Device and method for backing up image file based on dynamic decision making

Abstract

A device and a method for backing up an image file based on dynamic decision making is provided. The method includes following steps: using metadata to obtain a system name corresponding to a to-be-backed-up-image-file-name; using a quantitative score to obtain a summed quantitative score corresponding to the system name and the to-be-backed-up-image-file-name; using a summed quantitative score to select a target cloud environment backup operation function corresponding to the system name and the to-be-backed-up-image-file-name; and using a target Web API to perform a distributed backup operation on a to-be-backed-up-image-file to obtain an image file backup result.

Description

Technical Field

[0001] This invention relates to an apparatus and method for backing up image files based on dynamic decision-making. Prior Technology

[0002] Currently, cloud-related technologies are widely used. However, there is still a lack of effective image file backup technologies. Summary of the Invention

[0003] The device for backing up image files based on dynamic decision-making of the present invention includes an environmental importance index collection module, an environmental and resource importance assessment module, and a dynamic decision-making automatic backup execution module. The environmental importance index collection module uses interpretive data to obtain the system name corresponding to the name of the image file to be backed up. The environmental and resource importance assessment module uses quantitative scores to obtain a totalized quantitative score corresponding to the system name and the name of the image file to be backed up. The dynamic decision-making automatic backup execution module uses the totalized quantitative score to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up. The dynamic decision-making automatic backup execution module uses a target Web API to perform distributed backup operations on the image file to be backed up to obtain the image file backup result. The target Web API corresponds to the target cloud environment backup operation function, and the image file to be backed up corresponds to the name of the image file to be backed up.

[0004] The present invention provides a method for backing up image files based on dynamic decision-making, suitable for an apparatus comprising an environmental importance index collection module, an environmental and resource importance assessment module, and a dynamic decision-making automatic backup execution module. The method includes the following steps: the environmental importance index collection module uses interpretive data to obtain a system name corresponding to the name of the image file to be backed up; the environmental and resource importance assessment module uses quantitative scores to obtain a totalized quantitative score corresponding to the system name and the name of the image file to be backed up; the dynamic decision-making automatic backup execution module uses the totalized quantitative score to select a target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up; and the dynamic decision-making automatic backup execution module uses a target Web API to perform a distributed backup operation on the image file to be backed up to obtain the image file backup result, wherein the target Web API corresponds to a target cloud environment backup operation function, and the image file to be backed up corresponds to the name of the image file to be backed up. Simple Explanation of the Diagram

[0005] Figure 1 is a schematic diagram of an apparatus for backing up image files based on dynamic decision-making according to an embodiment of the present invention. Figures 2, 3 and 4 are further illustrations of the device for backup image files based on dynamic decision-making shown in Figure 1. Figure 5 is an example of the operation of the device for backup image files based on dynamic decision-making shown in Figure 1. Figure 6 is another operational example of the device for backing up image files based on dynamic decision-making shown in Figure 1. Figure 7 is a flowchart illustrating a method for backing up image files based on dynamic decision-making according to an embodiment of the present invention. Implementation

[0006] Figure 1 is a schematic diagram of an apparatus for backing up image files based on dynamic decision-making according to an embodiment of the present invention. In this embodiment, the apparatus for backing up image files based on dynamic decision-making may include an environmental importance indicator collection module 4, an environmental and resource importance assessment module 5, and a dynamic decision-making automatic backup execution module 7. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include a user interface 1. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include a response module 2. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include an image file resource collection module 3. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include a custom cloud environment backup operation function 6. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include a distributed container image file inventory module 8 and a distributed container image file backup module 9. In other embodiments, the apparatus for backing up image files based on dynamic decision-making may include a security and image file integrity verification module 10. In one embodiment, the user interface 1, response module 2, image file resource collection module 3, environmental importance indicator collection module 4, environmental and resource importance assessment module 5, customized cloud environment backup operation function 6, dynamic decision automatic backup execution module 7, distributed container image file list module 8, distributed container image file backup module 9, and security and image file integrity verification module 10 may be software and / or firmware code executed by the processor.

