Data acquisition method and device, electronic equipment and storage medium

Abstract

The present disclosure relates to a data collection method and device, electronic equipment and computer readable storage medium, and relates to the technical field of databases, and can be applied to a scenario of data collection operation through a configured data model. The method comprises: obtaining a data collection task; obtaining a pre-configured data collection model, the data collection model comprising any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model and a rack device model; performing a data collection operation based on the data collection model and the data collection task to obtain target collection data, the target collection data being stored in a topological structure. The present disclosure uses a pre-configured data collection model to quickly and accurately perform a data collection operation, which can effectively improve data collection efficiency and ensure data quality.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of database, and in particular, to a data collection method, a data collection device, an electronic device and a computer readable storage medium. BACKGROUND

[0002] With the rapid development of enterprise business, the enterprise Internet technology (IT) architecture is increasingly large. The enterprise introduces a configuration management database (CMDB) to uniformly manage a large number of configuration entity elements, which are referred to as configuration items. The CMDB is a logical database that contains information of the whole life cycle of the configuration items and the relationships between the configuration items, such as physical relationships, real-time communication relationships, non-real-time communication relationships, and dependency relationships.

[0003] The CMDB stores and manages various configuration information of devices in the enterprise IT architecture, and is closely related to all service support and service delivery processes, supports the operation of these processes, plays the value of the configuration information, and at the same time relies on related processes to ensure the accuracy of the data. However, the current CMDB data is usually analyzed and updated manually.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present disclosure is to provide a data collection method, a data collection device, an electronic device and a computer readable storage medium, thereby at least partially overcoming the problem that the current CMDB data is manually analyzed and updated, which is time-consuming and laborious, and the accuracy is difficult to guarantee, resulting in low data quality.

[0006] Other characteristics and advantages of the present disclosure will become apparent from the following detailed description, or will be learned by practice of the present disclosure.

[0007] According to a first aspect of the present disclosure, a data collection method is provided, comprising: obtaining a data collection task; obtaining a pre-configured data collection model, the data collection model comprising any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model; performing a data collection operation based on the data collection model and the data collection task to obtain target collection data, the target collection data being stored in a topology structure.

[0008] In an example embodiment of the present disclosure, the method further comprises: determining a data collection interface corresponding to the data collection task; configuring a data collection program matching the data collection interface according to the data collection task; and performing a data collection operation by the data collection program through the matching data collection interface.

[0009] In an example embodiment of the present disclosure, the data collection operation based on the data collection model and the data collection task to obtain target collection data comprises: determining a data collection tool matching the data collection task; the data collection tool comprises a combination of any one or more of a data collection protocol, a data collection interface, and a data collection service; and performing the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data.

[0010] In an example embodiment of the present disclosure, the data collection task comprises a domain name network address data collection task, and the target collection data comprises domain name network address model data; and the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data comprises: obtaining a domain name calling interface, and obtaining Internet domain name data and intranet domain name data through the domain name calling interface and an application layer protocol; and creating the domain name network address model data based on the Internet domain name data and the intranet domain name data by the data collection model.

[0011] In an example embodiment of the present disclosure, the domain name network address model data comprises network mapping relationship data; and the creation of the domain name network address model data based on the Internet domain name data and the intranet domain name data by the data collection model comprises: performing domain name resolution processing on the Internet domain name data to obtain a buffer network address; performing first resolution processing and second resolution processing on the intranet domain name data respectively to obtain a virtual network address and an intranet network address respectively; creating first network mapping relationship data between the buffer network address and the virtual network address by the data collection model; and creating second network mapping relationship data between the buffer network address and the intranet network address by the data collection model.

[0012] In an example embodiment of the present disclosure, the data collection task includes a network layer data collection task; and the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data includes: determining a network device connected to a switch port, the network device including any one or a combination of a storage device, a security device, a load balancing device, a physical server, and a fiber switch; determining a network device to be collected based on the network layer data collection task, obtaining device data of the network device to be collected, and generating initial network model data based on the device data; creating a device connection relationship between each of the network devices to be collected based on a device physical address; and generating network model data based on the initial network model data and the device connection relationship.

[0013] In an example embodiment of the present disclosure, the obtaining of the device data of the network device to be collected and the generating of the initial network model data based on the device data includes: collecting network switch data through an application layer protocol of a development system model, processing the network switch data into switch-switch port model data by the data collection model; collecting security device data through the application layer protocol, processing the security device data into security device model data by the data collection model; collecting storage device data through the application layer protocol, processing the storage device data into storage device-fiber switch model data by the data collection model; collecting operating system data through the application layer protocol and a network layer protocol, processing the operating system data into physical server model data by the data collection model; and collecting load balancing device data through the application layer protocol and the network layer protocol, processing the load balancing device data into load balancing device model data by the data collection model.

[0014] In an example embodiment of the present disclosure, the data collection task includes a software model data collection task; and the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data includes: collecting operating system data through an application layer protocol, processing process data in the operating system data into application program-service middleware-database model data by the data collection model; processing network configuration data in the operating system data into intranet network address data by the data collection model; and processing system kernel data in the operating system data into operating system model data by the data collection model.

[0015] In an example embodiment of the present disclosure, the data collection task includes a storage model data collection task; and the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data includes: collecting storage device data through a network layer protocol, processing the storage device data into storage device model data by the data collection model; collecting equipment with library data through the network layer protocol, processing the equipment with library data into equipment with library model data by the data collection model; collecting fiber switch data through the network layer protocol, and processing the data into fiber switch model data by the data collection model; determining storage model related equipment, and establishing a storage device connection relationship between the storage model related equipment.

[0016] In an example embodiment of the present disclosure, the establishment of the storage device connection relationship between the storage model related equipment includes: obtaining a server identification number matched with the storage model related equipment; based on the server identification number, establishing a first equipment connection relationship between the fiber switch, the storage device and the equipment with library; based on the server identification number, establishing a second equipment connection relationship between the physical server, the storage device and the fiber switch.

[0017] In an example embodiment of the present disclosure, the data collection task includes a rack equipment model data collection task; and the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data includes: determining rack external equipment connected with the rack equipment; respectively obtaining rack equipment data and external equipment data from the rack equipment and the rack external equipment; and creating rack model data based on the rack equipment data and the external equipment data by the data collection model.

[0018] In an example embodiment of the present disclosure, the above method further includes: determining a topology relationship corresponding to the target collection data; and based on the topology relationship, storing the target collection data in a topology structure to a graph database.

[0019] According to a second aspect of the present disclosure, a data collection device is provided, including: a task acquisition module configured to acquire a data collection task; a model acquisition module configured to acquire a pre-configured data collection model, the data collection model including any one or a combination of multiple of domain name network address model, network layer data model, software model, storage model, and rack equipment model; and a data collection module configured to perform a data collection operation based on the data collection model and the data collection task to obtain target collection data, the target collection data being stored in a topology structure.

[0020] In an example embodiment of the present disclosure, the data collection device further comprises an interface configuration module configured to: determine a data collection interface corresponding to the data collection task; configure a data collection program matching the data collection interface according to the data collection task; and perform a data collection operation by the data collection program through the matched data collection interface.

