A cloud resource division, monitoring and data analysis method based on label technology

Abstract

The application discloses a cloud resource division, monitoring and data analysis method based on a label technology, comprising a cloud platform, a processing layer, an abstraction layer and a display layer; the cloud platform is used for index collection, event monitoring and reporting data labeling of a monitored resource object; the processing layer is responsible for complex business operations between each cloud resource of the cloud platform and a twin object; the abstraction layer is used for establishing a unified resource twin object model and a label list, and continuously and dynamically labeling the model according to the model structure to reflect the latest state of the current monitored cloud resource; the abstraction of the twin object simplifies the heavy cloud resource object (and a set thereof) monitoring operation, shields the complex characteristics (dynamicity, migration and scalability) of the cloud resource, and converts the related resource monitoring into a twin object label, thereby improving the monitoring efficiency of the cloud resource object.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular, to a cloud resource division, monitoring and data analysis method based on label technology. BACKGROUND

[0002] The cloud resource (workload, virtual network, etc.) management and monitoring provided by current various cloud manufacturers is extremely dependent on their own cloud platform architecture; different cloud manufacturers have different monitoring schemes. Taking OpenStack as an example, it depends on the platform architecture such as Ceilometer; and Kubesphere depends on the platform architecture such as Prometheus.

[0003] But their basic way all depends on the agent deployed in the host, workload and other different positions, and uses the platform event monitoring point to carry out the grabbing and obtaining of indicators and events; and forwards the indicators and events to the back-end storage for saving; the operation and maintenance system uses the indicator data in the time series storage for further display and analysis, alarm;

[0004] 1) Due to the fragmentation of various platform technical architectures, a multi-cluster, cross-platform cloud deployment cannot be uniformly monitored, analyzed and data presented under a global view;

[0005] 2) The current technology focuses on the related monitoring of underlying cloud resource objects such as tenant internal workload (such as virtual machine, container group), host, etc.; lacks effective grouping and aggregation means, and cannot perform monitoring analysis and data presentation in high-order dimensions within and between groups.

[0006] The post-analysis and display based on time series data lack cloud real-time data assistance and supplement. The analysis results also lack feedback means and cannot automatically optimize the deployment of related cloud resources. Finally, the use of time series data also lacks effective access control means. SUMMARY

[0007] The technical problem to be solved by the present application is the defects of the background technology. The present application establishes a unified cloud resource label model, simplifies the label process and reduces the use cost of label technology by a cloud resource division, monitoring and data analysis method based on label technology.

[0008] The present application adopts the following technical solutions to solve the above technical problems:

[0009] A cloud resource division, monitoring and data analysis method based on label technology, comprising a cloud platform, a processing layer, an abstraction layer and a display layer; the cloud platform is used for index collection, event monitoring and data labelization of the monitored resource object;

[0010] The processing layer is responsible for complex business operations between various cloud resources of the cloud platform and the twin objects, and includes the following core functions:

[0011] Through the cloud identity center, the object agent is used to bind and authorize the twin objects and associated resources.

[0012] Through the data analysis engine, the analysis results are relabeled on the twin objects in the form of labels.

[0013] Through the label processing engine, the synchronization of different cloud resources with their twin labels and necessary business processing procedures are realized.

[0014] The abstraction layer is used to establish a unified resource twin object model and a label list, and continuously and dynamically label the model structure to reflect the latest state of the monitored cloud resources. Meanwhile, the time sequence storage is used to save the reported events and indicators, and the related data label selection is used to associate with the twin objects for business.

[0015] The display layer manages, groups, and displays the twin objects and indicator data in multiple dimensions in real time and historically according to the label selection algorithm.

[0016] Preferably, the following steps are further included:

[0017] Step S1, labeling cloud resource labels;

[0018] Step S2, reporting indicator events;

[0019] Step S3, label-based monitoring display and monitoring operation.