[0007] Figures 2, 3, and 4 further illustrate the device for backing up image files based on dynamic decision-making shown in Figure 1. Please refer to Figures 1, 2, 3, and 4 simultaneously. As shown in Figure 2, the environmental and resource importance assessment module 5 may include an image file conversion unit 5.1, an image file data management unit 5.2, and a link data management unit 5.3. Further, the environmental and resource importance assessment module 5 may include a business criticality indicator unit 5.4, a service availability indicator unit 5.5, and a compliance and security indicator unit 5.6. As shown in Figure 3, the dynamic decision-making automatic backup execution module 7 may include a decision analysis and quantitative calculation unit 7.1 and an image file backup selection unit 7.2. Further, the dynamic decision-making automatic backup execution module 7 may include a link data management unit 7.3. As shown in Figure 4, the distributed container image file backup module 9 may include a backup decision link management unit 9.1 and a distributed container image file selection unit 9.2. Further, the distributed container image file backup module 9 may include a distributed container image file backup execution unit 9.3.

[0008] Figure 5 is an example of the operation of the backup image file device based on dynamic decision-making shown in Figure 1. Please refer to Figures 1, 2, 3 and 5 simultaneously.

[0009] In step S501, user interface 1 can receive the name of the image file to be backed up. For example, the image file to be backed up can be a cloud-native container image file such as a Docker Image and / or a Docker Image Tar File. Specifically, the user can operate user interface 1 to select the name of the image file to be backed up. More specifically, user interface 1 can be developed based on Python and provide a Web Service; for example, user interface 1 can be written based on HTML, JavaScript, or CSS. Based on this, user interface 1 can transmit data to response module 2 via HTTP POST. Then, response module 2 can receive the name of the image file to be backed up from user interface 1. Specifically, response module 2 can be an HTTP Server interface module written in Go and also has the characteristics of a web service request (HTTP / HTTPS Service Request).

[0010] In step S502, the image file resource collection module 3 can obtain interpretation data using the name of the image file to be backed up. This interpretation data may include Tag Name, Creation Time, Image Audit Log, Image Digest, and vulnerability scan report. Specifically, for Docker Registry or Harbor systems stored in the image file repository platform, the image file resource collection module 3 can aggregate the stored data to obtain interpretation data. More specifically, the image file resource collection module 3 can use the interpretation data to obtain the (unique) image file identifier of this image file through the image file conversion unit 5.1 and the image file data management unit 5.2.

[0011] In step S503, the environmental importance index collection module 4 can use interpretive data to obtain the system name corresponding to the name of the image file to be backed up. Then, the environmental and resource importance assessment module 5 can use quantitative scores to obtain a total quantitative score corresponding to the system name and the name of the image file to be backed up.

[0012] In detail, the Environmental Importance Index Collection Module 4 can use image file identifiers to identify the name of the image file to be backed up. It should be noted that the image file identifier is a list of data (e.g., JSON, YAML, CSV file format) built using container images when creating different systems. Table 1 is an example of the image file name / image file identifier corresponding to the system name "System01".

[0013] Table 1 System Name System01 System Identification Code System01.sha256: 009e0a6b0841b66f87b66efba916ae4d4cb210affb5489e05f55e4605ac24e5f serial number Image file name Image file identification code 1 Docker Image01 sha256:4b01f0a8aca4684770b9674f33779e9a26597cdf6f5d1b26d78bb8fd79154239 2 Docker Image02 sha256:0513a773830246eb5bdc54dcb821273e7e6d20869c909ffad3a4815026a92b2f 3 Docker Image03 sha256:b3f73d3dee5a9d27e8d9f86d2ebe7526dd52bee81681cf613aa7ad705a1d823d 4 Docker Image04 sha256:d9f0a55cdd7d2d2ba55075520465eff364fa280e6ecd08bfc69b2331a7035135 5 Docker Image05 sha256:295cbd00c69f0c7a225e8393d6d198aed7b101bb84cf71122b237a8c23dab310 6 Docker Image06 sha256:7ab61710da1bce2d1a8fe7f531b6318f595592987b066e1c34e55374d551e6e8 7 Docker Image07 sha256:a1049ed1d3bb46239be33af720b0e025596ffff5421ddf723f32a834995751e8 8 Docker Image08 sha256:dfb424b5ff77335d8d04adeed9a51522ac9d808dcbe38b267fa988fd991f35e2 9 Docker Image09 sha256:d9fe7141996bc8f932575e0ad7d4eb9dbdff2fa116ac204698cd8e014ffd749d

[0014] In one embodiment, the quantization score may include a first quantization score, a second quantization score, and a third quantization score, wherein the system name may correspond to a system identification code.