[0021] In an example embodiment of the present disclosure, the data collection module comprises a data collection unit configured to: determine a data collection tool matching the data collection task; the data collection tool comprises a combination of any one or more of a data collection protocol, a data collection interface, and a data collection service; and perform the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data.

[0022] In an example embodiment of the present disclosure, the data collection task comprises a domain name network address data collection task, and the target collection data comprises domain name network address model data; the data collection unit comprises a first data collection subunit configured to: obtain a domain name calling interface, and obtain Internet domain name data and intranet domain name data through the domain name calling interface and an application layer protocol; and create the domain name network address model data based on the Internet domain name data and the intranet domain name data by the data collection model.

[0023] In an example embodiment of the present disclosure, the domain name network address model data comprises network mapping relationship data; and the first data collection subunit is configured to perform: domain name resolution processing on the Internet domain name data to obtain a buffer network address; first resolution processing and second resolution processing on the intranet domain name data to obtain a virtual network address and an intranet network address, respectively; creation of first network mapping relationship data between the buffer network address and the virtual network address by the data collection model; and creation of second network mapping relationship data between the buffer network address and the intranet network address by the data collection model.

[0024] In one exemplary embodiment of this disclosure, the data acquisition task includes a network layer data acquisition task; the data acquisition unit includes a second data acquisition subunit, configured to: determine network devices connected to switch ports, wherein the network devices include any one or more combinations of storage devices, security devices, load balancing devices, physical servers, and fiber optic switches; determine network devices to be acquired based on the network layer data acquisition task; acquire device data of the network devices to be acquired; generate initial network model data based on the device data; create device connection relationships between the network devices to be acquired based on their physical addresses; and generate network model data based on the initial network model data and the device connection relationships.

[0025] In one exemplary embodiment of this disclosure, the second data acquisition subunit is configured to perform the following: acquiring network switch data through the application layer protocol of the development system model, and processing the network switch data into switch-switch port model data by the data acquisition model; acquiring security device data through the application layer protocol, and processing the security device data into security device model data by the data acquisition model; acquiring storage device data through the application layer protocol, and processing the storage device data into storage device-fiber optic switch model data by the data acquisition model; acquiring operating system data through the application layer protocol and network layer protocol, and processing the operating system data into physical server model data by the data acquisition model; and acquiring load balancing device data through the application layer protocol and network layer protocol, and processing the load balancing device data into load balancing device model data by the data acquisition model.

[0026] In one exemplary embodiment of this disclosure, the data acquisition task includes a software model data acquisition task; the data acquisition unit includes a third data acquisition subunit, configured to: acquire operating system data through an application layer protocol; process process data in the operating system data into application-service middleware-database model data by the data acquisition model; process network configuration data in the operating system data into intranet network address data by the data acquisition model; and process system kernel data in the operating system data into operating system model data by the data acquisition model.

[0027] In an example embodiment of the present disclosure, the data collection task includes a storage model data collection task; the data collection unit includes a fourth data collection subunit configured to: collect storage device data via a network layer protocol, process the storage device data into storage device model data by the data collection model; collect library equipment data via the network layer protocol, process the library equipment data into library equipment model data by the data collection model; collect fiber switch data via the network layer protocol, and process the fiber switch data into fiber switch model data by the data collection model; determine storage model related equipment, and establish a storage device connection relationship between the storage model related equipment.

[0028] In an example embodiment of the present disclosure, the fourth data collection subunit is configured to perform: obtaining a server identification number matched with the storage model related equipment; establishing a first equipment connection relationship between the fiber switch, the storage device and the library equipment based on the server identification number; establishing a second equipment connection relationship between the physical server, the storage device and the fiber switch based on the server identification number.

[0029] In an example embodiment of the present disclosure, the data collection task includes a rack equipment model data collection task; the data collection unit includes a fifth data collection subunit configured to: determine a rack external equipment connected with a rack equipment; respectively obtain rack equipment data and external equipment data from the rack equipment and the rack external equipment; and create rack model data based on the rack equipment data and the external equipment data by the data collection model.

[0030] In an example embodiment of the present disclosure, the data collection device further includes a data storage module configured to: determine a topology relationship corresponding to the target collection data; and store the target collection data in a topology structure to a graph database based on the topology relationship.

[0031] According to a third aspect of the present disclosure, an electronic device is provided, including: a processor; and a memory having computer readable instructions stored thereon, the computer readable instructions being executed by the processor to implement the data collection method according to any one of the above.

[0032] According to a fourth aspect of the present disclosure, a computer readable storage medium is provided, having a computer program stored thereon, the computer program being executed by a processor to implement the data collection method according to any one of the above.

[0033] The technical solutions provided by the present disclosure can include the following beneficial effects:

[0034] The data collection method in the exemplary embodiments of the present disclosure can realize automatic collection and updating of CMDB data through the pre-configured data collection model, without the need for manual intervention. The data collection model can further improve the data quality of the target collection data. The topology structure can be used to store the target collection data, which can effectively improve the expansibility of the target collection data.

[0035] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0036] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure. It is apparent that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor. In the drawings:

[0037] Figure 1 A flowchart of a data collection method according to an exemplary embodiment of the present disclosure is schematically shown;

[0038] Figure 2 A flowchart of a domain name network address model data collection method according to an exemplary embodiment of the present disclosure is schematically shown;

[0039] Figure 3 A flowchart of a network model data collection method according to an exemplary embodiment of the present disclosure is schematically shown;

[0040] Figure 4 A flowchart of a software model data collection method according to an exemplary embodiment of the present disclosure is schematically shown;

[0041] Figure 5 A flowchart of a storage model data collection method according to an exemplary embodiment of the present disclosure is schematically shown;

[0042] Figure 6 A connection relationship diagram of a rack external device connected to a rack according to an exemplary embodiment of the present disclosure is schematically shown;

[0043] Figure 7 A topology structure diagram of target collection data obtained according to an exemplary embodiment of the present disclosure is schematically shown;

[0044] Figure 8 A block diagram of a data collection device according to an exemplary embodiment of the present disclosure is schematically shown;

[0045] Figure 9 a block diagram of an electronic device according to an example embodiment of the present disclosure is schematically illustrated;

[0046] Figure 10 a schematic diagram of a computer readable storage medium according to an example embodiment of the present disclosure is schematically illustrated. DETAILED DESCRIPTION

[0047] Example embodiments now will be described more fully hereinafter with reference to the accompanying drawings. Example embodiments, however, can be implemented in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example embodiments to those skilled in the art. Like reference numerals refer to like elements throughout the several views.

[0048] Moreover, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the techniques described herein can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail in order to avoid obscuring aspects of the disclosure.

[0049] The block diagrams in the drawings show functions and functionality as they can be implemented in software and / or firmware. In other words, the block diagrams do not depict the underlying circuitry or machine code of the implementations. Some of the functions / things can be implemented directly in hardware, such as in an application specific integrated circuit. Thus, functions / things in the diagrams can be carried out in a variety of ways.

