user
Behavioral data can be the corresponding log information of user.
It should be noted that can be for configuration in the server for the executive agent of the embodiment of the present application
Supervising device, or configuration monitoring module in the server etc..For example, server is right
When the service request for being currently received client transmission is handled, corresponding log information is have recorded,
And the supervising device in server is passed to, the supervising device is after the log information is received, from day
User identity information is obtained in will information.
102nd, detect whether there is monitoring model corresponding with user identity information.
Wherein, different nodes are included in the monitoring model, and binding has preset rules on node.One
Individual node can correspond to a user behavior type, i.e., in monitoring model corresponding with user identity information
In have recorded the node of different user behavior type corresponding with user mark, and the user behavior
Type can be to call the behavior types such as service interface, for example, accessing shop a service by calling
Interface, accesses the shop a page.The preset rules can be by technical staff according to user behavior class
The actual demand of type writes and in the corresponding presetting database of configuration server in advance, for example, user
Behavior type is the access shop b pages, and in order to detect whether the net for having to the shop b pages
Network reptile crawls behavior, the preset rules that will can be bound on node corresponding with the user behavior type
It is configured to the node and is accessed number of times less than alarm threshold.
Specifically, it whether there is monitoring model corresponding with user identity information in detection service device.It is right
In the embodiment of the present application, a user identity information can correspond to a monitoring model, if server
In monitoring model corresponding with user identity information is not present, can be created, for example, new user
When sending service request for the first time by client, received in server at the service request and progress
During reason, monitoring model corresponding with the new user identity information can be created.Specifically, monitoring model
In node can be configured according to behavioral data, for example, according to the user recorded in log information
Behavior type, the log information is filled into corresponding node object, while can save this
The access times of point are accumulative Jia 1；And the corresponding preset rules of the node can be corresponding according to the node
User behavior type, obtains from presetting database and binds on this node.
It should be noted that can specifically be detected by calculating the corresponding cryptographic Hash of user identity information
It whether there is monitoring model corresponding with user identity information in server.For example, working as in server
, can be with during the corresponding cryptographic Hash of recorded user identity information, it may be determined that the user is old user
Monitoring model corresponding with the user identity information is obtained from presetting database；When not having in server
When recording the corresponding cryptographic Hash of user identity information, it may be determined that the user is new user, it is necessary to create
The corresponding monitoring model of the new user, and record the corresponding cryptographic Hash of the new user identity information.
If the 103, in the presence of monitoring model corresponding with user identity information, according to behavioral data, configuration
The node corresponding with behavioral data in monitoring model.
For example, in the log information received user behavior type for access vegetable list page, from with
Determined in monitoring model corresponding to family identification information with the corresponding node of access vegetable list page, and by day
Will information is filled into the node.
104th, according to preset rules, configuration result is monitored.
For example, ought detect that server is to vegetable list page service interface in the newly-increased log information of egress
Acquisition request when being handled the consumed time more than or equal to 200 milliseconds of alarm threshold, it is determined that
The corresponding preset rules of the node, and corresponding log information are not met with the node postponed
In user identity information be user a, at this moment can export the corresponding nodes of user a with postponing renewal
Monitoring figure, so that monitoring personnel judges that exception occurs in user a；Monitoring device correspondence can also be passed through
Display screen show that user a accesses the time-consuming text more than or equal to 200 milliseconds of loading of vegetable list page
Word warning information, at the same can by the corresponding audio output outputting alarm audio of monitoring device, with
Just operation maintenance personnel is reminded to carry out associated maintenance in time.
A kind of monitoring method that the embodiment of the present application is provided, it is first when receiving the behavioral data of user
First obtain the user identity information of the user；Then detect whether exist and the user identity information
Different nodes are included in corresponding monitoring model, the monitoring model, and binding has default rule on node
Then；If in the presence of, according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；Finally according to the preset rules, configuration result is monitored.With current horizontal stroke
To the service monitoring mode based on service dimension itself compare, the application can take user and system
The behavior expression of business is built into one and binds the monitoring model for having preset rules, and by being marked with user
Know the preset rules bound on the corresponding monitoring model interior joint of information, can detect that user calls service
Correlation circumstance, and then can realize that calling the correlation circumstance of service to make for unique user is directed to
The feedback of property, so as to accomplish the real-time monitoring based on user's dimension, improves service system to list
The perception of individual user behavior, completed by the quality and state of monitoring model to user and
The monitoring of respective service, improves the precision of service monitoring.
Further, the embodiment of the present application provides another monitoring method, as shown in Fig. 2 described
Method includes：
201st, when detecting the log information for existing in default journal file and increasing newly, from log information
Obtain user identity information.
Wherein, clothes of the server to each transmission of different clients are preserved in the default journal file
The log information that business request is recorded when being handled.For example, have recorded client correspondence in log information
The longitude and latitude of position, place city, the time for receiving service request, the sign string of service request, use
Family mobile phone IP (agreement interconnected between Internet Protocol, network) address, mobile phone operating system class
Network environment information etc. residing for type, user.The user identity information can be user's name information, ID
Number, IP address etc..
Specifically, when server receives the service request of client transmission, server is according to service
The service fields information that is carried in request and an information is buried, service request is handled, returned
Object information.Wherein, the longitude and latitude of client correspondence position can be included in the service fields information
The information such as lon and lat, place city city.Described bury can be comprising reception service request in an information
Time current_time, service request sign string rn, user mobile phone IP address, mobile phone operating system
The information such as network environment residing for type os, user.It can be included to service in the returning result information
Request handle consumed time, whether the information such as normal returning result, user behavior type.
