Method, apparatus, electronic device and storage medium for project deployment

Abstract

The present application provides a method, apparatus, electronic device, and storage medium for project deployment. Among them, in the method for project deployment, first, project information and project code of the project to be deployed are obtained. Then, based on the project information, project registration of the project to be deployed is performed under a preset main project directory. A pre-trained software security detection model is called to process the code of the project to be deployed to obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data. Finally, project deployment is performed on the projects to be deployed whose project security scores are greater than a preset value. The method of the present application adopts a mode of merging multiple front-end projects and deploying them under the main project directory, which is convenient for unified management, and each project does not need to apply for a Web server separately, saving a large amount of resources. At the same time, the project code can be automatically audited, reducing the risks of project implementation and operation.

Description

Technical Field

[0001] This application relates to the technical field of project management, and in particular, to a method, device, electronic device, and storage medium for project deployment. Background Art

[0002] Traditional enterprise-level projects are usually managed in a rough manner. The resources, manpower, costs, and schedules of each project are controlled by the project team itself, making it difficult to conduct unified supervision. When deploying projects, different projects are also deployed on different servers, which consumes a large amount of server resources and is also difficult to manage the projects uniformly. At the same time, the review of projects is usually carried out manually, and the risk assessment of projects depends heavily on the personal experience of the staff, wasting a large amount of human resources.

[0003] Therefore, there are problems such as a large amount of resource waste, low project deployment efficiency, and difficulty in unified management of projects in the existing project deployment methods. Summary of the Invention

[0004] In view of this, this application provides a method, device, electronic device, and storage medium for project deployment to solve the problems of a large amount of resource waste, low project deployment efficiency, and difficulty in unified management of projects in the existing technology.

[0005] To achieve the above object, this application provides the following technical solutions:

[0006] The first aspect of this application discloses a method for project deployment, including:

[0007] Obtain the project information and project code of the project to be deployed; wherein, the project information includes the project basic information and detailed configuration information;

[0008] Based on the project information, perform project registration of the project to be deployed in a preset main project directory;

[0009] Call a pre-trained software security detection model to process the code of the project to be deployed to obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data;

[0010] Deploy the project to be deployed whose project security score is greater than a preset value.

[0011] Optionally, in the above method, after performing project registration of the project to be deployed in a preset main project directory based on the project information, it further includes:

[0012] Upload the version package of the project to be deployed after registration to the server.

[0013] Optionally, in the above method, the training process of the software security detection model includes:

[0014] Obtain a sample data set with marked project security scores;

[0015] Input the sample data set with marked project security scores into the initial model for calculation to obtain the project security score of the current sample data;

[0016] Determine whether the project security score of the current sample data is consistent with the project security score of the actually marked sample data;

[0017] If the project security score of the current sample data is consistent with the project security score of the actually marked sample data, the construction of the software security detection model is completed;

[0018] If the project security score of the current sample data is inconsistent with the project security score of the actually marked sample data, calculate the error function and use the error function to adjust the parameters of the neural network model until the project security score of the output current sample data is consistent with the project security score of the actually marked sample data, then the construction of the software security detection model is completed.

[0019] Optionally, in the above method, the project deployment of the project with a project security score greater than the preset value includes:

[0020] Generate a project deployment task for the project to be deployed with a project security score greater than the preset value;

[0021] Schedule the project deployment task through a scheduled job to complete the project deployment.

[0022] The second aspect of this application discloses a project deployment device, including:

[0023] An acquisition unit, configured to acquire project information and project code of the project to be deployed; wherein, the project information includes the project basic information and detailed configuration information;

[0024] A registration unit, configured to perform project registration of the project to be deployed under a preset main project directory based on the project information;

[0025] A call unit, configured to call a pre-trained software security detection model to process the code of the project to be deployed to obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data;

[0026] A deployment unit, configured to perform project deployment on the project to be deployed with a project security score greater than the preset value.

[0027] Optionally, the above-mentioned device further includes:

[0028] A sending unit, configured to upload the version package of the project to be deployed after registration is completed to a server.