[0050] At present, the configuration management database data is usually analyzed and updated manually, however, the above processing mode has the following problems: (1) the CMDB data is analyzed and updated manually, which is time-consuming and laborious, and the accuracy is difficult to guarantee, resulting in low data quality. (2) The traditional data model is in two-dimensional form, and it is difficult to obtain the possible mutual influence relationship in the complex IT infrastructure through simple query technical means. (3) The relational database is used to save the configuration item data and the configuration relationship data, which has poor expansibility, and the new model and the model relationship must be added to modify the table.

[0051] Based on this, in the present example embodiment, a data collection method is first provided, which can be implemented by a server or a terminal device. The terminal described in the present disclosure can include mobile terminals such as mobile phones, tablets, laptops, palmtop computers, personal digital assistants (PDA), portable media players (PMP), navigation devices, wearable devices, smart bands, pedometers, and the like, as well as fixed terminals such as desktop computers. Figure 1 A schematic diagram of a data collection method flow according to some embodiments of the present disclosure is shown schematically. Referring to Figure 1 The data collection method can include the following steps:

[0052] Step S110, obtaining a data collection task.

[0053] According to some example embodiments of the present disclosure, the data collection task can be an execution task configured according to business requirements to obtain specific type data.

[0054] For the massive business data generated in the business processing process, the relevant technical personnel can formulate the corresponding data collection task according to the business requirements, and determine the specific business data to be collected.

[0055] Step S120, obtaining a pre-configured data collection model, the data collection model including any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model.

[0056] According to some example embodiments of the present disclosure, the data collection model can be a data model for executing the data collection task, and the data collection model can be an abstraction of the data task matched by the data collection task. The domain name network address model can be a data model for executing the domain name network address model data collection task. The network layer data model can be a data model for executing the network layer model data collection task. The software model can be a data model for executing the software model data collection task. The storage model can be a data model for executing the storage model data collection task. The rack device model can be a data model for executing the rack device model data collection task.

[0057] After obtaining the data collection task, a pre-configured data collection model can be obtained. Since the data collection task can involve domain name network address data, network layer data, software data, storage data, and rack device data, a business personnel can pre-configure a data collection model for collecting the above business data. The data collection model defines abstract data features of different types of data, for example, the data collection model can define static features, dynamic behaviors, and constraint conditions of data, mainly including data structure, data operation, and data constraint, etc. The data structure can include data basic items, data format, etc.

[0058] For example, the data collection model can include a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model. From the pre-configured data collection model, a data collection model matching the data collection task is matched.

[0059] In step S130, data collection operation is performed based on the data collection model and the data collection task to obtain target collection data, and the target collection data is stored in a topology structure.

[0060] According to some example embodiments of the present disclosure, the data collection operation can be an execution operation of obtaining specific data by using the data collection model matching the data collection task. The target collection data can be data obtained by the data collection model based on the data collection task.

[0061] After obtaining the data collection model matching the data collection task, the data collection operation can be performed based on the data collection model according to the data collection task to obtain target collection data corresponding to the data collection task. After obtaining the target collection data, the target collection data can be stored in a topology structure, for example, the target collection data can store related device data of each physical device by using a point-based storage unit, and can also store related data of the connection relationship between two physical devices by using an edge-based storage unit. Storing the target collection data in a topology structure can effectively improve the scalability of the target collection data.

[0062] According to the data collection method in the example embodiment, on the one hand, the pre-configured data collection model can realize automatic collection and update of CMDB data without manual intervention. On the other hand, the data collection by using a more comprehensive data collection model can further improve the data quality of the target collection data. On the other hand, storing the target collection data in a topology structure can effectively improve the scalability of the target collection data.

[0063] In the following, the data collection method in the example embodiment will be further described.

[0064] In an example embodiment of the present disclosure, a data collection interface corresponding to a data collection task is determined; a data collection program matching the data collection interface is configured according to the data collection task; and a data collection operation is performed by the data collection program through the matched data collection interface.

[0065] The data collection interface can be an application programming interface (API) for performing the data collection task. The data collection program can be a specific program for performing the data collection task.

[0066] After obtaining the data collection task, each data collection interface corresponding to the data collection task can be determined, and for each obtained data collection interface, a data collection program matching the data collection interface can be configured according to the data collection task. For example, referring to Figure 2 Figure 2 A flowchart for collecting domain name network address model data according to an example embodiment of the present disclosure is schematically shown. As can be seen from Figure 2 To collect the domain name network address model data, data collection can be performed through an Internet domain name service interface 210, an intranet domain name service interface 220, a security device management interface 230, a network device management interface 240, a load balancing device management interface 250, and the like.

[0067] For different data collection interfaces, matching data collection programs can be configured. For example, for the Internet domain name service interface 210 and the intranet domain name service interface 220, a corresponding domain name data collection program 260 can be configured; for the security device management interface 230 and the network device management interface 240, a network address translation (NAT) mapping data collection program 270 can be configured; for the load balancing device management interface 250, a load balancing data collection program 280 can be configured; in addition, for the collection of domain name and network address model data, an IP alive probe program 290 can also be configured, and the like, to ensure the smooth progress of the data collection task.

[0068] Referring to Figure 3 Figure 3 ​​A flowchart of collecting network model data according to an example embodiment of the present disclosure is schematically shown. For the collection task of network layer data, a security device management interface 301, a switch device management interface 302, a load balancing device management interface 303, an operating system management interface 304, a storage device management interface 305, a hardware device management interface 306, etc. can be configured. For different data collection interfaces, corresponding data collection programs can be configured, for example, a network device data collection program 307 is configured for the security device management interface 301 and the switch device management interface 302; a load balancing data collection program 308 is configured for the load balancing device management interface 303; an operating system data collection program 309 is configured for the operating system management interface 304; a storage device data collection program 310 is configured for the storage device management interface 305; and a hardware device data collection program 311 is configured for the hardware device management interface 306.

[0069] Referring to Figure 4 , Figure 4 A flowchart of collecting software model data according to an example embodiment of the present disclosure is schematically shown. For the collection task of software model, an operating system management interface 410, a virtualization software management interface 420, and a public cloud management interface 430 can be configured. For the above data collection interfaces, data collection programs can be respectively configured, for example, an operating system data collection program 440 is configured for the operating system management interface 410; a virtualization data collection program 450 is configured for the virtualization software management interface 420; and a public cloud data collection program 460 is configured for the public cloud management interface 430.

[0070] Referring to Figure 5 , Figure 5 A flowchart of collecting storage model data according to an example embodiment of the present disclosure is schematically shown. For the collection task of storage model, an operating system management interface 510 and a storage device management interface 520 can be configured; and for the above data collection interfaces, data collection programs can be respectively configured. For example, an operating system data collection program 530 is configured for the operating system management interface 510; and a storage device data collection program 540 is configured for the storage device management interface 520.

[0071] After the data collection program is configured for different data collection interfaces, the data collection interfaces can perform data collection operations based on the data collection program to obtain different types of data. For example, different data collection interfaces can use a text parser (Another Tool for Language Recognition, antlr) generator to perform script parsing to execute corresponding data collection programs. By configuring data collection programs for different data collection interfaces to perform data collection operations, the flexibility of data processing can be improved while the means for processing complex formatted and unformatted data are enhanced.

