CN107302569A - A kind of security monitoring Data acquisition and storage method of facing cloud platform - Google Patents
A kind of security monitoring Data acquisition and storage method of facing cloud platform Download PDFInfo
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- CN107302569A CN107302569A CN201710427689.XA CN201710427689A CN107302569A CN 107302569 A CN107302569 A CN 107302569A CN 201710427689 A CN201710427689 A CN 201710427689A CN 107302569 A CN107302569 A CN 107302569A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24552—Database cache management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/56—Provisioning of proxy services
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Abstract
The present invention relates to a kind of security monitoring Data acquisition and storage method of facing cloud platform, this method includes:Remote and local message queues are initialized successively, obtain the relevant information of collection plug-in unit;Data acquisition rear end obtains cloud platform basic data according to the plugin information operation collection plug-in unit loaded;The data collected are sent to transmission agency by data acquisition rear end by message queue;Start transmission and act on behalf of broker, the agency is responsible for communicating with monitoring agent, and collection monitoring data are simultaneously saved into database.By the timestamp of all documents of TagModel and MetricModel, it is buffered in internal memory;TagModel is inquired about in the buffer, obtains the Tags of monitor control index;Insert a record simultaneously into caching and database or using Tags and timestamp as querying condition, inquiry is stored in database so as to update the data respective document or the new document of generation one in storehouse in current monitor measured value MODEL C urrentModel.The present invention is obtained comprehensively and storage mode is reasonable, will not produce repetition storage.
Description
Technical field
The present invention relates to a kind of cloud platform security monitoring data processing method, more particularly to a kind of safety of facing cloud platform
Monitoring data collection and storage method.
Background technology
Cloud computing has attracted the height of academia and industrial quarters with advantages such as its with low cost, rapid deployment and scaleables
Concern, at the same time, security monitoring and analysis for cloud platform also become study hotspot.
But the basic data granularity that existing virtual platform is collected is excessively thick, it is impossible to which accurately reflection cloud platform is pacified in time
Total state.
Multiple virtualization softwares coexist in cloud platform, the variation of basic data source, lack unified expression, are not suitable for
It is directly used in displaying and analysis.
Cloud platform data source spreads all over the at all levels of whole counting system, forgives main frame, network, and storage etc. is on-line off-line rich
Rich data source.However, including ultra-large service node inside cloud platform, during node is interior and comprising magnanimity, level is complicated
Service, can also form baroque network in large scale between node.The basic data collected from all kinds of nodes, service
Collect many as level, data volume is big, the complicated data set of data type.Information extraction and analysis are carried out to such data set
It is very difficult.
The content of the invention
Technical problem to be solved of the embodiment of the present invention is, is adopted for existing cloud platform from all kinds of nodes, service
The basic data collected collects many as level, and data volume is big, and the complicated data set of data type is carried out to such data set
A kind of the problem of information extraction and very difficult analysis, it is proposed that the security monitoring Data acquisition and storage side of facing cloud platform
Method.
In order to solve the above-mentioned technical problem, adopted the embodiments of the invention provide a kind of security monitoring data of facing cloud platform
Collection and storage method, including step:Initial message queue step, initializes monitoring agent and is transferred to cloud computing platform successively
Message queue remote and monitoring agent are transferred to the message queue local being locally stored;Collection plug-in unit step is loaded into, acquisition is adopted
Collect the relevant information of plug-in unit;Obtained according to the plugin information operation collection plug-in unit loaded gathered data step, data acquisition rear end
Take cloud platform basic data;Data step is sent, the data collected are sent to biography by data acquisition rear end by message queue
Defeated agency;Above-mentioned steps are data collection steps, and the following steps are data storing steps:Start transmission and act on behalf of broker, pre-read
The timestamp of all documents of TagModel and MetricModel, and be buffered in internal memory;Inquire about in the buffer
TagModel, obtains the Tags of monitor control index;If cache hit, one record of insertion simultaneously into caching and database;If
Cache miss, then using Tags and timestamp as querying condition, inquire about in CurrentModel;There is phase if inquiring
Document is answered, then updates the data the Value values of respective document in storehouse;If not inquiring and there is respective document, generation one is needed
New document, is stored in database.
Wherein, when carrying out data storage, uniform data expression way is used.
Wherein, uniform data expression way is to use four-tuple:Name, Tags, Value and TimeStamp are described
One monitoring data.
Wherein, when carrying out data storage, data deduplication processing is carried out.
Wherein, when carrying out data deduplication processing, including following two steps:Basic data label is separated;Data compression.