Then server is according to returning result information, service fields information and buries an information, generates daily record
Information is simultaneously stored in default journal file.For example, user accesses shop list page by client,
Client collects the service fields information of the operation and buries an information, and regard both information as parameter
The shop list page acquisition of information interface for calling service end to provide, it is corresponding that service end receives this operation
Service request, and by various inquiries, calculating logic, return result to client.Service simultaneously
End by the service fields information of service request, bury an information and returning result information is arrived by log recording
In default journal file, form can be as follows：
lon:120.11111；lat:30.11111；city:330100；current_time:2016-02-01
12:30:12；rn:46e86a2697014；ip:10.111.22.11；os:iphone5；.....
202nd, it whether there is monitoring model corresponding with user identity information in detection service device.
Wherein, different nodes, node one user behavior class of correspondence are included in the monitoring model
There being binding in type, and node also includes the corresponding incidence edge of node in preset rules, the monitoring model.
It should be noted that the concrete form of monitoring model can be determined according to specific business demand, it is right
In the access behavior of user, the corresponding incidence edge of monitoring model interior joint be all it is directive, therefore,
Monitoring model can be Directed Graph Model.For example, user a first accesses webpage A, then webpage clicking A
In link jump to access webpage B, in the corresponding monitoring models of user a, webpage A is corresponding
Association edge direction between the node 2 corresponding with webpage B of node 1 is to point to node 2 from node 1.
The Directed Graph Model can be very good to show the access behavior of user.Further, can also basis
It whether there is loop in Directed Graph Model, Directed Graph Model is divided into digraph has ring model and oriented
Acyclic graph model, for example, user a first accesses webpage A, then jumps to webpage B, so by webpage A
Jumped to again by webpage B in webpage A, the corresponding Directed Graph Models of user a afterwards and there is loop, therefore
The corresponding monitoring models of user a are directed cyclic graph model.
Specifically, can by the user behavior on APP (Application, application program), the page,
Interface etc. is reasonably encoded, and the node correspondence being built into a monitoring model, monitoring model
The page, the return information and page self information of the attribute corresponding with service interface of node, the association of node
Side correspondence user behavior, incidence edge attribute correspondence user behavior bury an information (facility information,
Call service interface information etc.).Preset rules can be bound on node, preset rules can specifically divide
For general rule and ad hoc rules, for example, ad hoc rules is configurable to the corresponding section of shop list page
Number of times is accessed in one minute of point to be less than 100 times, is more than or is waited if being accessed number of times in one minute
Just alerted in 100 times, this ad hoc rules is applied to crawl web crawlers the service prison of the behaviors such as data
Control；General rule, which is configurable to take the loading of node corresponding page, is less than 200 milliseconds, if plus
Carry the time-consuming just alarm more than or equal to 200 milliseconds.
For example, as shown in figure 3, the take-away APP clients that user is installed by mobile phone access shop row
Table page, vegetable list page, lower single page and order list page, it is corresponding with the user identity information oriented
Have and there is corresponding node in ring graph model, be shop list page node, vegetable list page section respectively
Point, lower single page node, order list page node, wherein, there be in real time binding on the list page node of shop
Rule, specially when the consumption that server pair service interface request corresponding with shop list page is handled
When more than 200 milliseconds when just trigger alarm；Binding has rule and clocking discipline in real time on lower single page node,
Rule specially returns tight after server is handled the request of lower single page corresponding service interface in real time
Alarm is just triggered during weight mistake, and clocking discipline is specially not place an order successfully within 10 minutes just to send one
Red packet message is to user.
It should be noted that can specifically be detected by calculating the corresponding cryptographic Hash of user identity information
With the presence or absence of monitoring model corresponding with user identity information.For example, user's mark ought have recorded
During the corresponding cryptographic Hash of information, it may be determined that the user is old user, can be obtained from presetting database
Take monitoring model corresponding with the user identity information；Breathed out when no record user identity information is corresponding
During uncommon value, it may be determined that the user is new user, it is necessary to create the corresponding monitoring model of the new user,
And record the corresponding cryptographic Hash of the new user identity information.
If there is monitoring model corresponding with user identity information in 203a, server, from monitoring model
It is middle to determine node corresponding with user behavior type in log information.
For the embodiment of the present application, also include before step 203a：Detect in the monitoring model whether
In the presence of node corresponding with user behavior type in the log information；If being not present, create and institute
The corresponding node of user behavior type in log information is stated, and according to the log information to the node
Configured；Step 205a can specifically include：If in the presence of, from the monitoring model determine with
The corresponding node of user behavior type in the log information.
If for example, in monitoring model be not present node corresponding with user behavior type in log information,
Corresponding node can be created in the monitoring model, log information is filled into the node, by this
The accessed number of times of node is configured to 1 time, and is obtained and the user behavior class from presetting database
The corresponding preset rules of type are simultaneously bound on this node.
204a, according to log information configuration node.
For the embodiment of the present application, step 206a can specifically include：According in the log information
Service fields information and bury an information, configure the corresponding incidence edge of the node；Believed according to the daily record
Returning result information in breath, configures the node.
Whether 205a, detection meet the preset rules being bundled on node with the node postponed.
For the embodiment of the present application, if the preset rules bound on the node are in prefixed time interval
The corresponding access times of the interior node are less than preset times threshold value, wherein, the prefixed time interval
And preset times threshold value can be configured according to the actual demand of business, for example, between preset time
Every being configurable to 5 seconds, 30 seconds etc., and preset times threshold value be configurable to 50 times, it is 100 inferior.
Step 204a can specifically include：The node is configured and by the node pair according to the log information
The access times answered are added up.And step 205a can specifically include：Detection is in the preset time
Whether the access times of the node are less than the preset times threshold value in interval；If when described default
Between be spaced in the node access times be more than or equal to the preset times threshold value, it is determined that configuration
The node afterwards does not meet the preset rules being bundled on the node.