[0072] In an exemplary embodiment of the present disclosure, for step S130, performing data collection operations based on the data collection model and the data collection task to obtain target collection data includes: determining a data collection tool matched with the data collection task; the data collection tool includes any one or a combination of multiple of data collection protocols, data collection interfaces, data collection services; performing data collection operations based on the data collection task and in combination with the data collection model and the data collection tool to obtain target collection data.

[0073] Among them, the data collection tool can be various tools used in the process of executing the data collection task, including data collection protocols, data collection interfaces, data collection services, etc. used in the data collection task. The data collection protocol can be a network protocol used in the process of executing the data collection task. The data collection service can be a related network service used in the process of executing the data collection task.

[0074] When performing data collection operations based on the data collection model, a data collection tool matched with the data collection task can be determined. For example, when performing data collection operations, different network protocols can be used, and the data collection interface is based on the corresponding network protocol and uses the corresponding data collection service to perform data collection operations. Therefore, the data collection tool can include data collection protocols, data collection interfaces, data collection services, etc. After the data collection task is determined, data collection operations can be performed based on the data collection task and in combination with the data collection model and the data collection tool to obtain target collection data matched with the data collection task. Through the above steps, target collection data in a specific format defined by the data collection model can be obtained, and the data quality of the target collection data can be effectively improved.

[0075] In one exemplary embodiment of this disclosure, the data acquisition task includes a domain name network address data acquisition task, and the target acquisition data includes domain name network address model data. Based on the data acquisition task, and in combination with the data acquisition model and data acquisition tools, data acquisition operations are performed to obtain the target acquisition data, including: obtaining a domain name call interface, and obtaining Internet domain name data and intranet domain name data through the domain name call interface and application layer protocol; and creating domain name network address model data based on the Internet domain name data and intranet domain name data by the data acquisition model.

[0076] Specifically, the domain name call interface can be an API interface used to obtain internet domain names and intranet domain names. The application layer protocol can be a network protocol at the application layer in the Open Systems Interconnection Reference Model (OSI). Internet domain name data can be domain name data that uniquely identifies a computer on the internet using character-type addresses. Intranet domain name data can be domain name data that uniquely identifies a computer on an internal network (i.e., a local area network). Domain name network address model data can be data that can express the abstract characteristics between domain names and network addresses.

[0077] Continue to refer to Figure 2 When collecting domain name network address model data, one can first obtain the domain name call interface. For example, different domain name call interfaces can be used for different types of domain name data, including calling the domain name service provider's service interface using a Software Development Kit (SDK) and calling the internal domain name service interface using an SDK. After obtaining the domain name call interface, domain name data acquisition operations can be performed based on the application layer protocols in the OSI model. Specifically, internet domain name data can be collected by calling the domain name service provider's service interface using the Hypertext Transfer Protocol (HTTP) protocol at the application layer; alternatively, intranet domain name data can also be collected by calling the internal domain name service interface using the internal HTTP protocol at the application layer.

[0078] After obtaining Internet domain name data and intranet domain name data respectively, the data collection model can abstract and process the above data to create domain name network address model data that conforms to the model format, so as to form the target collection data in the future.

[0079] In one exemplary embodiment of this disclosure, the domain name network address model data includes network mapping relationship data. The creation of the domain name network address model data by a data acquisition model, based on internet domain name data and intranet domain name data, includes: performing domain name resolution processing on the internet domain name data to obtain a buffer network address; performing first resolution processing and second resolution processing on the intranet domain name data respectively to obtain a virtual network address and an intranet network address; creating a first network mapping relationship data between the buffer network address and the virtual network address by the data acquisition model; and creating a second network mapping relationship data between the buffer network address and the intranet network address by the data acquisition model.

[0080] Domain name resolution processing can be the process of resolving a domain name address into an Internet Protocol (IP) address. A buffer network address can be an IP address located in a demilitarized zone (DMZ) between insecure and secure systems.

[0081] The first resolution process can be the process of converting internal network domain name data into virtual network addresses.

[0082] The second resolution process can be the conversion of internal network domain name data into internal network addresses. A virtual network address is a virtual network address. An internal network address can be an IP address within a local area network (LAN). The first network mapping relationship data can be data containing the mapping relationship between buffered network addresses and virtual network addresses. The second network mapping relationship data can be data containing the mapping relationship between buffered network addresses and internal network addresses.

[0083] Continue to refer to Figure 2 After obtaining the Internet domain name data 2010 and the intranet domain name data 2020, address resolution processing can be performed on these two types of domain name data respectively. For example, performing domain name resolution processing on the Internet domain name data 2010 yields the buffer network address (DMZ zone IP address) 2030; and performing the first resolution processing and the second resolution processing on the intranet domain name data 2020 respectively yields the load balancing virtual network address (IP address) 2040 and the intranet network address (IP address) 2050.

[0084] After obtaining the address data, the data collection model creates the first network mapping relationship data between the buffer network address 2030 and the virtual network address 2040, that is, processes the domain name data and the load balancing virtual IP address into Internet domain name model data and Internet domain name resolution DMZ zone IP address relationship data; at the same time, the data collection model creates the second network mapping relationship data between the buffer network address 2030 and the intranet network address 2050, that is, processes the buffer network address 2030 and the intranet network address 2050 into intranet domain name model data and intranet domain name resolution intranet IP, intranet domain name resolution load balancing virtual IP relationship data. Through the above processing steps, in the data collection operation process, it can support batch detection of live IP addresses based on network segments, match and collect domain names and DMZ zone IP addresses within the live IP address range, reduce the data volume, and improve the matching efficiency.

[0085] In an exemplary embodiment of the present disclosure, the data collection task includes a network layer data collection task; based on the data collection task, and in combination with the data collection model and the data collection tool, the data collection operation is performed to obtain target collection data, including: determining a network device connected to a switch port, the network device including any one or a combination of multiple of a storage device, a security device, a load balancing device, a physical server, and a fiber switch; determining a to-be-collected network device based on the network layer data collection task, obtaining device data of the to-be-collected network device, and generating initial network model data based on the device data; creating a device connection relationship between each to-be-collected network device based on the device physical address; and generating network model data based on the initial network model data and the device connection relationship.

[0086] The network layer data collection task can be a data acquisition task for collecting network layer model data. The to-be-collected network device can be a network device to be collected according to the data collection task. The device data can be data obtained from the to-be-collected network device. The initial network model data can be initial model data obtained according to the abstract features of the collected device data. The device physical address can be the physical address of each device in the network layer. The device connection relationship can be the connection relationship between different network layer devices. The network model data can be data that can express the abstract features between various types of data in the network layer.

[0087] With reference to the foregoing Figure 3 , Figure 3A flowchart of collecting network model data according to an example embodiment of the present disclosure is shown schematically. In performing a network layer data collection task, a plurality of network devices connected to the switch port 3010 can be determined first, including a network switch 3020, a physical server 3030, a fiber switch 3040, a storage device 3050, a load balancing device 3060, a tape library device 3070, a security device 3080, and additionally, an operating system 3090 can be installed in the physical server 3030. For the network devices connected to the switch port described above, the network devices to be collected can be determined according to the data collection task, and the network devices to be collected can be any one or a combination of the above network devices.