[0029] Optionally, for the above-mentioned device, the calling unit includes:

[0030] An acquisition subunit, configured to acquire a sample data set for annotating the security score of a project;

[0031] A first operation subunit, configured to input the sample data set for annotating the security score of the project into an initial model for operation to obtain the security score of the project for the current sample data;

[0032] A judgment subunit, configured to judge whether the security score of the project for the current sample data is consistent with the security score of the actually annotated sample data;

[0033] A construction subunit, configured to complete the construction of the software security detection model if the security score of the project for the current sample data is consistent with the security score of the actually annotated sample data;

[0034] A parameter adjustment subunit, configured to, if the security score of the project for the current sample data is inconsistent with the security score of the actually annotated sample data, obtain an error function and use the error function to adjust the parameters of the neural network model until the security score of the project for the output current sample data is consistent with the security score of the actually annotated sample data, and then complete the construction of the software security detection model.

[0035] Optionally, for the above-mentioned device, the deployment unit includes:

[0036] A task generation subunit, configured to generate a project deployment task for a project to be deployed whose project security score is greater than a preset value;

[0037] A scheduling subunit, configured to schedule the project deployment task by means of a timed job to complete project deployment.

[0038] A third aspect of this application discloses an electronic device, including:

[0039] One or more processors;

[0040] A storage device, on which one or more programs are stored;

[0041] When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method according to any one of the first aspect of this application.

[0042] The fourth aspect of the present application discloses a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in any one of the first aspects of the present application is implemented.

[0043] As can be seen from the above technical solutions, a method for project deployment provided by the present application first obtains the project information and project code of the project to be deployed. Among them, the project information includes project basic information and detailed configuration information. Then, based on the project information, project registration of the project to be deployed is performed under a preset main project directory. A pre-trained software security detection model is called to process the code of the project to be deployed to obtain a project security score. Among them, the software security detection model is pre-trained according to preset sample data. Finally, project deployment is performed on the projects to be deployed whose project security scores are greater than a preset value. It can be seen that the method of the present application adopts a mode of merging multiple front-end projects into the main project directory for deployment, which is convenient for unified management. And each project does not need to apply for a Web server separately, saving a large amount of resources. At the same time, the project code can be automatically audited, reducing the risks of project implementation and operation. It solves the problems of a large amount of resource waste, low project deployment efficiency, and difficulty in unified management existing in the prior art in project deployment methods. Description of the Drawings

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to the provided drawings.

[0045] Figure 1 It is a flowchart of a method for project deployment disclosed in an embodiment of the present application;

[0046] Figure 2 It is a flowchart of an implementation manner of the training process of the software security detection model in step S103 disclosed in another embodiment of the present application;

[0047] Figure 3 It is a schematic diagram of a project deployment device disclosed in another embodiment of the present application;

[0048] Figure 4 It is a schematic diagram of an electronic device disclosed in another embodiment of the present application. Detailed Embodiments

[0049] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0050] In the present application, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of additional identical elements in the process, method, article or device including the said element.

[0051] Also, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0052] As can be seen from the background technology, there are problems such as a large amount of resource waste, low project deployment efficiency, and difficulty in unified management of projects in the existing project deployment methods.

[0053] In view of this, the present application provides a method, device, electronic device and storage medium for project deployment to solve the problems of a large amount of resource waste, low project deployment efficiency, and difficulty in unified management of projects in the existing technology.

[0054] The embodiments of the present application provide a method for project deployment, which can be seen Figure 1 , specifically including:

[0055] S101. Obtain the project information and project code of the project to be deployed; wherein, the project information includes project basic information and detailed configuration information.

[0056] It should be noted that when project deployment is required, first obtain the project information and project code of the project to be deployed. Among them, the project information includes project basic information and detailed configuration information.

[0057] S102. Based on the project information, perform project registration of the project to be deployed under the preset main project directory.

[0058] It should be noted that after obtaining the project information and project code of the project to be deployed, based on the project information, project registration of the project to be deployed is carried out under the preset main project directory. Specifically, a directory for the project to be deployed is created under the nginx path in the main project directory to store the front-end resource package of the project. Based on the obtained project information, the nginx configuration file and Vue configuration file are modified to add the network address of the new project for accessing the new project under the main project domain name. For example, the main project domain name is http: / / domain, the Nginx path is nginx / html / dist, and the newly connected project is accessed using http: / / domain / a. The overall process is as follows:

[0059] 1) Create a new folder A under nginx / html / otherPro to store the connected project A.