For example, the preset rules bound on node are that the corresponding access times of the node are less than in 30 seconds
50 times, log information is filled into the node, and Jia 1 by the corresponding access times of the node are accumulative,
And detect whether the access times in the node 30 seconds are less than 50 times, the access in the node 30 seconds
When number of times is less than 50 times, it is determined that meeting the preset rules of binding on this node with the node postponed；When
When access times in the node 30 seconds are more than or equal to 50 times, it is determined that not met with the node postponed
The preset rules of binding on this node.
For the embodiment of the present application, if the preset rules bound on the node are that service request is carried out
Processing the consumed time is less than preset time threshold, wherein, the preset time threshold can basis
The actual demand of business is configured, for example, preset time threshold be configurable to 200 milliseconds, 220
Millisecond etc..Step 205a can specifically include：Detect in the newly-increased log information of the node to service
Request is handled whether the consumed time is less than the preset time threshold；If the time is more than
Or equal to the preset time threshold, it is determined that do not met with the node postponed and be bundled in the section
Preset rules on point.
For example, the preset rules bound on node handle what is consumed by server to service request progress
Time is less than 200 milliseconds, detects that server is carried out to service request in the newly-increased log information of the node
Whether processing the consumed time is less than 200 milliseconds, when server in the log information that the node is increased newly
When being handled service request the consumed time less than 200 milliseconds, it is determined that with the node symbol postponed
Close the preset rules of binding on this node；When the node increase newly log information in server to service
When request is handled the consumed time more than or equal to 200 milliseconds, it is determined that with the node postponed not
Meet the preset rules of binding on this node.
If corresponding with user identity information with being not present in step 203b that step 203a is arranged side by side, server
Monitoring model, then create corresponding with user identity information monitoring model.
204b, according to log information, node in configuration monitoring model and corresponding with node default
Rule.
Specifically, the user behavior type in log information, log information is filled into and the use
In the corresponding node of family behavior type, and the access times of the node are configured to 1 time, and from pre-
If obtaining preset rules corresponding with the user behavior type in database and being bundled on the node.
For the embodiment of the present application, also include after step 206b：Detection with the node that postpones whether
Meet the preset rules of binding on this node.
For example, when detecting the log information for existing in default journal file and increasing newly, by log information
Real-time computing engines jstorm clusters are sent to, jstorm clusters obtain log information and entered according to ID
Row cryptographic Hash is verified, and is determined that monitoring model corresponding with User IP is not present in server, is then selected
This log information is identified one machine jstorm_node, can identify following information：
The current time：2016-02-01 12:30:12
Behavior type：Access shop homepage
Whether normally return：It is
It is time-consuming：120ms
Corresponding user's mark：ip:10.111.22.11
。。。。。
According to above- mentioned information, a newly-built monitoring model, the user behavior type in log information,
Log information is filled into monitoring model node corresponding with the user behavior type, and by the node
Access times be configured to 1 time, and from presetting database obtain it is corresponding with the user behavior type
Preset rules and bind on this node, finally trigger a series of binding default rule on this node
Then, preset rules here are that whether the accessed number of times of the node is more than in continuous one minute of task
Or equal to alarm threshold, if the number of times is more than or equal to alarm threshold, alerted.
If the 206, detecting not meeting the preset rules being bundled on node with the node postponed, export
Warning information.
Wherein, the warning information can be text alert information, picture warning information, audible alarm
Information, visual alarm information etc..
If for example, the preset rules bound on node access for node within a preset time interval is corresponding
Number of times is less than preset times threshold value, and the access times when detection egress within a preset time interval
During more than or equal to preset times threshold value, outputting alarm information, to remind operation maintenance personnel timely
Carry out associated maintenance.
It should be noted that information (the bag that the follow-up a series of behavior of user and service end can be returned to
Include service related information：Such as take, whether report an error etc.) constantly collected, and continue structure
Build the corresponding monitoring model of user.For example, as shown in figure 4, the corresponding monitoring model of user can be
Persistently build and safeguarded in the internal memory of jstorm clusters, so as to construct the service based on user's dimension
Monitoring system.In this service monitoring system, behavior of the user on APP in certain time
A monitoring model can be corresponded to, the rule that this monitoring model is bound above can be triggered in real time,
So as to accomplish the real-time monitoring based on user's dimension.
Further, until the corresponding rule of triggering or more than the regular hour monitoring model no longer by
During access, monitoring model relevant information serializing is stored into database for future use.
Another monitoring method that the embodiment of the present application is provided, when receiving the behavioral data of user,
The user identity information of the user is obtained first；Then detect whether to exist to identify with the user and believe
Cease and different nodes are included in corresponding monitoring model, the monitoring model, and binding has default on node
Rule；If in the presence of, according to the behavioral data, configure in the monitoring model with the behavior number
According to corresponding node；Finally according to the preset rules, configuration result is monitored.With it is current
The horizontal service monitoring mode based on service dimension itself is compared, and the application can be by user and system
The behavior expression of service, which is built into one and bound, the monitoring models of preset rules, and by with user
The preset rules bound on monitoring model interior joint corresponding to identification information, can detect that user calls clothes
The correlation circumstance of business, and then can realize and call the correlation circumstance of service to make pin for unique user
To the feedback of property, so as to accomplish the real-time monitoring based on user's dimension, service system pair is improved
The perception of unique user behavior, is completed to user by the quality and state of monitoring model
With the monitoring of respective service, the precision of service monitoring is improved.
Further, implementing as method shown in Fig. 1, the embodiment of the present application provides one kind
Supervising device, as shown in figure 5, described device can include：Acquiring unit 51, detection unit 52,
Dispensing unit 53, monitoring unit 54.
