CN108933689A - A kind of data collection system and method - Google Patents
A kind of data collection system and method Download PDFInfo
- Publication number
- CN108933689A CN108933689A CN201710381163.2A CN201710381163A CN108933689A CN 108933689 A CN108933689 A CN 108933689A CN 201710381163 A CN201710381163 A CN 201710381163A CN 108933689 A CN108933689 A CN 108933689A
- Authority
- CN
- China
- Prior art keywords
- data
- collected
- detected
- analysis
- data collection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/02—Capturing of monitoring data
- H04L43/022—Capturing of monitoring data by sampling
- H04L43/024—Capturing of monitoring data by sampling by adaptive sampling
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Debugging And Monitoring (AREA)
Abstract
The present invention provides a kind of data collection system and methods, including two-level node, data collection agent and object to be detected；Wherein, data collection agent is set in each object to be detected, acquires the data to be collected in object to be detected；Two-level node obtains data to be collected, and carries out Macro or mass analysis based on data to be collected.Object to be detected and data acquisition are combined by implementation through the invention in a manner of loose coupling, are not interfere with each other between data acquisition and object to be detected normal operation, and can guarantee the flexibility of data acquisition to be collected, are convenient for aggregation process.
Description
Technical field
The present invention relates to data management field more particularly to a kind of data collection systems and method.
Background technique
In current virtualization system, generally only exist log system for error analysis and diagnosis and with it is virtual
The environmental information system of change system close-coupled.All logs of each module of virtualization can be collected by log system, just
In developer's positioning and problem analysis.But referring to FIG. 1, Fig. 1 is shown in the prior art, data collection system knot
The composition schematic diagram of structure, environmental information system due to virtualization system close coupling, have many problems, such as：It is unfavorable for pair
Various types of object datas are acquired and summarize, the data dispersion of acquisition；Due to environmental information system and the tight coupling of each module
It closes, has mutual interference between data acquisition and module operation itself, influence the normal operation of module, also influence data acquisition
Precision；And it is relatively difficult to data collection system progress Function Extension, the change to original module can be involved, it is unfavorable
In the extension of function.
Summary of the invention
The embodiment of the invention provides a kind of data collection system and methods, it is intended to solve close coupling institute band in the prior art
The problem of interference between the operation come and data acquisition, data are dispersed.
In order to solve the above-mentioned technical problem, the embodiment of the invention provides a kind of data collection systems, are applied to virtualization
System, including two-level node, data collection agent and object to be detected；Wherein, the data collection agent is set to each institute
It states in object to be detected, acquires the data to be collected in the object to be detected；The two-level node obtains the number to be collected
According to, and Macro or mass analysis is carried out based on the data to be collected.
In addition, the embodiment of the present invention also provides a kind of collecting method, including：
Acquire the data to be collected in object to be detected；
The data to be collected are obtained, and carry out Macro or mass analysis based on the data to be collected.
The beneficial effects of the invention are as follows：
The present invention provides a kind of data collection system and method, including two-level node, data collection agent and to be checked
Survey object；Wherein, data collection agent is set in each object to be detected, acquires the data to be collected in object to be detected；Two
Grade node obtains data to be collected, and carries out Macro or mass analysis based on data to be collected.Implementation through the invention, will be to be detected right
As being combined in a manner of loose coupling with data acquisition, data are acquired not to be interfere with each other between object to be detected normal operation,
And can guarantee the flexibility of data acquisition to be collected, it is convenient for aggregation process.
Detailed description of the invention
Fig. 1 is virtualization system composition schematic diagram in the prior art；
Fig. 2 is the data collection system structural schematic diagram that first embodiment of the invention provides；
Fig. 3 is a kind of collecting method flow chart that second embodiment of the invention provides；
Fig. 4 is a kind of collecting method flow chart that second embodiment of the invention provides；
Fig. 5 is a kind of collecting method flow chart that second embodiment of the invention provides.
Specific embodiment
Design point of the invention is, is arranged each object to be detected in a manner of agency, and based on agency service come into
The acquisition and transmitting-receiving process of row data, so realize the friendship between virtualization system and data collection system in a manner of loose coupling
Mutually, the flexibility ratio of system can be improved, reduce interference.
Specific embodiments of the present invention will be further explained with reference to the accompanying drawing.