[0015] In one embodiment, Business Keyness Indicator Unit 5.4 can obtain a first quantitative score using financial impact, user impact, dependent systems, transaction volume and processing volume, and operating costs corresponding to the system identifier. For example, Business Keyness Indicator Unit 5.4 can be composed of data in formats including JSON, YAML, and CSV. Table 2 is an example of Business Keyness Indicator Unit 5.4.

[0016] Table 2 System Name System01 System Identification Code System01.sha256: 009e0a6b0841b66f87b66efba916ae4d4cb210affb5489e05f55e4605ac24e5f serial number Sub-project Specific indicator values / descriptions First Quantitative Score 1 Financial impact System01 processes X New Taiwan Dollars in transactions per minute. A system outage of Y hours would result in a loss of Z New Taiwan Dollars. 0-1.0 2 User impact System01 supports X active users. If the system malfunctions, it will affect at least Y aspects of the user experience, including order processing delays and interruptions to user data query functions. 0-1.0 3 Dependency System System01 is the company's main platform, supporting internal service activities. Other internal systems also rely on System01 to complete data processing and reporting. 0-1.0 4 Transaction volume and processing volume System01 processes X transactions per second, with peak transaction volume increasing by Y%. 0-1.0 5 Operating costs System01's monthly operating cost is multiplied by New Taiwan Dollars; any disruption would incur significant recovery costs. 0-1.0

[0017] In one embodiment, the service availability metric unit 5.5 may obtain a second quantitative score using availability targets (SLA), mean time to repair (MTTR), mean time between failures (MTBF), recovery point objective (RPO) / recovery time objective (RTO), and fault impact extent corresponding to the system identifier. For example, the service availability metric unit 5.5 may use data in formats including JSON, YAML, and CSV files. Table 3 shows an example of the service availability metric unit 5.5.

[0018] Table 3 System Name System01 System Identification Code System01.sha256: 009e0a6b0841b66f87b66efba916ae4d4cb210affb5489e05f55e4605ac24e5f serial number Sub-project Specific indicator values / descriptions Second Quantitative Score 1 Availability Goals (SLA) System01 has an SLA of 99.99%, allowing for a maximum of X minutes of downtime per year. 0-1.0 2 Mean Time To Repair (MTTR) System01 has an average repair time of X minutes and features a fast recovery mechanism. 0-1.0 3 Mean Time Between Failures (MTBF) System01 has a mean time between failures (MTBF) of X days, demonstrating the system's high stability. 0-1.0 4 RPO / RTO System01 has an RPO of 5 minutes and an RTO of X minutes to ensure minimal data loss after a system failure and rapid recovery. 0-1.0 5 Scope of Fault A System01 malfunction may affect users in Taiwan and the operation of related systems. 0-1.0

[0019] In one embodiment, the compliance and security indicator unit 5.6 can obtain a third quantitative score using compliance requirements, data sensitivity, security threats, access control and auditing, and encryption requirements corresponding to the system identifier. For example, the compliance and security indicator unit 5.6 can use data correspondences including JSON, YAML, and CSV file formats. Table 4 is an example of the compliance and security indicator unit 5.6.

[0020] Table 4 System Name System01 System Identification Code System01.sha256: 009e0a6b0841b66f87b66efba916ae4d4cb210affb5489e05f55e4605ac24e5f serial number Sub-project Specific indicator values / descriptions Third Quantitative Score 1 Compliance requirements System01 involves personal data protection laws and must ensure the compliant processing of customer personal data. 0-1.0 2 Data sensitivity System01 processes users' personal data and has extremely high requirements for data sensitivity; any leakage could lead to significant compliance risks. 0-1.0 3 Security threats System01 is highly vulnerable to cyberattacks, having a history of data breaches and DDoS attacks, and requires advanced security measures. 0-1.0 4 Access control and auditing System01 uses multi-factor authentication (MFA) and has a complete log auditing system to track all management operations, ensuring security and compliance. 0-1.0 5 Encryption requirements System01 performs in-transmission and static encryption on all data to ensure that sensitive data is not exposed. 0-1.0

[0021] In one embodiment, the environmental and resource importance assessment module 5 can use a first quantitative score, a second quantitative score, and a third quantitative score to obtain a totalized quantitative score corresponding to the system name and the name of the image file to be backed up. For example, the environmental and resource importance assessment module 5 can perform a weighted average calculation on the first quantitative score, the second quantitative score, and the third quantitative score to obtain the totalized quantitative score. Then, the linking data management unit 5.3 can link the image file identification code and the totalized quantitative score of the image file to be backed up, and the linking data management unit 5.3 can input the image file identification code and the totalized quantitative score of the image file to be backed up to the dynamic decision-making automatic backup execution module 7.