Wherein, the step of basic data label is separated includes:Name the and Tags fields that redundancy is concentrated independently go out
It is used as TagModel, other models are using TagModel as external key, to realize label separation mechanism.
Wherein, data compressing step includes:During by the compression storing data in the scheduled time a to document to reduce
The monitor control index data redundancy that sequence is brought, meanwhile, increase cur_v and cur_t fields difference table in MetricModel
Show the latest data and newest timestamp in current hour.
Wherein, when carrying out data storage, to need the TagModel often inquired about to increase caching, and it is
The state that MetricModel caching current documents whether there is.
Implement the embodiment of the present invention, have the advantages that:The present invention is by gathering plug-in unit from multiple nodes acquisition cloud
Platform base data, obtain comprehensive, and storage mode is rationally, will not produce repetition storage.
Brief description of the drawings
Fig. 1 is the flow of the security monitoring Data acquisition and storage method of the facing cloud platform of first embodiment of the invention
Figure;
Fig. 2 is collection plug-in unit traffic diagram;
Fig. 3 is collection dongle configuration figure.
Embodiment
The technical scheme in the embodiment of the present invention will be clearly and completely described below, it is clear that described implementation
Example only a part of embodiment of the invention, rather than whole embodiments.Based on the embodiment in the present invention, this area is common
The every other embodiment that technical staff is obtained under the premise of creative work is not made, belongs to the model that the present invention is protected
Enclose.
Referring to Fig. 1 and Fig. 2, Fig. 1 is the security monitoring data acquisition of the facing cloud platform of first embodiment of the invention with depositing
The flow chart of method for storing, Fig. 2 is collection plug-in unit traffic diagram.Adopted the invention provides a kind of security monitoring data of facing cloud platform
Collection and storage method, the security monitoring Data acquisition and storage method of the facing cloud platform include step:
In step s 11, initial message queue step, initializes monitoring agent and is transferred to disappearing for cloud computing platform successively
Breath queue remote and monitoring agent are transferred to the message queue local being locally stored.Remote queue remote_mq be responsible for
Data Transport Agent is connected, and local queue local_mq is used for the message for collecting local platform agency.
In step s 12, collection plug-in unit step is loaded into, the relevant information of collection plug-in unit is obtained.Specially:Read plug-in unit
Configuration information plugin_desc, obtains the order line of collection plug-in unit, the information such as data target.
In step s 13, inserted according to the plugin information operation collection loaded gathered data step, data acquisition rear end
Part, obtains cloud platform basic data.In this step, further it is polled and updates the data step, institute in traversal configuration file
There is the description information of plug-in unit, it is grouped according to polling cycle.Each cycle polling once, updates monitor control index.
In step S14, data step is sent, the data collected are sent to by data acquisition rear end by message queue
Transmission agency.
In step S15, start transmission act on behalf of broker, pre-read all documents of TagModel and MetricModel when
Between stab, and be buffered in internal memory.
In step s 16, TagModel is inquired about in the buffer, obtains the Tags of monitor control index.If cache hit, enter
Step S17.If cache miss, into step S18.
In step S17, if cache hit, one record of insertion simultaneously into caching and database.
In step S18, if cache miss, using Tags and timestamp as querying condition, in CurrentModel
Middle inquiry.There is respective document if inquiring, into step S19.If not inquiring and there is respective document, into step
S20。
In step S19, there is respective document if inquiring, update the data the Value values of respective document in storehouse.
In step S20, there is respective document if not inquiring, need to generate a new document, be stored in database.
Wherein, step S11~step S14 is data collection steps, and step S15~step S20 is data storing steps.
Label model TagModel is pre-read by the agency:{ Name, Tags } and history monitor measured value model
MetricModel:The timestamp of { Name, Tags, Timestamp, Value } all documents, and be buffered in internal memory;
TagModel is inquired about in caching, the Tags of monitor control index is obtained;To caching and database in simultaneously insertion one record or with
Tags and timestamp are as querying condition, in current monitor measured value MODEL C urrentModel:{Name,Tags,
Timestamp, Value } middle inquiry;If the Value values that respective document in storehouse is updated the data if inquiring;Needed if not inquiring
Generate a new document deposit database.
Refering to Fig. 3, Fig. 3 is collection dongle configuration figure.Data collecting mechanism is divided into two layers:Data acquisition plug-in unit, data are adopted
Collect rear end.
Data acquisition plug-in unit provides uniform data collection API and called for data acquisition rear end, and acquiescence used herein is adopted
Collecting plug-in unit includes VSphere/VCenter platform plug-ins, service discovery plug-in unit, windows platform monitorings plug-in unit, linux platforms
Plug-in unit is monitored, user can voluntarily add plug-in unit as needed;It is responsible for according to configuration file specific control data data acquisition rear end
Gather the behavior, the preliminary filtering of data and periodically transmission of plug-in unit.