First embodiment
Referring to FIG. 2, Fig. 2 is a kind of data collection system composition schematic diagram that first embodiment of the invention provides, including：
Two-level node 201, data collection agent 202 and object to be detected 203；Wherein, data collection agent 202 is set to each to be checked
It surveys in object 203, acquires the data to be collected in object 203 to be detected；Two-level node 201 obtains data to be collected, and is based on
Data to be collected carry out Macro or mass analysis.
System virtualization is referred to using virtualization software in a physical machine, fictionalizes one or more virtual machine,
Virtual machine is operated in an isolation environment, the logical computer with complete hardware function using system virtualization technology
System, including client operating system and application program therein.The major function of virtualization system is to various loose resources
The monitoring concentrated manages and maintains.
Data collection system in the present embodiment is applied to virtualization system, main to realize to mould each in virtualization system
Block, that is, the data collection and analysis process of each object to be detected 203.In the present embodiment, object 203 to be detected is exactly empty
Each component part in quasi-ization system is broadly divided into following a few classes：Management node, calculate node, virtual machine and terminal.Its
In, in the present embodiment, management node refers to the computer of all calculate nodes in one virtualized environment of management；And
Calculate node, which then refers to, provides the computer of virtualization capability；Virtual machine is then referred to be had completely by what software was simulated
Hardware capability, operate in the complete computer in a completely isolated environment.Wherein, virtual machine operates in calculate node
On.
In the present embodiment, data collection agent 202 is set in each object to be detected 203, acquires object 203 to be detected
Data to be collected.The module run in each object to be detected 203 namely virtualization system, data collection agent 202 are arranged
In object 203 to be detected, the operation of object 203 to be detected will not influence, object 203 to be detected will not influence data acquisition
Agency 202 treats the acquisition of generated data to be collected in the operation of test object 203, that is to say, that the present embodiment uses
A kind of mode of loose coupling, virtualization system and data collection system are combined.Data collection agent 202 it is collected to
Test object 203 includes four above-mentioned classes：Management node, calculate node, virtual machine and terminal.Due in these objects to be detected
In 203, virtual machine is operated in calculate node, and calculate node is to provide the computer of virtualization capability, then data acquire generation
Channel can be formed by by calculate node by managing 202 data to be collected collected, be sent to two-level node 201.
Wherein, in the present embodiment, the data to be collected acquired in object 203 to be detected may include：It determines to be detected
Object 203 and corresponding data to be collected and collection period, and generate corresponding configuration parameter；Configuration parameter is issued to
In object 203 to be detected；Data collection agent 202 parses configuration parameter, and executes adopting for data to be collected based on configuration parameter
Collection.Wherein it is determined that object 203 to be detected and data to be collected may include, it is required in the module in all virtualization systems
The module of detection, that is, object to be detected 203, and in these objects 203 to be detected, required data parameters, that is,
Data to be collected.It determines collection period, is exactly data collection agent 202 in which type of frequency collection object 203 to be detected
Data to be collected.It can also include sending cycle in addition, other than collection period, wherein refer to will be to be collected for sending cycle
Data are sent to the period of two-level node 201.
Two-level node 201 is the center of a management O&M, for realizing to number to be collected in a virtualization system
According to summarize storage, analysis and displaying.Wherein, summarize, refer in a virtualization system comprising it is multiple to be checked
Object 203, such as multiple virtual machines, multiple calculate nodes etc. are surveyed, these objects 203 to be detected are produced in the process of running
Corresponding data to be collected, by data collection agent 202 obtain after, be aggregated into two-level node 201.Storage, then
Referring to, these data to be collected are stored, and the target position of storage can be the database in two-level node 201,
The database being either located in other physical machines.