[0088] After determining the network devices to be collected, device data can be obtained from the network devices to be collected. For the obtained device data, initial network model data corresponding to the device data can be generated according to a pre-constructed network layer data model. And for different network devices, device connection relationships between the network devices to be collected can be created based on device physical addresses, for example, connection relationships between switch ports and network switches, security devices, storage devices, fiber switches, physical servers, and load balancing devices can be established by matching Media Access Control Addresses (MAC addresses).

[0089] After obtaining the device connection relationships between the network devices, network model data can be generated based on the initial network model data and the device connection relationships, as target collection data corresponding to the data collection task.

[0090] In an example embodiment of the present disclosure, device data of the network devices to be collected is obtained, and initial network model data is generated based on the device data, including: collecting network switch data through an application layer protocol of a development system model, processing the network switch data into switch-switch port model data by a data collection model; collecting security device data through the application layer protocol, processing the security device data into security device model data by the data collection model; collecting storage device data through the application layer protocol, processing the storage device data into storage device-fiber switch model data by the data collection model; collecting operating system data through the application layer protocol and a network layer protocol, processing the operating system data into physical server model data by the data collection model; collecting load balancing device data through the application layer protocol and the network layer protocol, processing the load balancing device data into load balancing device model data by the data collection model.

[0091] The switch-switch port model data can be model data expressing a mapping relationship between a network switch and a switch port. The security device model data can be data containing abstract features of security device data. The storage device-fiber switch model data can be model data expressing a mapping relationship between a storage device and a fiber switch. The physical server model data can be data containing abstract features of physical server data. The load balancing device model data can be data containing abstract features of load balancing device data.

[0092] With reference to the foregoing Figure 3 In determining the initial network model data, the following steps can be included: (1) collecting network switch data through application layer protocols of the development system model, and processing the network switch data into switch-switch port model data by a data collection model. The network switch data is collected through Simple Network Management Protocol (SNMP) and Secure Shell File Transfer Protocol (SSH) of the application layer, and is processed into network switch-switch port model data by the data collection model.

[0093] (2) collecting security device data through application layer protocols, and processing the security device data into security device model data by a data collection model. The security device data is collected through the SNMP and ssh protocols and is processed into security device model and relationship data.

[0094] (3) collecting storage device data through application layer protocols, and processing the storage device data into storage device-fiber switch model data by a data collection model. The storage device data is collected through the SNMP, SSH, and Storage Management Interface Specification (SMI-S) protocols and is processed into storage device-fiber switch model and relationship data.

[0095] (4) collecting operating system data through application layer protocols and network layer protocols, and processing the operating system data into physical server model data by a data collection model. The operating system data is collected through the SNMP, SSH, and Internet Protocol Multimedia Private Identity (IPMI) protocols, and is processed into physical server model and relationship data by an agent service.

[0096] (5) Collecting load balancing equipment data through application layer protocol and network layer protocol, and processing the load balancing equipment data into load balancing equipment model data by the data collection model. The load balancing equipment data is collected through SNMP protocol, SSH protocol and HTTP protocol and processed into load balancing equipment model and relational data. In the process of data acquisition and data construction of the initial network model data, the corresponding parsing program of the text parser can be used to adapt to various network equipment models, facilitating network equipment expansion.

[0097] In an exemplary embodiment of the present disclosure, the data collection task includes a software model data collection task; based on the data collection task, and in combination with the data collection model and the data collection tool, a data collection operation is performed to obtain target collection data, including: collecting operating system data through an application layer protocol, and processing process data in the operating system data into application program-service middleware-database model data by the data collection model; processing network configuration data in the operating system data into intranet network address data by the data collection model; and processing system kernel data in the operating system data into operating system model data by the data collection model.

[0098] The process data can be related data of a process running in the operating system. The application program-service middleware-database model data can be data expressing the mapping relationship between the application program, the service middleware and the database. The network configuration data can be related data contained in the service end network configuration. The intranet network address data can be related data of an IP address inside the local area network. The system kernel data can be related data of a functional module set in the operating system running in the kernel state and responsible for managing the system. The operating system model data can be data expressing the abstract features between the kernel and the process in the operating system.

[0099] With reference to Figure 4 When constructing the software model data, operating system data can be collected through an application layer protocol. The operating system 4010 can be installed in the cloud host 4020, and the operating system 4010 can also run software programs such as the application program 470, the service middleware 480 and the database 490. At the same time, the operating system 4010 can install the virtual machine 4030, and the virtual machine operating system 4040 can be run in the virtual machine 4030, which can be managed by the virtualization management software 4050 installed therein; in addition, the corresponding intranet IP address 4060 can be configured for the operating system 4010, and the virtualization operating system 4040 can also be installed in the physical server 4070.

[0100] When performing operating system data collection, it needs to be performed through the collection agent service. Specifically, operating system data collection can be performed through the SNMP protocol, the SSH protocol, and the collection agent service, and the obtained operating system data can include process data running in the operating system, network configuration data corresponding to the operating system, and system kernel data of the operating system, and the like. For the above data, the following processing can be performed respectively:

[0101] The process data in the operating system data 4010 is processed into application program-service middleware-database model data by the data collection model. The process data of the operating system is processed into application program-service middleware-database model and relational data. The network configuration data in the operating system data is processed into intranet network address data by the data collection model. The network configuration data of the operating system is processed into intranet IP model and relational data. The system kernel data in the operating system data is processed into operating system model data by the data collection model. The system kernel data of the operating system is processed into operating system model and relational data. Through the above steps, operating system data of various operating systems such as Linux, windows, AIX, etc. can be obtained, and the acquisition of operating system data of multiple types of operating systems is supported.

[0102] In an exemplary embodiment of the present disclosure, the data collection task includes a storage model data collection task; based on the data collection task, and in combination with the data collection model and the data collection tool, a data collection operation is performed to obtain target collection data, including: collecting storage device data through a network layer protocol, processing the storage device data into storage device model data by the data collection model; collecting library-equipped equipment data through a network layer protocol, processing the library-equipped equipment data into library-equipped equipment model data by the data collection model; collecting fiber switch data through a network layer protocol, and processing it into fiber switch model data by the data collection model; determining storage model related equipment, and establishing a storage device connection relationship between the storage model related equipment.

[0103] The storage device model data can be data of abstract features such as mutual connection between storage devices. The library-equipped equipment model data can be data containing abstract features of the library-equipped equipment. The fiber switch model data can be data containing abstract features of the fiber switch. The storage model related equipment can be related equipment from which the storage model data is derived. The storage device connection relationship can be a connection relationship between the storage model related equipment.

[0104] Continuing to refer to Figure 5For storage model data, storage device data can be collected through a network layer protocol. The storage device data is processed into storage device model data by a data collection model. Specifically, the storage device data can be collected through an SNMP protocol, an SSH protocol, and an SMI-S protocol and processed into storage device model and relationship data.