[0020] Preferably, the step S1 includes the following specific steps:

[0021] Step S11, the cloud resource (such as a workload) accesses securely through the identity authentication center and resource authentication;

[0022] Step S12, the identity authentication center uses the resource ID to initiate a cloud resource association operation to the resource twin management through the object agent, and performs cloud resource and twin association;

[0023] Step S13, due to the triggering of the resource association event, the twin manager initiates a label synchronization operation of the twin object to the cloud resource object to the resource using the related cloud resource resource ID through the label processing engine;

[0024] Step S14, the label processing engine authenticates and searches the cloud resource, confirms the location of the cloud resource, exposes the interface, and confirms the related operation permissions;

[0025] Step S15, according to the business needs, the label processing engine can initiate resource object query operation, baseline check operation, etc. to the cloud platform, so as to obtain the key information for label decision and conversion;

[0026] Step S16, the label processing engine converts the twin label value into policy issuing, scheduling change, resource label marking to the cloud platform resource object, data label marking processing to the related index data, etc. by using the engine rule and the adaptation interface.

[0027] Preferably, the step S2 comprises the following steps:

[0028] Step S21, the cloud platform detects or triggers the cloud resource index or event reporting mechanism through probes, security components, and agent interception, etc.

[0029] Step S22, when reporting, the related index or event must contain the necessary label information of its corresponding cloud resource, and also contains its resource ID;

[0030] Step S23, the data analysis engine performs batch processing analysis on the index or event, and the processing data (including data labels) can be stored in a time series database;

[0031] Step S24, the analysis engine performs real-time processing analysis on the index or event, and feeds back the processing result to the twin manager in the form of twin object label change;

[0032] Step S25, according to the twin object manager, when receiving the label change information of a certain twin object, the label is changed, and at the same time, the label processing engine is initiated for label synchronization;

[0033] Step S26, the label synchronization processing is synchronized with step S1.

[0034] Preferably, the step S3 comprises the following steps:

[0035] Step S31, the display layer selects, screens, and aggregates the time series data and twin data according to the monitoring business needs by using the label selector, and presents the processing result;

[0036] Step S32, the display layer labels the filtered twin objects with unified business labels according to the monitoring business, resource grouping, etc. by using the label selector;

[0037] Step S33, the changed twin object initiates label synchronization to the label processing engine;

[0038] Step S34, the label synchronization processing is synchronized with step S1.

[0039] Compared with the prior art, the application has the following beneficial effects:

[0040] 1. The cloud resource division, monitoring and data analysis method based on the label technology provided by the application establishes a unified cloud resource label model, simplifies the label process and reduces the use cost of the label technology.

[0041] 2. The cloud resource division, monitoring and data analysis method based on the label technology provided by the application can flexibly extend different business monitoring scenarios by using the label technology, and breaks through the technical limitations of current cloud resource monitoring and analysis, such as platform limitations and resource grouping limitations.

[0042] 3. The cloud resource division, monitoring and data analysis method based on the label technology provided by the application simplifies the heavy cloud resource object (and its set) monitoring operation by the abstraction of the twin object, shields the complex characteristics (dynamicity, migration and scalability) of the cloud resource, converts the related resource monitoring into the twin object label, and thus improves the monitoring efficiency of the cloud resource object.

[0043] 4. The cloud resource division, monitoring and data analysis method based on the label technology provided by the application simultaneously performs related cloud resource label synchronization and policy management based on the twin object label, can focus on the business, and realizes the unified management of the cloud resource scheduling and the monitoring policy.

[0044] 5. The cloud resource division, monitoring and data analysis method based on the label technology provided by the application combines the twin object label and the time sequence index data label, uses the related label selection algorithm, can multi-dimensionally and richly display and analyze the real-time and historical records of the cloud resource. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the specific embodiments or the prior art, the drawings needed to be used in the specific embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0046] Figure 1 The system diagram of the cloud resource division, monitoring and data analysis method based on the label technology;

[0047] Figure 2 The initial label flowchart;

[0048] Figure 3 The label flowchart processing diagram of the reported index and event;

[0049] Figure 4 Label-based monitoring display and monitoring operation processing flow. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0051] A cloud resource division, monitoring and data analysis method based on a label technology, comprising a cloud platform, a processing layer, an abstraction layer and a display layer; the cloud platform is used for index collection, event monitoring and reporting data labeling of a monitored resource object;

[0052] The processing layer is responsible for complex business operations between each cloud resource of the cloud platform and a twin object, and comprises the following core functions:

[0053] Through a cloud identity center, an object agent is used to bind and authorize the twin object and its associated resources;

[0054] Through a data analysis engine, an analysis result is relabeled on the twin object in the form of a label;

[0055] Through a label processing engine, different cloud resources are synchronized with their twin labels and necessary business processing flows are realized;

[0056] The abstraction layer is used to establish a unified resource twin object model and a label list, and according to the model structure, the abstraction layer is used to continuously and dynamically label the labels, to reflect the latest state of the monitored cloud resources; meanwhile, a time sequence storage is used to save reporting events and indexes, and a related data label selection is used to associate the business with the twin object;

[0057] The display layer is used to manage, group and display the twin object and index data in multiple dimensions in real time and in history records according to a label selection algorithm.

[0058] 1) In a cloud system, there is a relationship of allocation, use and monitoring between a user (subject) and various resources (object, including host, data, work load, resource combination, etc.).

[0059] 2) A label is a brief description of a certain feature or state of an object, generally in the form of key-value pair, in the form of object metadata, and acts on the entire life cycle of the labeled object.

[0060] 3) Define the twin model and label list of resource objects or collections, and establish the link between the twin and the resource, realize the synchronization of the label of the twin object and the resource.

[0061] 4) The authorized subject uses the twin object and the label technology to dynamically label the resource continuously.

[0062] 5) The label has transitivity, that is, the sub-resource derived from a resource automatically has the data label. For example, the index data of a host automatically contains the host label.

[0063] 6) The label can be used for:

[0064] a) Resource allocation. Mark the purpose of using the resource.

[0065] b) Resource authorization. Mark who can use the resource.

[0066] c) Resource selection and use. Mark the service that the resource can be applied to or the ability that the resource has. And select the resource for use.

[0067] d) Resource statistics. Aggregate statistics on the same type or different type of resources by label.

[0068] e) Resource isolation. Use label technology to isolate resources.

[0069] Security monitoring. Through the judgment of the resource label, the risk and violation in the use of the resource can be quickly located, alarmed and investigated.

[0070] As a specific implementation, the following steps are further included:

[0071] Step S1, mark the cloud resource label;

[0072] Step S2, report the index event;

[0073] Step S3, label-based monitoring display and monitoring operation.

[0074] As a specific implementation, the step S1 has the following specific steps:

[0075] Step S11, the cloud resource (such as workload) accesses the system through identity authentication center and performs resource authentication for secure access;

[0076] Step S12, the identity authentication center uses the resource ID to initiate a cloud resource association operation to the resource twin management through the object agent, and associates the cloud resource and the twin;

[0077] Step S13, due to the triggering of the resource association event, the twin manager initiates a label synchronization operation of the twin object and the cloud resource object to the resource by the label processing engine using the related cloud resource resource ID;

[0078] Step S14, the label processing engine authenticates and searches the cloud resource, confirms the location of the cloud resource, exposes the interface, and has related operation permissions;

[0079] Step S15, according to the business needs, the label processing engine may initiate resource object query operation, baseline check operation, etc. to the cloud platform, so as to obtain the key information for label decision and conversion;

[0080] Step S16, the label processing engine converts the twin label value into policy issuance, scheduling change, resource label marking to the cloud platform resource object, data label marking processing to the related index data, and other operations by using the engine rule and the adaptive interface.

[0081] As a specific implementation, the step S2 has the following specific steps:

[0082] Step S21, the cloud platform detects or triggers the cloud resource index or event reporting mechanism by means of probes, security components, and agent interception;

[0083] Step S22, when reporting, the related index or event must contain the necessary label information of the corresponding cloud resource, and also contains the resource ID;

[0084] Step S23, the data analysis engine performs batch processing analysis on the index or event, and the processing data (including data labels) can be stored in a time series database;

[0085] Step S24, the analysis engine performs real-time processing analysis on the index or event, and feeds back the processing result to the twin manager in the form of twin object label change;

[0086] Step S25, according to the twin object manager, the label change information of a certain twin object is received, the label is changed, and at the same time, the label synchronization is initiated to the label processing engine;

[0087] Step S26, the label synchronization processing is synchronized with step S1.