[0060] 2) Configure the vue.config.js file and set publicPath: ' / otherPro / A / ' in module.exports; configure the URL in the scr / router / index.js file and set base: ' / a / '.

[0061] 3) Modify the server part of the nginx.conf file. location / points to the web front-end of the main project, and location / a points to the web front-end of project A.

[0062] 4) Enter the nginx installation directory, reload after modifying the configuration to take effect: nginx -s reload.

[0063] Optionally, in another embodiment of the present application, after performing step S102, it may further include:

[0064] Upload the version package of the project to be deployed after registration to the server.

[0065] It should be noted that after completing the project registration, the version package of the project to be deployed after registration is uploaded to the server dedicated for version release, so as to create a version release work order, fill in the production plan, online content, test report, etc.

[0066] S103. Call a pre-trained software security detection model to process the code of the project to be deployed, and obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data.

[0067] It should be noted that before project deployment, a security review of the project to be deployed is required. Therefore, a pre-trained software security detection model is called to process the code of the project to be deployed, and a project security score is obtained. Among them, the software security detection model is pre-trained based on sample data with marked project security scores. The software security detection model converts the program code into a sequence of word vectors. The convolutional layer performs convolution on the word vectors using different-sized convolutions, and the pooling layer converts the results of the convolutional layer into long feature vectors. The fully connected layer performs backpropagation according to the penalty protocol of the penalty layer, updates the word vectors and convolutional kernel parameters, and finally performs security classification based on the output results of the softmax layer to identify software vulnerabilities and obtain the project security score.

[0068] Optionally, in another embodiment of the present application, an implementation manner of the training process of the software security detection model in step S103 is as Figure 2 shown, and may include:

[0069] S201. Obtain a sample data set with marked project security scores.

[0070] It should be noted that first, a sample data set with marked project security scores is obtained, and these sample data are used as training data and input into the neural network model for training.

[0071] S202. Input the sample data set with marked project security scores into the initial model for operation to obtain the project security score of the current sample data.

[0072] S203. Determine whether the project security score of the current sample data is consistent with the actually marked project security score of the sample data.

[0073] It should be noted that after obtaining the project security score of the current sample data through operation in the initial operation model, the obtained project security score of the current sample data is compared with the actually marked project security score of the current sample data to determine whether the project security score of the current sample data obtained through operation in the initial operation model is accurate.

[0074] S204. If the project security score of the current sample data is consistent with the actually marked project security score of the sample data, the construction of the software security detection model is completed.

[0075] S205. If the project security score of the current sample data is inconsistent with the actually marked project security score of the sample data, an error function is obtained, and the parameters of the neural network model are adjusted using the error function until the output project security score of the current sample data is consistent with the actually marked project security score of the sample data, and then the construction of the software security detection model is completed.

[0076] It should be noted that if the project security score of the calculated sample data is inconsistent with the project security score of the actually labeled sample data, the error function of the neural network model is calculated, the parameters of the neural network model are adjusted using the error function, and a new round of operations is performed until the project security score of the output sample data is consistent with the project security score of the actually labeled sample data, then the construction of the software security detection model is completed.

[0077] S104. Perform project deployment on the to-be-deployed projects with a project security score greater than a preset value.

[0078] It should be noted that after obtaining the project security score of the to-be-deployed project, project deployment is performed on the to-be-deployed projects with a project security score greater than the preset value. If the project security score is greater than the preset value, it is considered that the risk of its project is relatively low and project deployment can be carried out. This preset value is set according to actual requirements, for example, 8 points.

[0079] Optionally, in another embodiment of the present application, an implementation manner of step S104 may include:

[0080] Generate a project deployment task for the to-be-deployed project with a project security score greater than the preset value;

[0081] Schedule the project deployment task in the way of a timed job to complete the project deployment.

[0082] It should be noted that for the to-be-deployed projects with a project security score greater than the preset value, corresponding project deployment tasks are generated. Then the project deployment tasks are abstracted into timed jobs, and ZooKeeper (a distributed application coordination service) is used to synchronize the status and metadata of the distributed job shards. By obtaining task information from ZooKeeper, scheduling is triggered respectively when the corresponding time points are reached. Using this architecture can greatly improve the version deployment efficiency, standardize the online operation, and reduce the production operation and maintenance risks.