The acquiring unit 51, can be used for when receiving the behavioral data of user, obtain described use
The user identity information at family.The acquiring unit 51 is user in acquisition user behavior data in the present apparatus
The main functional modules of identification information.
The detection unit 52, can be used in detection service device whether there is to identify with the user believing
Cease and different nodes are included in corresponding monitoring model, the monitoring model, and binding has default on node
Rule.The detection unit 52 is to be used in detection service device with the presence or absence of monitoring model in the present apparatus
Main functional modules.
The dispensing unit 53, if can be used for the detection unit 52 detects exist and the user
Monitoring model corresponding to identification information, then according to the behavioral data, configure in the monitoring model with
The corresponding node of the behavioral data.The dispensing unit 53 be the present apparatus according to user behavior number
According to the main functional modules of configuration monitoring model node.
The monitoring unit 54, can be used for, according to the preset rules, being monitored configuration result.
The monitoring unit 54 is the main functional modules of progress service monitoring in the present apparatus.
It should be noted that the device embodiment is corresponding with preceding method embodiment, specifically it may be referred to
Correspondence description in Fig. 1, for ease of reading, present apparatus embodiment is no longer in preceding method embodiment
Detail content repeated one by one, it should be understood that the device in the present embodiment can correspond to realize
Full content in preceding method embodiment.
A kind of supervising device that the embodiment of the present application is provided, it is first when receiving the behavioral data of user
First obtain the user identity information of the user；Then detect whether exist and the user identity information
Different nodes are included in corresponding monitoring model, the monitoring model, and binding has default rule on node
Then；If in the presence of, according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；Finally according to the preset rules, configuration result is monitored.With current horizontal stroke
To the service monitoring mode based on service dimension itself compare, the application can take user and system
The behavior expression of business is built into one and binds the monitoring model for having preset rules, and by being marked with user
Know the preset rules bound on the corresponding monitoring model interior joint of information, can detect that user calls service
Correlation circumstance, and then can realize that calling the correlation circumstance of service to make for unique user is directed to
The feedback of property, so as to accomplish the real-time monitoring based on user's dimension, improves service system to list
The perception of individual user behavior, completed by the quality and state of monitoring model to user and
The monitoring of respective service, improves the precision of service monitoring.
Further, implementing as method shown in Fig. 2, the embodiment of the present application provides another
Supervising device is planted, as shown in fig. 6, described device can include：Acquiring unit 61, detection unit 62,
Dispensing unit 63, monitoring unit 64.
The acquiring unit 61, can be used for when receiving the behavioral data of user, obtain described use
The user identity information at family.The acquiring unit 61 is user in acquisition user behavior data in the present apparatus
The main functional modules of identification information.
The detection unit 62, can be used in detection service device whether there is to identify with the user believing
Cease and different nodes are included in corresponding monitoring model, the monitoring model, and binding has default on node
Rule.The detection unit 62 is to be used in detection service device with the presence or absence of monitoring model in the present apparatus
Main functional modules.
The dispensing unit 63, if can be used for the detection unit 62 detects exist and the user
Monitoring model corresponding to identification information, then according to the behavioral data, configure in the monitoring model with
The corresponding node of the behavioral data.The dispensing unit 63 be the present apparatus according to user behavior number
According to the main functional modules of configuration monitoring model node.
The monitoring unit 64, can be used for, according to the preset rules, being monitored configuration result.
The monitoring unit 64 is the main functional modules of progress service monitoring in the present apparatus.
Specifically, the monitoring unit 64 includes：Detection module 641, output module 642.
The detection module 641, can be used for detection with whether the node postponed meets and is bundled in the section
Preset rules on point.
The output module 642, is detected with the node postponed if can be used for the detection module 641
The preset rules being bundled on the node are not met, then outputting alarm information.
Alternatively, the behavioral data can be the corresponding log information of user, in the monitoring model
One node one user behavior type of correspondence.
Further, the dispensing unit 63 includes：Determining module 631, configuration module 632.
The determining module 631, can be used for from the monitoring model in determination and the log information
The corresponding node of user behavior type.
The configuration module 632, can be used for configuring the determining module determination according to the log information
Node.
If the preset rules bound on the node are visited for the node within a preset time interval is corresponding
Ask that number of times is less than preset times threshold value, the configuration module 632 specifically can be used for according to the daily record
Node described in information configuration is simultaneously added up the corresponding access times of the node.
The detection module 641, specifically can be used for detection node in the prefixed time interval
Access times whether be less than the preset times threshold value.
The detection module 641, if specifically can be also used for detecting the institute in the prefixed time interval
The access times for stating node are more than or equal to the preset times threshold value, it is determined that with the section postponed
Point does not meet the preset rules being bundled on the node.
If the preset rules bound on the node handle what is consumed by server to service request progress
Time is less than preset time threshold, and the detection module 641 specifically can be used for detecting that the node is new
Whether server is handled service request the consumed time less than described pre- in the log information of increasing
If time threshold.
The detection module 641, if specifically can be also used for detecting the time more than or equal to described
Preset time threshold, it is determined that do not met with the node postponed and be bundled in presetting on the node
Rule.
The acquiring unit 61, specifically can be used for detecting in the default journal file in the presence of new
During the log information of increasing, user identity information is obtained from the log information, wherein, it is described default
Preserve when server is handled the service request of each transmission of different clients and remember in journal file
The log information of record.
Alternatively, the corresponding incidence edge of node can also be included in the monitoring model.
The configuration module 632, specifically can be also used for the service fields letter in the log information
Cease and bury an information, configure the corresponding incidence edge of the node.
The configuration module 632, specifically can be also used for the returning result letter in the log information
Breath, configures the node.