Wherein, carrying out Macro or mass analysis based on data to be collected may include：Corresponding quantization is formulated according to data to be collected
Index analyzes data to be collected.Corresponding quantizating index, it is corresponding according to the difference of the type of data to be collected
Quantizating index is also different.Each object to be detected 203 in the process of running, always has some parameters can area in normal and exception
Not, this difference, so that it may be determined by the way that corresponding quantizating index is arranged.Specifically, according to the difference of data type, wait adopt
Collecting data may include：At least one of resource data, operation data, performance data and daily record data.It is corresponding, according to
Data to be collected formulate corresponding quantizating index, carry out analysis to data to be collected and may include：It draws and data pair to be collected
The chart answered analyzes data to be collected.In the present embodiment, the concrete type of chart may include：What resource used
Time hotspot graph, the time hotspot graph of performance, virtual machine running track figure and module error statistical chart etc..Wherein, resource
The time hotspot graph used refers to point in different times, for the distribution condition of resource；And the time hotspot graph of performance,
Then refer to point in different times, the performance of object 203 to be detected.Module error statistical chart then may include, corresponding to be checked
It surveys object 203 and time, duration and the error reason etc. of mistake occurs, wherein the decision procedure of mistake can be and pass through log
The relationship between log content or other data and corresponding quantizating index in data determines.
After being analyzed based on data to be collected, in the present embodiment, two-level node 201 be can be also used for：According to
To the state of the analysis result judgement of data to be collected object 203 to be detected；If it is determined that object 203 to be detected has exception, then root
It is handled according to abnormal cause notification data Collection agent 202.After an analysis, and then can according to analysis as a result, come into
The malfunction elimination of row system and reparation.Specifically, according to the shape of the analysis result judgement object 203 to be detected to data to be collected
State may include：When data to be collected include performance data, according to performance data analysis system energy consumption；When data packet to be collected
When including operation data, according to operation data, the abnormality of each object 203 to be detected is monitored；When data to be collected include resource
When data, according to resource data Evaluation Environment resource consumption situation, and the distribution based on assessment result adjustment environmental resource；When to
When acquisition data include daily record data, according to daily record data location tasks executive condition, the running track of virtual machine is determined.It can be with
Find out, according to the difference of the type of each data to be collected, may be implemented in virtualization system, corresponding object 203 to be detected
Corresponding state judgement.Wherein, according to performance data analysis system energy consumption, the time hotspot graph of rendering performance can be passed through
Come carry out；According to resource data Evaluation Environment resource consumption situation, can be analyzed by resource using hotspot graph.Its
In, in the present embodiment, various types of data to be collected can be sent to two-level node 201 by various modes.Log number
According to that can export by original log system, the acquisition to the key log of all critical workflows is realized；Key log is adopted
The rule of collection may include：Log information is stamped into corresponding identity information, including module belonging to the daily record data, submodule
The step of block, process, execution and result etc.；Then, based on the identity information of daily record data, daily record data can be carried out
Filter.Operation data is by data collection agent 202 to system core module, that is, 203 process of object to be detected and resource consumption
More is acquired；Resource data is then acquired in virtualized environment by data collection agent 202, the usage amount of resource；
Performance data is acquired the performance data of the key objects such as network interface card, block device by data collection agent 202.It is only arranged in the present embodiment
Some of data and corresponding acquisition mode have been lifted, has limited specific data to be collected and its acquisition mode there is no specific,
Other data in virtualization system can be acquired by other means under the premise of meeting present inventive concept, that is to say, that
The data collection system of the present embodiment can extend to various types of objects, with the proviso that, according to specified data format pair
The data to be collected of acquisition are packaged.Therefore, system can be easily scalable to various types of management nodes, calculate section
In point, virtual machine and terminal.Facilitate the type for extending data to be collected, core is the format for defining data to be collected.
In addition, can also include first nodes 204, for summarizing the second level section in each virtualization system in the present embodiment
The data to be collected of 201 Macro or mass analysis of point.Two-level node 201 is the Macro or mass analysis to a virtualized environment, and level-one section
The data to be collected of different virtualized environments then can be carried out Macro or mass analysis by point 204.First nodes 204 and two-level node 201
Between typically just function difference, may not have any different on actual hardware.First nodes 204 are realized to different virtual
Change system summarizes management comprising with the virtualized environment of framework, for example multiple is based on kvm (Keyboard Video
Mouse, keyboard, display and mouse) virtualized environment；Or multiple virtualized environments based on isomery, for example it is based on kvm
Virtualized environment and virtualized environment based on xen.
The present invention provides a kind of data collection systems, including two-level node, data collection agent and object to be detected；
Wherein, data collection agent is set in each object to be detected, acquires the data to be collected in object to be detected；Two-level node obtains
Data to be collected are taken, and carry out Macro or mass analysis based on data to be collected.By the implementation of the present embodiment, by object sum number to be detected
It is combined, is not interfere with each other between data acquisition and object to be detected normal operation, and can be protected in a manner of loose coupling according to acquisition
The flexibility for demonstrate,proving data acquisition to be collected, is convenient for aggregation process.