[0083] A method for project deployment provided by this application first obtains the project information and project code of the project to be deployed. Among them, the project information includes project basic information and detailed configuration information. Then, based on the project information, project registration of the project to be deployed is performed under the preset main project directory. A pre-trained software security detection model is called to process the code of the project to be deployed to obtain a project security score. Among them, the software security detection model is pre-trained according to the preset sample data. Finally, project deployment is performed on the projects to be deployed whose project security scores are greater than the preset value. It can be seen that the method of this application adopts a mode of merging multiple front-end projects for deployment under the main project directory, which is convenient for unified management. Moreover, each project does not need to apply for a Web server separately, saving a large amount of resources. At the same time, it can automatically review the project code, reducing the risks of project implementation and operation. This solves the problems of a large amount of resource waste, low project deployment efficiency, and difficulty in unified management in the existing project deployment methods.

[0084] Another embodiment of this application also provides a project deployment device, specifically as Figure 3 shown, including:

[0085] An acquisition unit 301, configured to acquire the project information and project code of the project to be deployed. Among them, the project information includes project basic information and detailed configuration information.

[0086] A registration unit 302, configured to perform project registration of the project to be deployed under the preset main project directory based on the project information.

[0087] A calling unit 303, configured to call a pre-trained software security detection model to process the code of the project to be deployed to obtain a project security score. Among them, the software security detection model is pre-trained according to the preset sample data.

[0088] A deployment unit 304, configured to perform project deployment on the projects to be deployed whose project security scores are greater than the preset value.

[0089] In this embodiment, for the specific execution processes of the acquisition unit 301, the registration unit 302, the calling unit 303, and the deployment unit 304, reference can be made to the content of the corresponding Figure 1 method embodiment, which will not be elaborated here.

[0090] An apparatus for project deployment provided by this application first has an acquisition unit 301 acquire project information and project code of a project to be deployed; wherein, the project information includes project basic information and detailed configuration information. Then a registration unit 302 performs project registration of the project to be deployed under a preset main project directory based on the project information. A call unit 303 calls a pre-trained software security detection model to process the code of the project to be deployed, and obtains a project security score; wherein, the software security detection model is pre-trained according to preset sample data. Finally, a deployment unit 304 performs project deployment on the project to be deployed whose project security score is greater than a preset value. It can be seen from this that the method of this application adopts a mode of merging multiple front-end projects into the main project directory for deployment, which is convenient for unified management, and each project does not need to apply for a Web server separately, saving a large amount of resources. At the same time, it can automatically review the project code, reducing the risks of project implementation and operation. It solves the problems of a large amount of resource waste, low project deployment efficiency, and difficulty in unified management existing in the prior art for project deployment methods.

[0091] Optionally, in another embodiment of this application, the above apparatus for project deployment may further include:

[0092] A sending unit, configured to upload the version package of the project to be deployed after registration to a server.

[0093] In this embodiment, for the specific execution process of the sending unit, reference may be made to the corresponding method embodiment content above, which will not be elaborated here.

[0094] Optionally, in another embodiment of this application, an implementation manner of the call unit 303 may include:

[0095] An acquisition subunit, configured to acquire a sample data set for annotating project security scores.

[0096] A first operator subunit, configured to input the sample data set for annotating project security scores into an initial model for operation, and obtain a project security score of the current sample data.

[0097] A judgment subunit, configured to judge whether the project security score of the current sample data is consistent with the project security score of the actually annotated sample data.

[0098] A construction subunit, configured to complete the construction of the software security detection model if the project security score of the current sample data is consistent with the project security score of the actually annotated sample data.

[0099] A parameter adjustment subunit, configured to, if the project security score of the current sample data is inconsistent with the project security score of the actually annotated sample data, calculate an error function and use the error function to adjust the parameters of the neural network model until the project security score of the output current sample data is consistent with the project security score of the actually annotated sample data, then complete the construction of the software security detection model.

[0100] In this embodiment, for the specific execution processes of the acquisition subunit, the first operation subunit, the judgment subunit, the construction subunit, and the parameter adjustment subunit, reference may be made to the corresponding Figure 2 method embodiment content, which will not be elaborated here.