After data acquisition rear end starts, configuration file is read first, confirms running environment and the data acquisition of monitoring agent
Task (as be located at physical host Linux server, need collection cloud nodal information and physical host running status), according to
File configuration agency is put, corresponding data acquisition plug-in unit is loaded, the monitoring index for periodically calling collection plug-in unit to obtain.
Basic data storage method is as follows:
The characteristics of there is source data isomery due to cloud platform monitoring data, to ensure the compatibility of storage uniformity and data source
Property, it is necessary to design unified, be easy to interaction and store, therefore when carrying out data storage, use uniform data expression way.
This programme uses four-tuple:Name, Tags, Value and TimeStamp describe a monitoring data, and it is determined
Justice is:
Name:The title of measured value is monitored, e.g., cpu_usage represents cpu loads.
Tags:The adeditive attribute of measured value is monitored, is a dictionary structure, is mainly used to represent the source (collection of measured value
Group, main frame, virtual machine), type, unit etc..
Value:The specific measured value of measured value is monitored, can be an array or dictionary.
TimeStamp:Monitor precise time stamp when measured value is obtained.
Obviously, { Name, Tags, TimeStamp } triple can uniquely position a data point, use wherein any one
Or two can obtain the volume of data point for meeting certain condition.This form can not only may also be used for making for storage
For the data interaction form between system module.This data format can easily be converted into JSON.Even if monitoring server
Or monitoring agent employs the realization of other programming languages, JSON is also well positioned to meet the compatibility of message transmission between service
Property and interactivity.Meanwhile, the storage of this form can be easily extended:When increasing new monitored object, only need
The object type is added toward monitoring measurement value list.
Wherein, when carrying out data storage, data deduplication processing is carried out.And when carrying out data deduplication processing, including such as
Lower two steps:The separation of basic data label, data compression.
Data label is separated:Basis is turned to anti-normal form herein and carries out data storage, but by monitoring data various dimensions, it is tree-like
The characteristics of structure, most dimension high duplication (low cardinality), using anti-normal formization it is expected that will necessarily be introduced
Bulk redundancy information.When monitoring cluster increase, when monitor control index increases, excessive space consuming can be brought.Therefore herein using mark
Sign separation mechanism, Name the and Tags fields that redundancy is concentrated are independent as TagModel, other models with
TagModel is external key, to realize label separation mechanism.
Data compression:Data compression scheme is used to eliminate monitor control index data redundancy.Monitoring data is timing data, phase
Same monitor control index, timestamp is different, can have a plurality of document in database.When in a period of time, monitor control index is relatively steady
Regularly, this plurality of record is except timestamp difference is without any other difference.And arrive the compression storing data in a period of time
The monitor control index data redundancy that timing is brought can be greatly reduced in one document.Meanwhile, current data is inquired about for convenience,
Increase cur_v and cur_t fields represent the latest data and newest timestamp in current hour respectively in MetricModel.
The most direct benefit that this storage mode is brought is that record strip number is largely reduced.Represented to compress duration with T, per t
Second updates the compression ratio p=T/t of a data, then record strip number.Every document size is vp, measurement index size is vi, directly
Space needed for storing the data of T time section is V=pvp=Tvp/ t, after compression storage, space needed for the data of storage T time section
For Vc=vp+vip-vi=vp+(T-t)vi/t;Compression ratio is p '=V/Vc=vpT/vpt+(T-t)vi.If a length of one during compression
Hour, a data is updated within every 2 seconds, the mean size of every document is 200B, and measured value mean size is 16B.Then compression ratio
For 12:1.Further, since only storing the data changed, monitoring agent need to only send data in data variation, can significantly
Reduction network (queue) loads and reduced the pressure that transmission agency receives data.
Preheating caching mechanism is used to eliminate the write-in enlarge-effect in storing process.Though data compression and label separation mechanism
Data redundancy can be so reduced, space availability ratio is improved, but can also increase the complexity of data structure simultaneously, serious number is brought
Scale-up problem is write according to storehouse.Such as Fig. 3, by taking performance data as an example, the first number of certain monitor control index according to during feeding database, it is necessary to
2 inquiries and 2 write operations are done, could be the complete write into Databasce of data.Even if under normal circumstances, monitoring data
Tags can be inquired about in TagModel and obtained, it is still necessary to 2 inquiries, 1 modification (or 1 write-in).Obviously it is such to write amplification
Effect can not meet actual demand.