[0105] The library equipment data is collected through a network layer protocol, and the library equipment data is processed into library equipment model data by a data collection model. Specifically, the library equipment data can be collected through an SNMP protocol, an SSH protocol, and an SMI-S protocol and processed into library equipment model and relationship data. The fiber switch data is collected through a network layer protocol, and the fiber switch data is processed into fiber switch model data by a data collection model. Specifically, the fiber switch data can be collected through an SNMP protocol, an SSH protocol, and an SMI-S protocol and processed into fiber switch model and relationship data.

[0106] In addition, storage model related equipment can be determined, for example, the storage model related equipment can include a physical server 550, a storage device 560, a fiber switch 570, and a library equipment 580. After the storage model related equipment is determined, a storage device connection relationship between the storage model related equipment can be established. Based on the storage device connection relationship, the storage model data is collectively composed. By using a corresponding parsing program of a text parser, a plurality of storage device models can be adapted, and new storage device models can be easily extended.

[0107] In an exemplary embodiment of the present disclosure, establishing a storage device connection relationship between storage model related equipment includes: obtaining a server identification number matched with the storage model related equipment; based on the server identification number, establishing a first device connection relationship between a fiber switch, a storage device, and library equipment; based on the server identification number, establishing a second device connection relationship between a physical server, a storage device, and a fiber switch.

[0108] The server identification number can be an identification number of a world wide name (WWN) of each device. The first device connection relationship can be a connection relationship between the fiber switch, the storage device, and the library equipment. The second device connection relationship can be a connection relationship between the physical server, the storage device, and the fiber switch.

[0109] In establishing the device connection relationship, the first device connection relationship of the fiber switch, the storage device, and the library equipment can be established through the server identification number (WWN number) matching, and the second device connection relationship of the physical server, the storage device, and the fiber switch can be established through the WWN number matching. The established device connection relationship is used as a data basis for generating storage model data.

[0110] In an example embodiment of the present disclosure, the data collection task includes a rack device model data collection task; based on the data collection task, and in combination with the data collection model and the data collection tool, a data collection operation is performed to obtain target collection data, including: determining a rack external device connected to the rack device; obtaining rack device data and external device data from the rack device and the rack external device, respectively; and creating rack model data based on the rack device data and the external device data by the data collection model.

[0111] The rack external device can be a physical device connected to the rack. The rack model data can be data containing abstract features between the rack and the rack external device.

[0112] Reference is made to Figure 6 , Figure 6 A connection relationship diagram of a rack external device connected to a rack according to an example embodiment of the present disclosure is schematically shown. As can be seen from Figure 6 , the external device connected to the rack 610 can include a fiber switch 620, a tape library device 630, a security device 640, a storage device 650, a physical server 660, a load balancing device 670, a network switch 680, a data center room 690, and a blade server drawer 6010, etc. After determining the above-mentioned rack external device, rack device data and external device data can be obtained from the rack device and the rack external device, respectively; and rack model data can be created based on the rack device data and the external device data by the data collection model.

[0113] After determining the rack device and the rack external device, the rack device data and the external device data can be obtained from the rack device and the rack external device, respectively, by a data collection program in cooperation with a corresponding data collection tool. After obtaining the rack device data and the external device data, rack model data corresponding to the rack device data and the external device data can be generated according to the model data format of the data collection model.

[0114] In an example embodiment of the present disclosure, a topology relationship corresponding to the target collection data is determined; and the target collection data is stored in a graph database in a topological structure based on the topology relationship.

[0115] The topology relationship can refer to the mutual relationship between the spatial data of the target collection data obtained in accordance with the principles of topological geometry. The graph database is a data management system based on point and edge storage units and designed for efficient storage and query of graph data. For the target collection data obtained, a database based on point and edge storage units can be used for data storage.

[0116] After obtaining the target collection data, the topology relationship corresponding to the target collection data can be automatically determined. Reference is made to Figure 7, Figure 7 A topology structure diagram of the collected target collection data according to an example embodiment of the present disclosure is shown. Figure 7 The topology relationship between a plurality of different model data is shown, and the topology relationship is determined, so that the target collection data can be stored in a graph database in a topology structure. Using the graph database to store configuration and relationship data can improve the configuration relationship query speed and further enhance the data scalability.

[0117] When storing the target collection data, different service nodes can be represented by points, for example, the business system 110 and the application program 120, the service middleware 130, the database 150, the cloud host 150, the operating system 160, the domain name 170, the DMZ zone IP address 180, the load balancing virtual IP address 190, the internal network IP address 1010, the virtual machine 1020, the virtualization host system 1030, the virtualization management software 1040, the load balancing equipment 1050, the switch port 1060, the physical server 1070, the physical storage equipment 1080, the network switch 1090, the rack 1110, the blade server 1120, the fiber switch 1130, the private line 1140, the data center machine room 1150, the uninterruptible power supply (UPS) 1160, and the tape library equipment 1170, and the like. The above subjects are stored by nodes.

[0118] For the connection relationship between two nodes, edge data can be used for storage, for example, the business system 110 can contain the application program 120, and the connection relationship between the two is “contains”, and the business system 110 is node 1 corresponding to the edge; the business system 110 can use the service middleware 130 and the database 140, so the connection relationship between the business system 110 and the service middleware 130, and the connection relationship between the business system 110 and the database 140 are both “use”.

[0119] It should be noted that the terms “first”, “second”, and the like used in the present disclosure are only used to distinguish different network mapping relationship data and different device connection relationships, and should not impose any limitation on the present disclosure.

[0120] In summary, the data collection method of the present disclosure acquires a data collection task; acquires a pre-configured data collection model, the data collection model including any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model; performs a data collection operation based on the data collection model and the data collection task to obtain target collection data, the target collection data being stored in a topology structure. On one hand, through the pre-configured data collection model, the CMDB data can be automatically collected and updated without manual intervention. On the other hand, through the relatively comprehensive data collection model, the data quality of the target collection data can be further improved. On yet another hand, the topology structure is used to store the target collection data, which can effectively improve the expansibility of the target collection data.

[0121] It should be noted that although the steps of the method in the present disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired result. In addition or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be divided into multiple steps, etc.

[0122] In addition, in the present example embodiment, a data collection device is also provided. Referring to Figure 8 The data collection device 800 can include a task acquisition module 810, a model acquisition module 820, and a data collection module 830.

[0123] Specifically, the task acquisition module 810 is configured to acquire a data collection task; the model acquisition module 820 is configured to acquire a pre-configured data collection model, the data collection model including any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model; and the data collection module 830 is configured to perform a data collection operation based on the data collection model and the data collection task to obtain target collection data, the target collection data being stored in a topology structure.

[0124] In an example embodiment of the present disclosure, the data collection device 800 further includes an interface configuration module configured to: determine a data collection interface corresponding to the data collection task; configure a data collection program matched with the data collection interface according to the data collection task; and perform a data collection operation by the data collection program through the matched data collection interface.

[0125] In an example embodiment of the present disclosure, the data collection module 830 comprises a data collection unit configured to: determine a data collection tool matched with the data collection task; the data collection tool comprises a combination of any one or more of a data collection protocol, a data collection interface, and a data collection service; and perform a data collection operation based on the data collection task and in combination with the data collection tool, to obtain target collection data.