Further, the dispensing unit 63 also includes：Detection module 633, creation module 634.
The detection module 633, can be also used for detecting in the monitoring model whether there is and the day
The corresponding node of user behavior type in will information.
The creation module 634, if can be used for the detection module 633 detects the monitoring model
In be not present node corresponding with user behavior type in the log information, then create with the daily record
The corresponding node of user behavior type in information.
The configuration module 632, can be also used for according to the log information to the creation module 634
The node of establishment is configured.
The determining module 631, if specifically can be used for the detection module 623 detects the monitoring
There is node corresponding with user behavior type in the log information in model, then from the monitoring mould
Node corresponding with user behavior type in the log information is determined in type.
Further, described device also includes：Creating unit 65.
The creating unit 65, is used if can be used for the detection unit 62 and detect to be not present with described
Monitoring model corresponding to family identification information, then create monitoring model corresponding with the user identity information.
The dispensing unit 63, can be also used for, according to the behavioral data, configuring the creating unit
Node and preset rules corresponding with the node in 65 monitoring models created.
Alternatively, the monitoring model can be Directed Graph Model.
It should be noted that the device embodiment is corresponding with preceding method embodiment, specifically it may be referred to
Correspondence description in Fig. 2, for ease of reading, present apparatus embodiment is no longer in preceding method embodiment
Detail content repeated one by one, it should be understood that the device in the present embodiment can correspond to realize
Full content in preceding method embodiment.
The supervising device includes processor and memory, above-mentioned acquiring unit, detection unit, configuration
Unit, monitoring unit, creating unit etc. are stored in memory, by processor as program unit
The said procedure unit of storage in memory is performed to realize corresponding function.
Kernel is included in processor, is gone in memory to transfer corresponding program unit by kernel.Kernel can
To set one or more, being tieed up based on service for current transverse direction in itself is solved by adjusting kernel parameter
The service monitoring mode of degree, can cause the problem of precision of service monitoring is relatively low.
Memory potentially includes the volatile memory in computer-readable medium, random access memory
The form such as device (RAM) and/or Nonvolatile memory, such as read-only storage (ROM) or flash memory (flash
RAM), memory includes at least one storage chip.
Another supervising device that the embodiment of the present application is provided, when receiving the behavioral data of user,
The user identity information of the user is obtained first；Then detect whether to exist to identify with the user and believe
Cease and different nodes are included in corresponding monitoring model, the monitoring model, and binding has default on node
Rule；If in the presence of, according to the behavioral data, configure in the monitoring model with the behavior number
According to corresponding node；Finally according to the preset rules, configuration result is monitored.With it is current
The horizontal service monitoring mode based on service dimension itself is compared, and the application can be by user and system
The behavior expression of service, which is built into one and bound, the monitoring models of preset rules, and by with user
The preset rules bound on monitoring model interior joint corresponding to identification information, can detect that user calls clothes
The correlation circumstance of business, and then can realize and call the correlation circumstance of service to make pin for unique user
To the feedback of property, so as to accomplish the real-time monitoring based on user's dimension, service system pair is improved
The perception of unique user behavior, is completed to user by the quality and state of monitoring model
With the monitoring of respective service, the precision of service monitoring is improved.
Present invention also provides a kind of computer program product, when being performed on data processing equipment,
It is adapted for carrying out the program code of initialization there are as below methods step：When receiving the behavioral data of user,
Obtain the user identity information of the user；Detect whether in the presence of corresponding with the user identity information
Different nodes are included in monitoring model, the monitoring model, and binding has preset rules on node；If
In the presence of corresponding with the behavioral data in the configuration monitoring model then according to the behavioral data
Node；According to the preset rules, configuration result is monitored.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system,
Or computer program product.Therefore, the application can be implemented using complete hardware embodiment, complete software
The form of embodiment in terms of example or combination software and hardware.Moreover, the application can be used at one
Or multiple computer-usable storage mediums for wherein including computer usable program code are (including but not
Be limited to magnetic disk storage, CD-ROM, optical memory etc.) on the computer program product implemented
Form.
The application is produced with reference to according to the monitoring method of the embodiment of the present application, device and computer program
The flow chart and/or block diagram of product is described.It should be understood that can be by computer program instructions implementation process
In figure and/or each flow and/or square frame and flow chart and/or block diagram in block diagram
The combination of flow and/or square frame.These computer program instructions can be provided to all-purpose computer, special
The processor of computer, Embedded Processor or other programmable data processing devices is to produce a machine
Device so that produced by the instruction of computer or the computing device of other programmable data processing devices
For realizing in one flow of flow chart or multiple flows and/or one square frame of block diagram or multiple square frames
In the device of function specified.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable datas to handle
In the computer-readable memory that equipment works in a specific way so that be stored in this and computer-readable deposit
Instruction in reservoir, which is produced, includes the manufacture of command device, and command device realization is in flow chart one
The function of being specified in flow or multiple flows and/or one square frame of block diagram or multiple square frames.
These computer program instructions can also be loaded into computer or other programmable data processing devices
On so that series of operation steps is performed on computer or other programmable devices to produce computer
The processing of realization, so that the instruction performed on computer or other programmable devices is provided for realizing
Specified in one flow of flow chart or multiple flows and/or one square frame of block diagram or multiple square frames
The step of function.
In a typical configuration, computing device include one or more processors (CPU), input/
Output interface, network interface and internal memory.
Memory potentially includes the memory permanently or non-permanently in computer-readable medium, with
The form such as machine access memory (RAM) and/or Nonvolatile memory, such as read-only storage (ROM) or sudden strain of a muscle
Deposit (flash RAM).Memory is the example of computer-readable medium.