Second embodiment
Referring to FIG. 3, Fig. 3 is a kind of collecting method flow chart that second embodiment of the invention provides, including：
Data to be collected in S301, acquisition object to be detected；
S302, data to be collected are obtained, and carries out Macro or mass analysis based on data to be collected.
In S301, data collection agent is set in each object to be detected, acquires the data to be collected of object to be detected.Respectively
The module run in object i.e. virtualization system to be detected, data collection agent are set in object to be detected, Bu Huiying
Ring the operation of object to be detected, object to be detected will not influence caused by data collection agent treats in test object operation
The acquisition of data to be collected, that is to say, that the present embodiment adopts virtualization system and data by the way of a kind of loose coupling
Collecting system is combined.Data collection agent object to be detected collected includes four above-mentioned classes：Management node calculates section
Point, virtual machine and terminal.Since in these objects to be detected, virtual machine is operated in calculate node, and calculate node is to provide
The computer of virtualization capability, then data collection agent data to be collected collected can be formed by by calculate node
Channel is sent to two-level node.
Wherein, in the present embodiment, referring to FIG. 4, the data to be collected acquired in object to be detected may include：
S401, object to be detected and corresponding data to be collected and collection period are determined, and generates corresponding configuration ginseng
Number；
S402, configuration parameter is issued in object to be detected；
S403, data collection agent parse configuration parameter, and the acquisition of data to be collected is executed based on configuration parameter.
Wherein it is determined that object to be detected and data to be collected may include, it is required in the module in all virtualization systems
The module to be detected, that is, object to be detected, and in these objects to be detected, required data parameters, that is, wait adopt
Collect data.It determines collection period, is exactly data collection agent with the number to be collected in which type of frequency collection object to be detected
According to.In addition, can also include sending cycle, wherein sending cycle, which refers to, is sent to data to be collected other than collection period
The period of two-level node.
Two-level node is the center of a management O&M, for realizing to data to be collected in a virtualization system
Summarize storage, analysis and displaying.Wherein, summarize, refer in a virtualization system comprising it is multiple to be detected right
As, such as multiple virtual machines, multiple calculate nodes etc., these objects to be detected in the process of running caused by it is corresponding to
Data are acquired, after being obtained by data collection agent, are aggregated into two-level node.Storage, then refer to, these are to be collected
Data are stored, and the target position of storage can be the database in two-level node, or be located at other physical machines
In database.
In S302, carrying out Macro or mass analysis based on data to be collected may include：Corresponding amount is formulated according to data to be collected
Change index, data to be collected are analyzed.Corresponding quantizating index is corresponded to according to the difference of the type of data to be collected
Quantizating index it is also different.Each object to be detected in the process of running, always has some parameters can area in normal and exception
Not, this difference, so that it may be determined by the way that corresponding quantizating index is arranged.Specifically, according to the difference of data type, wait adopt
Collecting data may include：At least one of resource data, operation data, performance data and daily record data.It is corresponding, according to
Data to be collected formulate corresponding quantizating index, carry out analysis to data to be collected and may include：It draws and data pair to be collected
The chart answered analyzes data to be collected.In the present embodiment, the concrete type of chart may include：What resource used
Time hotspot graph, the time hotspot graph of performance, virtual machine running track figure and module error statistical chart etc..Wherein, resource
The time hotspot graph used refers to point in different times, for the distribution condition of resource；And the time hotspot graph of performance,
Then refer to point in different times, the performance of object to be detected.Module error statistical chart then may include, corresponding to be detected
There is time, duration and the error reason etc. of mistake in object, wherein the decision procedure of mistake can be and pass through daily record data
In log content or other data and corresponding quantizating index between relationship determine.
After being analyzed based on data to be collected, in the present embodiment, summarize point based on data to be collected
After analysis, can also include：According to the state of the analysis result judgement object to be detected to data to be collected；If it is determined that be detected
Object has exception, then is handled according to abnormal cause notification data Collection agent.Specifically, referring to FIG. 5, the process of analysis processing
It is as follows：
S501, data to be collected are analyzed；
S502, abnormal process is judged based on the analysis results；
S503, it is performed corresponding processing according to judging result.