[0101] Optionally, in another embodiment of the present application, an implementation manner of the deployment unit 304 may include:

[0102] A task generation subunit, configured to generate a project deployment task for a to-be-deployed project whose project security score is greater than a preset value;

[0103] A scheduling subunit, configured to schedule the project deployment task by means of a scheduled job to complete the project deployment.

[0104] In this embodiment, for the specific execution processes of the task generation subunit and the scheduling subunit, reference may be made to the corresponding above-mentioned method embodiment content, which will not be elaborated here.

[0105] Another embodiment of the present application further provides an electronic device, as Figure 4 shown, specifically including:

[0106] One or more processors 401.

[0107] A storage device 402, on which one or more programs are stored.

[0108] When the one or more programs are executed by the one or more processors 401, the one or more processors 401 are caused to implement any one of the methods in the above embodiments.

[0109] Another embodiment of the present application further provides a computer storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, any one of the methods in the above embodiments is implemented.

[0110] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for a system or system embodiment, since it is basically similar to a method embodiment, the description is relatively simple. For the relevant parts, reference can be made to the description of the method embodiment. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative efforts.

[0111] Those skilled in the art can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0112] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for project deployment, characterized in that, including: Obtain the project information and project code of the project to be deployed; wherein, the project information includes the project basic information and detailed configuration information; Based on the project information, perform project registration of the project to be deployed under a preset main project directory; Upload the version package of the project to be deployed after registration to the server; Call a pre-trained software security detection model to process the code of the project to be deployed to obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data; Deploy the project to be deployed whose project security score is greater than a preset value.

2. The method according to claim 1, wherein The training process of the software security detection model includes: Obtain a sample data set with labeled project security scores; Input the sample data set with labeled project security scores into the initial model for calculation to obtain the project security score of the current sample data; Determine whether the project security score of the current sample data is consistent with the project security score of the actually labeled sample data; If the project security score of the current sample data is consistent with the project security score of the actually labeled sample data, complete the construction of the software security detection model; If the project security score of the current sample data is not consistent with the project security score of the actually labeled sample data, calculate the error function and use the error function to adjust the parameters of the neural network model until the project security score of the output current sample data is consistent with the project security score of the actually labeled sample data, then complete the construction of the software security detection model.

3. The method according to claim 1, characterized in that, The deploying the project to be deployed whose project security score is greater than a preset value includes: Generate a project deployment task for the project to be deployed whose project security score is greater than a preset value; Schedule the project deployment task through a scheduled job to complete the project deployment.

4. A device for project deployment, characterized in that, including: An obtaining unit, configured to obtain the project information and project code of the project to be deployed; wherein, the project information includes the project basic information and detailed configuration information; A registering unit, configured to perform project registration of the project to be deployed under a preset main project directory based on the project information; A sending unit, configured to upload the version package of the project to be deployed after registration to the server; A calling unit, configured to call a pre-trained software security detection model to process the code of the project to be deployed to obtain a project security score; wherein, the software security detection model is pre-trained according to preset sample data; A deploying unit, configured to deploy the project to be deployed whose project security score is greater than a preset value.

5. The device according to claim 4, characterized in that, The calling unit includes: An obtaining subunit, configured to obtain a sample data set with labeled project security scores; A first calculating subunit, configured to input the sample data set with labeled project security scores into the initial model for calculation to obtain the project security score of the current sample data; A judging subunit, configured to judge whether the project security score of the current sample data is consistent with the project security score of the actually labeled sample data; A construction subunit, configured to complete the construction of the software security detection model if the project security score of the current sample data is consistent with the project security score of the actually labeled sample data; A parameter tuning subunit, configured to, if the project security score of the current sample data is inconsistent with the project security score of the actually labeled sample data, obtain an error function, and use the error function to adjust the parameters of the neural network model until the project security score of the output current sample data is consistent with the project security score of the actually labeled sample data, then complete the construction of the software security detection model.

6. The device according to claim 4, characterized in that, The deployment unit includes: A task generation subunit, configured to generate a project deployment task for a to-be-deployed project whose project security score is greater than a preset value; A scheduling subunit, configured to schedule the project deployment task by means of a scheduled job to complete project deployment.

7. An electronic device, characterized in that, Comprising: One or more processors; A storage device having stored thereon one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 3.

8. A computer storage medium, characterized in that, Having stored thereon a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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