Embodiments herein is these are only, the application is not limited to.For this area skill
For art personnel, the application can have various modifications and variations.It is all spirit herein and principle it
Interior made any modification, equivalent substitution and improvements etc., should be included in claims hereof model
Within enclosing.
Claims (20)
1. a kind of monitoring method, it is characterised in that including：
When receiving the behavioral data of user, the user identity information of the user is obtained；
Detect whether exist in monitoring model corresponding with the user identity information, the monitoring model
Comprising different nodes, and on node, binding has preset rules；
If in the presence of, according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；
According to the preset rules, configuration result is monitored.
2. monitoring method according to claim 1, it is characterised in that described according to described pre-
If regular, configuration result is monitored, specifically included：
Whether detection meets the preset rules being bundled on the node with the node postponed；
If it is not, then outputting alarm information.
3. monitoring method according to claim 2, it is characterised in that the behavioral data is use
Node one user behavior type of correspondence in the corresponding log information in family, the monitoring model,
It is described according to the behavioral data, configure corresponding with the behavioral data in the monitoring model
Node, specifically include：
Node corresponding with user behavior type in the log information is determined from the monitoring model；
The node is configured according to the log information.
4. monitoring method according to claim 3, it is characterised in that if being bound on the node
Preset rules be less than preset times threshold for corresponding access times of the node within a preset time interval
Value, it is described that the node is configured according to the log information, specifically include：
The node is configured according to the log information and the corresponding access times of the node are tired out
Plus；
Whether the detection meets the preset rules being bundled on the node with the node postponed, specifically
Including：
Detect whether the access times of the node in the prefixed time interval are less than described default time
Number threshold value；
If the access times of the node are more than or equal to described default time in the prefixed time interval
Number threshold value, it is determined that the preset rules being bundled on the node are not met with the node postponed.
5. monitoring method according to claim 3, it is characterised in that if being bound on the node
Preset rules to be handled service request the consumed time less than preset time threshold, it is described
Whether detection meets the preset rules being bundled on the node with the node postponed, specifically includes：
Detecting, consumed time is handled service request in the newly-increased log information of the node is
It is no to be less than the preset time threshold；
If the time is more than or equal to the preset time threshold, it is determined that with the node postponed
The preset rules being bundled on the node are not met.
6. monitoring method according to claim 3, it is characterised in that described to receive user
Behavioral data when, obtain the user identity information of the user, specifically include：
When detecting the log information for existing in default journal file and increasing newly, from the log information
User identity information is obtained, wherein, server is preserved to different clients in the default journal file
The log information recorded when holding the service request sent every time to be handled.
7. monitoring method according to claim 3, it is characterised in that in the monitoring model also
Comprising the corresponding incidence edge of node,
It is described that the node is configured according to the log information, specifically include：
Service fields information in the log information is corresponded to an information, the configuration node is buried
Incidence edge；
Returning result information in the log information, configures the node.
8. monitoring method according to claim 3, it is characterised in that described from the monitoring mould
Determined in type before node corresponding with user behavior type in the log information, methods described is also wrapped
Include：
Detect in the monitoring model with the presence or absence of corresponding with user behavior type in the log information
Node；
If being not present, node corresponding with user behavior type in the log information, and root are created
The node is configured according to the log information；
It is described that section corresponding with user behavior type in the log information is determined from the monitoring model
Point, is specifically included：
If in the presence of determination and user behavior type pair in the log information from the monitoring model
The node answered.
9. monitoring method according to claim 1, it is characterised in that described to detect whether exist
After monitoring model corresponding with the user identity information, methods described also includes：
If being not present, monitoring model corresponding with the user identity information is created；
According to the behavioral data, node in the monitoring model is configured and corresponding with the node
Preset rules.
10. the monitoring method according to any one of claim 1 to 9, it is characterised in that described
Monitoring model is Directed Graph Model.
11. a kind of supervising device, it is characterised in that including：
Acquiring unit, user's mark for when receiving the behavioral data of user, obtaining the user
Know information；
Detection unit, for detecting whether in the presence of monitoring model corresponding with the user identity information,
Different nodes are included in the monitoring model, and binding has preset rules on node；
Dispensing unit, if being detected for the detection unit in the presence of corresponding with the user identity information
Monitoring model, then according to the behavioral data, configure in the monitoring model with the behavioral data
Corresponding node；
Monitoring unit, for according to the preset rules, being monitored to configuration result.
12. supervising device according to claim 11, it is characterised in that the monitoring unit bag
Include：
Detection module, presetting on the node is bundled in for detecting whether to meet with the node postponed
Rule；
Output module, institute is bundled in if detecting not meeting with the node postponed for the detection module
The preset rules on node are stated, then outputting alarm information.
13. supervising device according to claim 12, it is characterised in that the behavioral data is
Node one user behavior type of correspondence in the corresponding log information of user, the monitoring model,
The dispensing unit includes：
Determining module, for being determined from the monitoring model and user behavior class in the log information
The corresponding node of type；
Configuration module, for configuring the node that the determining module is determined according to the log information.
14. supervising device according to claim 13, it is characterised in that if being tied up on the node
Fixed preset rules are less than preset times for the corresponding access times of the node within a preset time interval
Threshold value,
The configuration module, specifically for configuring the node and by the section according to the log information
The corresponding access times of point are added up；
The detection module, the access specifically for detecting the node in the prefixed time interval
Whether number of times is less than the preset times threshold value；
The detection module, if being specifically additionally operable to detect the node in the prefixed time interval
Access times be more than or equal to the preset times threshold value, it is determined that be not inconsistent with the node postponed
Close the preset rules being bundled on the node.