It after an analysis, and then can be according to analysis as a result, to carry out the malfunction elimination of system and reparation.Specifically
, the state according to the analysis result judgement object to be detected to data to be collected may include：When data to be collected are inclusive
When energy data, according to performance data analysis system energy consumption；When data to be collected include operation data, according to operation data, prison
Control the abnormality of each object to be detected；When data to be collected include resource data, according to resource data Evaluation Environment resource
Expenditure Levels, and the distribution based on assessment result adjustment environmental resource；When data to be collected include daily record data, according to log
Data location tasks executive condition, determines the running track of virtual machine.As can be seen that not according to the type of each data to be collected
Together, the judgement of the corresponding state of corresponding object to be detected in virtualization system may be implemented.Wherein, according to performance number
According to analysis system energy consumption, can be carried out by the time hotspot graph of rendering performance；Disappeared according to resource data Evaluation Environment resource
Situation is consumed, can be analyzed by resource using hotspot graph.Wherein, in the present embodiment, various types of numbers to be collected
According to two-level node can be sent to by various modes.Daily record data can be exported by original log system, realization pair
The acquisition of the key log of all critical workflows；Key log acquisition rule may include：Log information is stamped accordingly
Identity information includes the steps that module belonging to the daily record data, submodule, process, execution and result etc.；Then, base
In the identity information of daily record data, daily record data can be filtered.Operation data is by data collection agent to system core mould
Block, that is, object process to be detected and resource consumption is more is acquired；Resource data is then by data collection agent
It acquires in virtualized environment, the usage amount of resource；Performance data is by key objects such as data collection agent acquisition network interface card, block devices
Performance data.Some of data and corresponding acquisition mode only are listed in the present embodiment, limits spy there is no specific
Fixed data to be collected and its acquisition mode can acquire virtualization by other means under the premise of meeting present inventive concept
Other data in system, that is to say, that the data collection system of the present embodiment can extend to various types of objects, before
Mentioning is, is packaged according to be collected data of the specified data format to acquisition.Therefore, system can be easily scalable to respectively
In the management node of seed type, calculate node, virtual machine and terminal.Facilitate the type for extending data to be collected, core is
Define data format to be collected.In addition, can then be transported by corresponding interface notification for the new exception for not finding solution
Dimension personnel carry out artificial treatment.
In addition, can also include first nodes, for summarizing the two-level node institute in each virtualization system in the present embodiment
The data to be collected of Macro or mass analysis.Two-level node is the Macro or mass analysis to a virtualized environment, and first nodes can then incite somebody to action
The data to be collected of different virtualized environments carry out Macro or mass analysis.Typically just function is not between first nodes and two-level node
Together, it may not have any different on actual hardware.First nodes realization summarizes management to different virtualization systems comprising
With the virtualized environment of framework, such as multiple virtualized environments based on kvm；Or multiple virtualized environments based on isomery,
Such as the virtualized environment based on kvm and the virtualized environment based on xen.
The present invention provides a kind of collecting method, the data to be collected in object to be detected are acquired；Two-level node obtains
Data to be collected are taken, and carry out Macro or mass analysis based on data to be collected.By the implementation of the present embodiment, by object sum number to be detected
It is combined, is not interfere with each other between data acquisition and object to be detected normal operation, and can be protected in a manner of loose coupling according to acquisition
The flexibility for demonstrate,proving data acquisition to be collected, is convenient for aggregation process.
Obviously, those skilled in the art should be understood that each module of aforementioned present invention or each step can be with general
Computing device realizes that they can be concentrated on a single computing device, or be distributed in constituted by multiple computing devices
On network, optionally, they can be realized with the program code that computing device can perform, it is thus possible to be stored in
It is performed by computing device in storage medium (ROM/RAM, magnetic disk, CD), and in some cases, it can be to be different from this
The sequence at place executes shown or described step, perhaps they are fabricated to each integrated circuit modules or by it
In multiple modules or step be fabricated to single integrated circuit module to realize.So the present invention is not limited to any specific
Hardware and software combine.