[0088] As a specific implementation, the step S3 has the following specific steps:

[0089] Step S31, the display layer uses the label selector to perform time series data and twin data selection, screening, and aggregation according to the monitoring business needs, and presents the processing result;

[0090] Step S32, the display layer uses the label selector to mark the filtered twin object with a unified business label according to the monitoring business, resource grouping and other needs;

[0091] Step S33, the changed twin object initiates label synchronization to the label processing engine at the same time;

[0092] Step S34, the label synchronization processing is synchronized with step S1.

[0093] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A cloud resource partitioning, monitoring and data analysis method based on tag technology, characterized in that, It comprises a cloud platform, a processing layer, an abstraction layer and a display layer; the cloud platform is used for index collection, event monitoring and reporting data tagging of monitored resource objects; and the following steps are further included: Step S1, marking cloud resource tags; Step S2, reporting index events; Step S3, tag-based monitoring display and monitoring operation; The processing layer is responsible for complex business operations between the cloud platform and the twin objects of each cloud resource, including the following core functions: Through the cloud identity center, the object agent is used to bind and authorize the twin objects and their associated resources; Through the data analysis engine, the analysis results are re-tagged on the twin objects in the form of tags; Through the tag processing engine, different cloud resources are synchronized with their twin tags and necessary business processing flows are realized; The abstraction layer is used to establish a unified resource twin object model and a tag list, and according to the model structure, it is continuously and dynamically tagged to reflect the latest state of the monitored cloud resources; at the same time, the reporting events and indexes are saved by using time sequence storage, and the business correlation with the twin objects is realized by using related data tag selection; The display layer manages, groups and displays the real-time and historical records of the twin objects and index data in multiple dimensions according to the tag selection algorithm. 2.The cloud resource partitioning, monitoring and data analysis method based on tag technology of claim 1, wherein, The step S1 comprises the following specific steps: Step S11, the cloud resource accesses securely through the identity authentication center and resource authentication; Step S12, the identity authentication center uses the resource ID to initiate a cloud resource association operation to the resource twin management through the object agent, and performs cloud resource and twin association; Step S13, due to the triggering of the resource association event, the twin manager initiates a tag synchronization operation of the twin object to the cloud resource object to the resource by using the related cloud resource resource ID through the tag processing engine; Step S14, the tag processing engine authenticates and searches the cloud resource, confirms the location of the cloud resource, exposes the interface and related operation permissions; Step S15, according to business requirements, the tag processing engine may initiate a resource object query operation to the cloud platform, baseline check operation, so as to obtain key information for tag decision and conversion; Step S16, the tag processing engine uses engine rules and adaptive interfaces to convert the twin tag value into policy issuance, scheduling change, resource tag marking to the cloud platform resource object, and data tag marking processing to related index data. 3.The cloud resource partitioning, monitoring and data analyzing method based on tag technology of claim 1, wherein, The step S2 comprises the following specific steps: Step S21, the cloud platform uses probes, security components and agent interception methods to detect or trigger cloud resource index or event reporting mechanisms; Step S22, when reporting, the related index or event must include the necessary tag information of the corresponding cloud resource, as well as the resource ID; Step S23, the data analysis engine performs batch processing analysis on the index or event, and stores the processing data in the time sequence database; Step S24, the analysis engine performs real-time processing analysis on the index or event, and feeds back the processing result to the twin manager in the form of twin object tag change; Step S25, according to the twin object manager, receiving the label change information of a certain twin object, changing its label, and at the same time, initiating label synchronization to the label processing engine; Step S26, the label synchronization processing is synchronized with step S1. 4.The cloud resource partitioning, monitoring and data analyzing method based on tag technology of claim 1, wherein, The specific steps of the step S3 are as follows: Step S31, the display layer uses the label selector to perform time series data and twin data selection, screening and aggregation operation according to the monitoring business needs, and presents the processing results; Step S32, the display layer uses the label selector to mark the filtered twin object with a unified business label according to the monitoring business and resource grouping needs; Step S33, the changed twin object initiates label synchronization to the label processing engine at the same time; Step S34, the label synchronization processing is synchronized with step S1.

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