[0126] In an example embodiment of the present disclosure, the data collection task comprises a domain name network address data collection task, and the target collection data comprises domain name network address model data; the data collection unit comprises a first data collection subunit configured to: obtain a domain name calling interface, and through the domain name calling interface and an application layer protocol, obtain Internet domain name data and intranet domain name data; and based on the Internet domain name data and the intranet domain name data, create domain name network address model data by using a data collection model.

[0127] In an example embodiment of the present disclosure, the domain name network address model data comprises network mapping relationship data; the first data collection subunit is configured to perform: domain name resolution processing on the Internet domain name data to obtain buffer network addresses; first resolution processing and second resolution processing on the intranet domain name data to obtain virtual network addresses and intranet network addresses, respectively; and create first network mapping relationship data between the buffer network addresses and the virtual network addresses by using the data collection model; and create second network mapping relationship data between the buffer network addresses and the intranet network addresses by using the data collection model.

[0128] In an example embodiment of the present disclosure, the data collection task comprises a network layer data collection task; the data collection unit comprises a second data collection subunit configured to: determine network devices connected to switch ports, the network devices comprising a combination of any one or more of a storage device, a security device, a load balancing device, a physical server, and a fiber switch; determine to-be-collected network devices based on the network layer data collection task, obtain device data of the to-be-collected network devices, and generate initial network model data based on the device data; create device connection relationships between the to-be-collected network devices based on device physical addresses; and generate network model data based on the initial network model data and the device connection relationships.

[0129] In an example embodiment of the present disclosure, the second data acquisition subunit is configured to perform: acquiring network switch data through the application layer protocol of the development system model, processing the network switch data into switch-switch port model data by the data acquisition model; acquiring security device data through the application layer protocol, processing the security device data into security device model data by the data acquisition model; acquiring storage device data through the application layer protocol, processing the storage device data into storage device-fiber switch model data by the data acquisition model; acquiring operating system data through the application layer protocol and the network layer protocol, processing the operating system data into physical server model data by the data acquisition model; acquiring load balancing device data through the application layer protocol and the network layer protocol, processing the load balancing device data into load balancing device model data by the data acquisition model.

[0130] In an example embodiment of the present disclosure, the data acquisition task includes a software model data acquisition task; the data acquisition unit includes a third data acquisition subunit, configured to: acquire operating system data through the application layer protocol, process process data in the operating system data into application-service-middleware-database model data by the data acquisition model; process network configuration data in the operating system data into intranet network address data by the data acquisition model; process system kernel data in the operating system data into operating system model data by the data acquisition model.

[0131] In an example embodiment of the present disclosure, the data acquisition task includes a storage model data acquisition task; the data acquisition unit includes a fourth data acquisition subunit, configured to: acquire storage device data through the network layer protocol, process the storage device data into storage device model data by the data acquisition model; acquire library-equipped device data through the network layer protocol, process the library-equipped device data into library-equipped device model data by the data acquisition model; acquire fiber switch data through the network layer protocol, and process into fiber switch model data by the data acquisition model; determine storage model related devices, and establish storage device connection relationships between the storage model related devices.

[0132] In an example embodiment of the present disclosure, the fourth data acquisition subunit is configured to perform: obtaining a server identification number matched with the storage model related device; based on the server identification number, establishing a first device connection relationship between the fiber switch, the storage device and the library-equipped device; based on the server identification number, establishing a second device connection relationship between the physical server, the storage device and the fiber switch.

[0133] In an example embodiment of the present disclosure, the data collection task includes a rack device model data collection task; the data collection unit includes a fifth data collection subunit configured to: determine a rack external device connected to the rack device; respectively acquire rack device data and external device data from the rack device and the rack external device; and create rack model data based on the rack device data and the external device data by using the data collection model.

[0134] In an example embodiment of the present disclosure, the data collection device 800 further includes a data storage module configured to: determine a topological relationship corresponding to the target collection data; and store the target collection data in a topological structure to a graph database based on the topological relationship.

[0135] The specific details of the virtual modules of the data collection devices in the above embodiments have been described in detail in the corresponding data collection methods, and thus will not be described here.

[0136] It should be noted that, although several modules or units of the data collection device are mentioned in the above detailed description, such division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into a plurality of modules or units.

[0137] In addition, in an example embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0138] Those skilled in the art can understand that each aspect of the present disclosure can be implemented as a system, a method or a program product. Therefore, each aspect of the present disclosure can be embodied as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" here.

[0139] The electronic device 900 according to this embodiment of the present disclosure will be described below with reference to Figure 9 The electronic device 900 is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present disclosure. Figure 9 The electronic device 900 is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present disclosure.

[0140] As shown in Figure 9 The components of the electronic device 900 can include, but are not limited to, the above-mentioned at least one processing unit 910, the above-mentioned at least one storage unit 920, a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910), and a display unit 940.

[0141] The storage unit stores program codes which can be executed by the processing unit 910, so that the processing unit 910 performs the steps described in the above "Exemplary Methods" section according to various exemplary embodiments of the present disclosure.

[0142] The storage unit 920 can include a readable medium in the form of volatile storage such as a random access memory (RAM) 921 and / or cache memory 922, and can further include a read-only memory (ROM) 923.

[0143] The storage unit 920 can include program / utility 924 having a set of program modules 925 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or a combination thereof can include implementation of a network environment.

[0144] The bus 930 can represent one or more of several types of bus structures, including a storage bus or bus controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of a variety of bus architectures.

[0145] The electronic device 900 can also communicate with one or more external devices 970 such as a keyboard or pointing device, using one or more communication interfaces 950. For example, the communication interfaces 950 can include a sound card, a modem, a network interface card, an infrared communication device, a wireless communication device, and / or a chipset such as a Bluetooth® device, etc. The communication interfaces 950 allow the electronic device 900 to communicate with one or more devices using electrical, electromagnetic, or optical packets in a wired or wireless communication scheme. The communication interfaces 950 can transmit and / or receive data according to various wired or wireless communication protocols including, but not limited to, Bluetooth®, Wi-Fi, 3G, 4G, Code Division Multiple Access (CDMA), Global System for Mobile Communications (GSM), and / or various other protocols.

[0146] Those skilled in the art can easily understand from the above description of the embodiments that the example embodiments described herein can be implemented by software or by software in combination with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a U disk, a mobile hard disk, etc.) or a network, and includes a plurality of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to perform the methods according to the embodiments of the present disclosure.

[0147] In the example embodiments of the present disclosure, a computer readable storage medium is also provided, on which a program product capable of implementing the above-mentioned method of the present disclosure is stored. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program codes for causing a terminal device to perform the steps described in the above-mentioned “example method” section according to various example embodiments of the present disclosure when the program product is run on the terminal device.

[0148] Reference Figure 10 As shown, a program product 1000 for implementing the above-mentioned method according to the embodiments of the present disclosure is described, which can adopt a portable compact disc read-only memory (CD-ROM) and include program codes, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited to this, and in this document, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device or apparatus.