The above content is specific embodiment is combined, further detailed description of the invention, and it cannot be said that this hair
Bright specific implementation is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, it is not taking off
Under the premise of from present inventive concept, a number of simple deductions or replacements can also be made, all shall be regarded as belonging to protection of the invention
Range.
Claims (13)
1. a kind of data collection system is applied to virtualization system, which is characterized in that including two-level node, data collection agent
And object to be detected；Wherein, the data collection agent is set in each object to be detected, and it is described to be detected right to acquire
Data to be collected as in；The two-level node obtains the data to be collected, and is summarized based on the data to be collected
Analysis.
2. data collection system as described in claim 1, which is characterized in that further include first nodes, the first nodes are used
In the data to be collected for summarizing the two-level node institute Macro or mass analysis in each virtualization system.
3. data collection system as described in claim 1, which is characterized in that described to be summarized based on the data to be collected
Analysis includes：
Corresponding quantizating index is formulated according to the data to be collected, the data to be collected are analyzed.
4. data collection system as claimed in claim 3, which is characterized in that described formulated according to the data to be collected corresponds to
Quantizating index, to the data to be collected carry out analysis include：
Chart corresponding with the data to be collected is drawn, the data to be collected are analyzed.
5. data collection system according to any one of claims 1-4, which is characterized in that the two-level node is also used to：
According to the state of the analysis result judgement object to be detected to the data to be collected；
If it is determined that the object to be detected has exception, then the data collection agent is notified to handle according to abnormal cause.
6. data collection system as claimed in claim 5, which is characterized in that the data to be collected include resource data, fortune
At least one of row data, performance data and daily record data；The basis sentences the analysis result of the data to be collected
The state of object to be collected includes calmly：
When the data to be collected include performance data, according to the performance data analysis system energy consumption；
When the data to be collected include operation data, according to the operation data, the different of each object to be detected is monitored
Normal state；
When the data to be collected include resource data, according to the resource data Evaluation Environment resource consumption situation, and base
The distribution of the environmental resource is adjusted in assessment result；
When the data to be collected include daily record data, according to the daily record data location tasks executive condition, determine virtual
The running track of machine.
7. data collection system according to any one of claims 1-4, which is characterized in that the acquisition object to be detected
In data to be collected include：
It determines the object to be detected and corresponding data to be collected and collection period, and generates corresponding configuration parameter；
The configuration parameter is issued in object to be detected；
The data collection agent parses the configuration parameter, and executes adopting for the data to be collected based on the configuration parameter
Collection.
8. data collection system according to any one of claims 1-4, which is characterized in that the object to be collected includes：Pipe
Manage at least one of node, calculate node, virtual machine and terminal.
9. a kind of collecting method, including：
Acquire the data to be collected in object to be detected；
The data to be collected are obtained, and carry out Macro or mass analysis based on the data to be collected.
10. collecting method as claimed in claim 9, which is characterized in that after the acquisition data to be collected,
Further include：
Summarize the data to be collected of the two-level node institute Macro or mass analysis in each virtualization system.
11. collecting method as claimed in claim 9, which is characterized in that described to be converged based on the data to be collected
Bulk analysis includes：
Corresponding quantizating index is formulated according to the data to be collected, the data to be collected are analyzed.
12. collecting method as claimed in claim 9, which is characterized in that carried out described based on the data to be collected
After Macro or mass analysis, further include：
According to the state of the analysis result judgement object to be detected to the data to be collected；
If it is determined that the object to be detected has exception, then the data collection agent is notified to handle according to abnormal cause.