15. supervising device according to claim 13, it is characterised in that if being tied up on the node
Fixed preset rules are less than preset time threshold to be handled service request the consumed time,
To service request in the detection module, the log information newly-increased specifically for detecting the node
Handled whether the consumed time is less than the preset time threshold；
The detection module, if be specifically additionally operable to detect that the time is more than or equal to described default
Between threshold value, it is determined that the preset rules being bundled on the node are not met with the node postponed.
16. supervising device according to claim 13, it is characterised in that
, there is newly-increased day in the default journal file specifically for working as to detect in the acquiring unit
During will information, user identity information is obtained from the log information, wherein, the default daily record text
The day recorded when server is handled the service request of each transmission of different clients is preserved in part
Will information.
17. supervising device according to claim 13, it is characterised in that in the monitoring model
The corresponding incidence edge of node is also included,
The configuration module, is specifically additionally operable to the service fields information in the log information and buries
Point information, configures the corresponding incidence edge of the node；
The configuration module, is specifically additionally operable to the returning result information in the log information, matches somebody with somebody
Put the node.
18. supervising device according to claim 13, it is characterised in that the dispensing unit is also
Including：Detection module and creation module；
The detection module, for detect in the monitoring model whether there is with the log information
The corresponding node of user behavior type；
The creation module, if for the detection module detect in the monitoring model be not present with
The corresponding node of user behavior type in the log information, then create and user in the log information
The corresponding node of behavior type；
The configuration module, is additionally operable to the node created according to the log information to the creation module
Configured；
The determining module, if detecting exist in the monitoring model specifically for the detection module
Node corresponding with user behavior type in the log information, then from the monitoring model determine with
The corresponding node of user behavior type in the log information.
19. supervising device according to claim 11, it is characterised in that described device also includes：
Creating unit；
The creating unit, believes if detecting to be not present to identify with the user for the detection unit
Corresponding monitoring model is ceased, then creates monitoring model corresponding with the user identity information；
Dispensing unit, is additionally operable to according to the behavioral data, configures the monitoring that the creating unit is created
Node and preset rules corresponding with the node in model.
20. the supervising device according to any one of claim 11 to 19, it is characterised in that institute
Monitoring model is stated for Directed Graph Model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610349960.8A CN107092544B (en) | 2016-05-24 | 2016-05-24 | Monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610349960.8A CN107092544B (en) | 2016-05-24 | 2016-05-24 | Monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107092544A true CN107092544A (en) | 2017-08-25 |
| CN107092544B CN107092544B (en) | 2020-09-15 |
Family
ID=59648831
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610349960.8A Expired - Fee Related CN107092544B (en) | 2016-05-24 | 2016-05-24 | Monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107092544B (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107562551A (en) * | 2017-09-05 | 2018-01-09 | 北京小度信息科技有限公司 | Monitoring method, device and the computer-readable recording medium of outside access system |
| CN108228431A (en) * | 2018-01-04 | 2018-06-29 | 北京中关村科金技术有限公司 | A kind of method and system of configurationization reptile quality-monitoring |
| CN108322350A (en) * | 2018-02-27 | 2018-07-24 | 阿里巴巴集团控股有限公司 | Business monitoring method and device and electronic equipment |
| CN109583758A (en) * | 2018-11-30 | 2019-04-05 | 广州净松软件科技有限公司 | Early warning rule modification method, device and the computer equipment of observation system |
| CN109766370A (en) * | 2018-12-27 | 2019-05-17 | 口碑(上海)信息技术有限公司 | Data processing method, data service system and equipment |
| CN109961200A (en) * | 2017-12-25 | 2019-07-02 | 北京嘀嘀无限科技发展有限公司 | Monitoring and reminding method, monitoring and reminding system, computer equipment and storage medium |
| CN110120964A (en) * | 2018-02-07 | 2019-08-13 | 北京三快在线科技有限公司 | User behavior monitoring method and device and calculating equipment |
| CN110489311A (en) * | 2019-03-01 | 2019-11-22 | 北京亿赛通科技发展有限责任公司 | Automatic detection computer user behavior and the method and system for automatically updating detection model |
| CN110874307A (en) * | 2018-08-29 | 2020-03-10 | 北京京东尚科信息技术有限公司 | Event buried point collecting and reporting method and device |
| CN111045950A (en) * | 2019-12-16 | 2020-04-21 | 上海钧正网络科技有限公司 | Method and device for determining performance problem point, data analysis system and storage medium |
| US11017340B2 (en) | 2017-12-05 | 2021-05-25 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for cheat examination |
| CN112839008A (en) * | 2019-11-22 | 2021-05-25 | 北京沃东天骏信息技术有限公司 | Access monitoring method, device and system |
| CN113138905A (en) * | 2021-05-11 | 2021-07-20 | 北京京东拓先科技有限公司 | Software function monitoring method and device |
| CN113941901A (en) * | 2020-07-17 | 2022-01-18 | 智能云科信息科技有限公司 | Machine tool cutter monitoring method and device and electronic equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102404741A (en) * | 2011-11-30 | 2012-04-04 | 中国联合网络通信集团有限公司 | Method and device for detecting abnormal online of mobile terminal |