Solution is cached to need the TagModel often inquired about to increase, and ought be above for MetricModel cachings
The state that shelves whether there is.TagModel, even monitoring large-scale cloud platform, is monitored equivalent to a catalogue listing of monitor control index
All Tag of index also will not be too many, so TagModel can be buffered in internal memory completely.In the situation of cache hit
Under, it is only necessary to 1 time write-in (renewal) can complete data storage.
And actually only have TagModel cachings under rare occasion not hit:
(1) if not having data in database, the TagModel cachings that internal memory is read in advance are sky, are now occurred every time new
Tags, TagModel cache all without hit.
(2) during querying condition mistake, TagModel cachings will not be hit.
(3) a document deposit database can be generated after the completion of control operation, this document is inquired about before this,
TagModel cachings will not be hit.
(4) when the reason such as monitor control index change or the change of cloud platform node causes new Tags generations, TagModel delays
Depositing to hit.
In most cases, TagModel cache hit rates are 100%, and its time complexity inquired about is O (1),
The problem of having substantially solved write-in amplification.
That is, when carrying out data storage, to need the TagModel often inquired about to increase caching, and being
The state that MetricModel caching current documents whether there is.
The present invention has following advantage compared with prior art:
(1) basic data collected with reference to virtual machine/host monitor agency with virtual platform monitoring agent, is improved
The precision and range of cloud platform basic data acquisition.
(2) present invention uses plug-in unit Collection agent, supports all kinds of cloud platforms, facilitates secondary development.
(3) uniform data expression way, label separation, data compression and preheating four kinds of mechanism of caching are combined, are offset each other
Deficiency, comprehensive raising data storage performance.For the efficient write-in of monitoring data, update expansible and light with inquiry and data
Magnitude data maintenance characteristics, which are provided, to be ensured.
Implement the embodiment of the present invention, have the advantages that:The present invention is by gathering plug-in unit from multiple nodes acquisition cloud
Platform base data, obtain comprehensive, and storage mode is rationally, will not produce repetition storage.
These are only presently preferred embodiments of the present invention, be not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent substitution and improvements made etc. should be included in the scope of the protection.
Claims (8)
1. a kind of security monitoring Data acquisition and storage method of facing cloud platform, it is characterised in that the facing cloud platform
Security monitoring Data acquisition and storage method includes:
Initial message queue step, initializes remote and local message queues successively;
Collection plug-in unit step is loaded into, the relevant information of collection plug-in unit is obtained;
Gathered data step, data acquisition rear end obtains cloud platform basis according to the plugin information operation collection plug-in unit loaded
Data;
Data step is sent, the data collected are sent to transmission agency by data acquisition rear end by message queue;
Above-mentioned steps are data collection steps, and the following steps are data storing steps:
Start transmission and act on behalf of broker, pre-read the timestamp of all documents of TagModel and MetricModel, and be buffered in
In internal memory;
TagModel is inquired about in the buffer, obtains the Tags of monitor control index;
If cache hit, one record of insertion simultaneously into caching and database;
If cache miss, using Tags and timestamp as querying condition, inquired about in CurrentModel;
There is respective document if inquiring, update the data the Value values of respective document in storehouse;
If not inquiring and there is respective document, need to generate a new document, be stored in database.
2. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 1, it is characterised in that
When carrying out data storage, uniform data expression way is used.
3. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 2, it is characterised in that institute
Uniform data expression way is stated to use four-tuple:Name, Tags, Value and TimeStamp monitor number to describe one
According to.
4. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 3, it is characterised in that
When carrying out data storage, data deduplication processing is carried out.
5. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 4, it is characterised in that
When carrying out data deduplication processing, including following two steps:
Basic data label is separated;
Data compression.
6. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 5, it is characterised in that institute
Stating the step of basic data label is separated includes:Name and Tags fields that redundancy is concentrated it is independent as
TagModel, other models are using TagModel as external key, to realize label separation mechanism.
7. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 5, it is characterised in that institute
Stating data compressing step includes:By what is brought in the compression storing data in the scheduled time a to document with reducing timing
Monitor control index data redundancy, meanwhile, increase cur_v and cur_t fields were represented in current hour respectively in MetricModel
Latest data and newest timestamp.
8. the security monitoring Data acquisition and storage method of facing cloud platform according to claim 4, it is characterised in that
When carrying out data storage, to need the TagModel often inquired about to increase caching, and current document being cached for MetricModel to be
The state of no presence.
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CN115022402A (en) * | 2022-07-01 | 2022-09-06 | 杭州乘云数字技术有限公司 | Agent acquisition method and system based on one-stack integration technology |
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