[0149] The program product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, be but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0150] A computer readable signal medium can include a propagated data signal with computer executable code embodied therein. For example, a propagated signal can be an electromagnetic signal, an optical signal, and / or any other suitable type of signal. Such a propagated signal can be in the form of electrical magnetic waves, optical waves, and / or any other suitable type of waves upon which computer executable code is embodied. A suitable medium for storing and / or transmitting computer readable code includes one or more types of random access memory (RAM), magnetic storage, optical storage, and / or any other suitable type of storage.

[0151] Program code embodied on a computer readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0152] Computer readable program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider. The application program code can be downloaded to the user's computing device from an external computing device or server through any type of network, including a local area network, a wide area network, or the Internet using a browser or other applet.

[0153] Furthermore, the above-described figures are only schematic and are non-limiting. It is readily understood that the processes depicted in the figures are not necessarily performed in the order depicted. Further, it is readily understood that the processes can be performed synchronously or asynchronously, and that the processes can be performed in a different order than depicted in the figures.

[0154] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0155] It is to be understood that the application is not limited to the precise details of construction and the exemplary embodiments described above and illustrated in the drawings. Various modifications and changes can be made thereunto without departing from the scope of the application. The scope of the application is indicated by the appended claims rather than by the embodiments disclosed above.

Claims

1. A data acquisition method, characterized by, The method comprises: acquiring a data collection task, the data collection task being an execution task of acquiring specific type data configured according to business requirements; acquiring a pre-configured data collection model, and matching a data collection model matched with the data collection task from the pre-configured data collection model, the data collection model comprising any one or a combination of multiple of a domain name network address model, a network layer data model, a software model, a storage model, and a rack device model; performing a data collection operation based on the data collection model and the data collection task to obtain target collection data, and automatically determining a topology relationship corresponding to the target collection data; based on the topology relationship, storing the target collection data in a graph database in a topology structure, the graph database being a data management system taking points and edges as basic storage units.

2. The method of claim 1, wherein, The method further comprises: determining a data collection interface corresponding to the data collection task; configuring a data collection program matched with the data collection interface according to the data collection task; performing a data collection operation by the data collection program through the matched data collection interface.

3. The method of claim 1, wherein, The data collection operation based on the data collection model and the data collection task to obtain target collection data comprises: determining a data collection tool matched with the data collection task; the data collection tool comprising any one or a combination of multiple of a data collection protocol, a data collection interface, and a data collection service; performing the data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data.

4. The method of claim 3, wherein, The data collection task comprises a domain name network address data collection task, and the target collection data comprises domain name network address model data. The data collection operation based on the data collection task and in combination with the data collection model and the data collection tool to obtain the target collection data comprises: acquiring a domain name calling interface, and acquiring Internet domain name data and intranet domain name data through the domain name calling interface and an application layer protocol; creating, by the data collection model, the domain name network address model data based on the Internet domain name data and the intranet domain name data.

5. The method of claim 4, wherein, The domain name network address model data comprises network mapping relationship data; the creation, by the data collection model, of the domain name network address model data based on the Internet domain name data and the intranet domain name data comprises: performing domain name resolution processing on the Internet domain name data to obtain a buffer network address; respectively performing first resolution processing and second resolution processing on the intranet domain name data to respectively obtain a virtual network address and an intranet network address; creating, by the data collection model, first network mapping relationship data between the buffer network address and the virtual network address; creating, by the data collection model, second network mapping relationship data between the buffer network address and the intranet network address.

6. The method of claim 3, wherein, The data collection task includes a network layer data collection task; the data collection operation is performed based on the data collection task, in combination with the data collection model and the data collection tool, to obtain the target collection data, including: Determine the network device connected to the switch port, the network device includes any one or combination of storage device, security device, load balancing device, physical server, fiber switch; Determine the network device to be collected based on the network layer data collection task, obtain the device data of the network device to be collected, and generate initial network model data based on the device data; Create a device connection relationship between each of the network devices to be collected based on the device physical address; Generate network model data based on the initial network model data and the device connection relationship.

7. The method of claim 6, wherein, The device data of the network device to be collected is obtained, and the initial network model data is generated based on the device data, including: Collect network switch data through the application layer protocol of the development system model, and process the network switch data into switch-switch port model data by the data collection model; Collect security device data through the application layer protocol, and process the security device data into security device model data by the data collection model; Collect storage device data through the application layer protocol, and process the storage device data into storage device-fiber switch model data by the data collection model; Collect operating system data through the application layer protocol and network layer protocol, and process the operating system data into physical server model data by the data collection model; Collect load balancing device data through the application layer protocol and network layer protocol, and process the load balancing device data into load balancing device model data by the data collection model.

8. The method of claim 3, wherein, The data collection task includes a software model data collection task; the data collection operation is performed based on the data collection task, in combination with the data collection model and the data collection tool, to obtain the target collection data, including: Collect operating system data through the application layer protocol, and process the process data in the operating system data into application program-service middleware-database model data by the data collection model; Process the network configuration data in the operating system data into intranet network address data by the data collection model; Process the system kernel data in the operating system data into operating system model data by the data collection model.

9. The method of claim 3, wherein, The data collection task includes a storage model data collection task; the data collection operation is performed based on the data collection task, in combination with the data collection model and the data collection tool, to obtain the target collection data, including: Collect storage device data through the network layer protocol, and process the storage device data into storage device model data by the data collection model; Collect library-equipped device data through the network layer protocol, and process the library-equipped device data into library-equipped device model data by the data collection model; Collecting the fiber switch data through the network layer protocol, and processing the fiber switch data into fiber switch model data by the data collection model; Determine the storage model related devices, and establish the storage device connection relationship between the storage model related devices.

10. The method of claim 9, wherein, The method for establishing the storage device connection relationship between the storage model related devices comprises: Obtain the server identification number matched with the storage model related devices; Based on the server identification number, establish the first device connection relationship between the fiber switch, the storage device and the tape library device; Based on the server identification number, establish the second device connection relationship between the physical server, the storage device and the fiber switch.

11. The method of claim 3, wherein, The data collection task comprises a rack device model data collection task; based on the data collection task, and combining the data collection model and the data collection tool to perform the data collection operation, the target collection data is obtained, which comprises: Determine the rack external device connected with the rack device; Respectively obtain rack device data and external device data from the rack device and the rack external device; Create rack model data based on the rack device data and the external device data by the data collection model.

12. A data acquisition device, characterized by Comprise: Task acquisition module, used for acquiring data collection tasks, the data collection tasks being execution tasks for acquiring specific type data according to business requirements; Model acquisition module, used for matching and acquiring data collection models matched with data collection tasks from pre-configured data collection models, the data collection models comprising any one or more combinations of domain name network address model, network layer data model, software model, storage model and rack device model; Data collection module, used for performing data collection operation based on the data collection model and the data collection task to obtain target collection data, and automatically determining the topology relationship corresponding to the target collection data; Based on the topology relationship, the target collection data is stored in a graph database in a topology structure, and the graph database is a data management system taking points and edges as basic storage units.

13. An electronic device, comprising: Comprise: Processor; And Memory, the memory having computer readable instructions stored thereon, the computer readable instructions being executed by the processor to implement the data collection method according to any one of claims 1 to 11.

14. A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the data collection method according to any one of claims 1 to 11.

Images