| CN103049163A (en) * | 2012-12-28 | 2013-04-17 | 华为技术有限公司 | Method and device for controlling intelligent displaying of user interfaces |
| US8645919B2 (en) * | 2008-04-16 | 2014-02-04 | Microsoft Corporation | Generic validation test framework for graphical user interfaces |
| CN104636237A (en) * | 2015-01-19 | 2015-05-20 | 上海新炬网络信息技术有限公司 | Monitoring method for Web application system service performance based on Java platform |
-
2016
- 2016-05-24 CN CN201610349960.8A patent/CN107092544B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8645919B2 (en) * | 2008-04-16 | 2014-02-04 | Microsoft Corporation | Generic validation test framework for graphical user interfaces |
| CN102404741A (en) * | 2011-11-30 | 2012-04-04 | 中国联合网络通信集团有限公司 | Method and device for detecting abnormal online of mobile terminal |
| CN103049163A (en) * | 2012-12-28 | 2013-04-17 | 华为技术有限公司 | Method and device for controlling intelligent displaying of user interfaces |
| CN104636237A (en) * | 2015-01-19 | 2015-05-20 | 上海新炬网络信息技术有限公司 | Monitoring method for Web application system service performance based on Java platform |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107562551A (en) * | 2017-09-05 | 2018-01-09 | 北京小度信息科技有限公司 | Monitoring method, device and the computer-readable recording medium of outside access system |
| US11017340B2 (en) | 2017-12-05 | 2021-05-25 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for cheat examination |
| CN109961200A (en) * | 2017-12-25 | 2019-07-02 | 北京嘀嘀无限科技发展有限公司 | Monitoring and reminding method, monitoring and reminding system, computer equipment and storage medium |
| CN108228431A (en) * | 2018-01-04 | 2018-06-29 | 北京中关村科金技术有限公司 | A kind of method and system of configurationization reptile quality-monitoring |
| CN110120964A (en) * | 2018-02-07 | 2019-08-13 | 北京三快在线科技有限公司 | User behavior monitoring method and device and calculating equipment |
| CN108322350A (en) * | 2018-02-27 | 2018-07-24 | 阿里巴巴集团控股有限公司 | Business monitoring method and device and electronic equipment |
| CN108322350B (en) * | 2018-02-27 | 2021-06-01 | 创新先进技术有限公司 | Service monitoring method and device and electronic equipment |
| CN110874307A (en) * | 2018-08-29 | 2020-03-10 | 北京京东尚科信息技术有限公司 | Event buried point collecting and reporting method and device |
| CN109583758A (en) * | 2018-11-30 | 2019-04-05 | 广州净松软件科技有限公司 | Early warning rule modification method, device and the computer equipment of observation system |
| CN109766370A (en) * | 2018-12-27 | 2019-05-17 | 口碑(上海)信息技术有限公司 | Data processing method, data service system and equipment |
| CN110489311A (en) * | 2019-03-01 | 2019-11-22 | 北京亿赛通科技发展有限责任公司 | Automatic detection computer user behavior and the method and system for automatically updating detection model |
| CN110489311B (en) * | 2019-03-01 | 2023-04-18 | 北京亿赛通科技发展有限责任公司 | Method and system for automatically detecting computer user behaviors and automatically updating detection model |
| CN112839008A (en) * | 2019-11-22 | 2021-05-25 | 北京沃东天骏信息技术有限公司 | Access monitoring method, device and system |
| CN112839008B (en) * | 2019-11-22 | 2024-02-06 | 北京沃东天骏信息技术有限公司 | Access monitoring method, device and system |
| CN111045950A (en) * | 2019-12-16 | 2020-04-21 | 上海钧正网络科技有限公司 | Method and device for determining performance problem point, data analysis system and storage medium |
| CN111045950B (en) * | 2019-12-16 | 2023-06-30 | 上海钧正网络科技有限公司 | Performance problem point determining method, device, data analysis system and storage medium |
| CN113941901A (en) * | 2020-07-17 | 2022-01-18 | 智能云科信息科技有限公司 | Machine tool cutter monitoring method and device and electronic equipment |
| CN113941901B (en) * | 2020-07-17 | 2024-04-23 | 智能云科信息科技有限公司 | Machine tool cutter monitoring method, machine tool cutter monitoring device and electronic equipment |
| CN113138905A (en) * | 2021-05-11 | 2021-07-20 | 北京京东拓先科技有限公司 | Software function monitoring method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107092544B (en) | 2020-09-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107092544A (en) | monitoring method and device | |
| US9432821B2 (en) | Adaptive notification system for mobile devices | |
| US10432669B1 (en) | Security appliance to monitor networked computing environment | |
| CN104252479B (en) | Processing method, the device and system of information | |
| CN107426252B (en) | The method and apparatus of web application firewall service is provided | |
| CN107402880A (en) | A kind of method of testing and electronic equipment | |
| CN104753730B (en) | A kind of method and device of Hole Detection | |
| CN105531679B (en) | The abnormality detection carried out on networking client | |
| CN107015991A (en) | Self checking method, device, system and the service apparatus of data consistency | |
| CN106156147B (en) | A kind of report sending method based on big data analysis, apparatus and system | |
| US20200327045A1 (en) | Test System and Test Method | |
| US20200356462A1 (en) | Systems and methods for determining performance metrics of remote relational databases | |
| CN109766502A (en) | Page improved method, device, computer equipment and storage medium | |
| CN103095693A (en) | Method for positioning and accessing database user host information | |
| CN108134708A (en) | The method and apparatus for monitoring third party's interface | |
| CN107168844B (en) | Performance monitoring method and device | |
| CN106603464A (en) | Network detection method, system and device | |
| CN110380890A (en) | A kind of CDN system service quality detection method and system | |
| CN109241435A (en) | It is a kind of for digital cash transaction data push method, apparatus and system | |
| RU2015143226A (en) | ONLINE PRIVACY MANAGEMENT | |
| US20180329907A1 (en) | Reducing data sent from a user device to a server | |
| CN108337100B (en) | Cloud platform monitoring method and device | |
| CN107943678A (en) | A kind of method for evaluating application access process and evaluation server | |
| CN112383513A (en) | Crawler behavior detection method and device based on proxy IP address pool and storage medium | |
| US9378230B1 (en) | Ensuring availability of data in a set being uncorrelated over time |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200915 |