13. setting as claim 9-12 is described in any item, which is characterized in that in the acquisition object to be detected wait adopt
Collecting data includes：
It determines the object to be detected and corresponding data to be collected and collection period, and generates the configuration parameter to application；
The configuration parameter is issued in object to be detected；
The configuration parameter is parsed, and executes the acquisition of the data to be collected based on the configuration parameter.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710381163.2A CN108933689A (en) | 2017-05-25 | 2017-05-25 | A kind of data collection system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710381163.2A CN108933689A (en) | 2017-05-25 | 2017-05-25 | A kind of data collection system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108933689A true CN108933689A (en) | 2018-12-04 |
Family
ID=64450911
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710381163.2A Pending CN108933689A (en) | 2017-05-25 | 2017-05-25 | A kind of data collection system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108933689A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112445674A (en) * | 2019-08-30 | 2021-03-05 | 中国石油化工股份有限公司 | Data processing method and storage medium of computer cluster |
| CN113726647A (en) * | 2021-08-30 | 2021-11-30 | 中国联合网络通信集团有限公司 | Identification analysis method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102891864A (en) * | 2011-07-18 | 2013-01-23 | 北京邮电大学 | Method for acquiring and analyzing credible data of cloud resources based on distributed Agent |
| CN103888287A (en) * | 2013-12-18 | 2014-06-25 | 北京首都国际机场股份有限公司 | Information system integrated operation and maintenance monitoring service early warning platform and realization method thereof |
| CN104113596A (en) * | 2014-07-15 | 2014-10-22 | 华侨大学 | Cloud monitoring system and method for private cloud |
| WO2015184850A1 (en) * | 2014-07-22 | 2015-12-10 | 中兴通讯股份有限公司 | Method, apparatus and system for collecting stale data |
-
2017
- 2017-05-25 CN CN201710381163.2A patent/CN108933689A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102891864A (en) * | 2011-07-18 | 2013-01-23 | 北京邮电大学 | Method for acquiring and analyzing credible data of cloud resources based on distributed Agent |
| CN103888287A (en) * | 2013-12-18 | 2014-06-25 | 北京首都国际机场股份有限公司 | Information system integrated operation and maintenance monitoring service early warning platform and realization method thereof |
| CN104113596A (en) * | 2014-07-15 | 2014-10-22 | 华侨大学 | Cloud monitoring system and method for private cloud |
| WO2015184850A1 (en) * | 2014-07-22 | 2015-12-10 | 中兴通讯股份有限公司 | Method, apparatus and system for collecting stale data |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112445674A (en) * | 2019-08-30 | 2021-03-05 | 中国石油化工股份有限公司 | Data processing method and storage medium of computer cluster |
| CN113726647A (en) * | 2021-08-30 | 2021-11-30 | 中国联合网络通信集团有限公司 | Identification analysis method and device |
| CN113726647B (en) * | 2021-08-30 | 2022-07-29 | 中国联合网络通信集团有限公司 | Identification analysis method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | Understanding and addressing quality attributes of microservices architecture: A Systematic literature review | |
| EP3243136B1 (en) | Dynamic telemetry message profiling and adjustment | |
| US10592372B2 (en) | Confidence-controlled sampling methods and systems to analyze high-frequency monitoring data and event messages of a distributed computing system | |
| US10747592B2 (en) | Router management by an event stream processing cluster manager | |
| US8819701B2 (en) | Cloud computing monitoring and management system | |
| US10762452B2 (en) | System and method for designing and executing control loops in a cloud environment | |
| US10353799B2 (en) | Testing and improving performance of mobile application portfolios | |
| EP2609507B1 (en) | Evaluating dataflow graph characteristics | |
| US20100198636A1 (en) | System and method for auditing governance, risk, and compliance using a pluggable correlation architecture | |
| CN109831478A (en) | Rule-based and model distributed processing intelligent decision system and method in real time | |
| CN109684052B (en) | Transaction analysis method, device, equipment and storage medium | |
| Bhaduri et al. | Detecting abnormal machine characteristics in cloud infrastructures | |
| CN108337266A (en) | A kind of efficient protocol client vulnerability mining method and system | |
| CN105740142A (en) | Pressure test management system for SSR (Server Security Reinforcement) centralized management platform | |
| Hammad et al. | Provenance as a service: A data-centric approach for real-time monitoring | |
| Majumdar et al. | Learning probabilistic dependencies among events for proactive security auditing in clouds | |
| CN108933689A (en) | A kind of data collection system and method | |
| Schütte et al. | Model-based security event management | |
| US20200213203A1 (en) | Dynamic network health monitoring using predictive functions | |
| WO2011115983A1 (en) | Automated governance, risk management, and compliance integration | |
| Oppermann et al. | Anomaly Detection Approaches for Secure Cloud Reference Architectures in Legal Metrology. | |
| Kai et al. | Development of qualification of security status suitable for cloud computing system | |
| Bovenzi et al. | Towards identifying OS-level anomalies to detect application software failures | |
| Carata | Provenance-based computing | |
| CN109271296A (en) | A kind of jelly screen test method |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181204 |