[0022] Please refer to Figure 5. In step S504, the dynamic decision-making automatic backup execution module 7 can use the aggregated score to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up.

[0023] In one embodiment, the decision analysis and quantification calculation unit 7.1 can perform decision analysis and quantification calculation operations on the totalized quantitative score to obtain the totalized quantitative score after the decision analysis and quantification calculation operations. For example, suppose... The system is Each system has a weighted average index score. If image file 'a' exists in some systems, then the weighted average index scores of those systems will be included in the averaging calculation. Assume this... Each system has an image file 'a' containing system variables. This indicates whether image file 'a' exists in the system. When 'a' exists in the system hour, On the other hand, when 'a' does not exist in the system... hour, Since 'a' must exist in one or more... In the middle, the decision analysis and quantitative calculation unit 7.1 can be implemented through formulas. To calculate the total quantitative score after decision analysis and quantitative calculation operations. .

[0024] In one embodiment, the custom cloud environment backup operation function 6 may include local machine backup, regional multi-host backup, hybrid cloud off-site backup, and full cloud incremental backup. Specifically, the custom cloud environment backup operation function 6 may be in JSON, YAML, or CSV file format. Table 5 provides examples of the custom cloud environment backup operation function 6.

[0025] Table 5 serial number Sub-project Detailed backup description The range of totalized fractions 1 Ground-end original machine backup Perform backups on a local server or storage device to ensure fast data access and recovery. 0.1-0.25 2 Regional multi-host backup Perform backups on multiple hosts within the same region to improve availability and disaster recovery capabilities. 0.25-0.5 3 Hybrid cloud off-site backup Backups can be performed using a combination of local and cloud resources for flexibility and redundancy. 0.5-0.75 4 Full cloud incremental backup Data backup relies on cloud service providers, facilitating expansion and selectable differential backups. 0.75-1.0

[0026] Then, the image file backup selection unit 7.2 can use the aggregated quantitative score after decision analysis and quantitative calculation to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up from the custom cloud environment backup operation functions 6. Specifically, the image file backup selection unit 7.2 can select the target cloud environment backup operation function based on the aggregated quantitative score (from Table 5) to complete the dynamic decision-making automatic backup execution for each image file backup action. Then, the linked data management unit 7.3 can output the target cloud environment backup operation function to the distributed container image file backup module 9.

[0027] Please refer to Figure 5. In step S505, the linked data management unit 7.3 can determine whether the data conforms to the format of the linked data management unit 7.3. If the linked data management unit 7.3 determines that the data does not conform to the format of the linked data management unit 7.3 (the determination result of step S505 is "no"), then the process can return to step S501.

[0028] Figure 6 is another operational example of the device for backing up image files based on dynamic decision-making shown in Figure 1. Please refer to Figures 1, 3, 4, and 6 simultaneously.

[0029] In step S601, the dynamic decision automatic backup execution module 7 can use the aggregated quantitative score to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up.

[0030] In step S602, the dynamic decision automatic backup execution module 7 can use the target Web API to perform distributed backup operations on the image file to be backed up to obtain the image file backup result, wherein the target Web API corresponds to the target cloud environment backup operation function, and the image file to be backed up corresponds to the name of the image file to be backed up.

[0031] In one embodiment, the distributed container image file manifest module 8 may include a Web API. Specifically, the distributed container image file manifest module 8 may be a regional, local, or remote Web API provided by a cloud service provider. For example, the distributed container image file manifest module 8 may be:

[0032] Amazon Web Services (AWS) provides Amazon Elastic Container Registry (ECR), a fully managed Docker image registry service that supports image backup and management.

[0033] The Azure Container Registry (ACR) provided by Microsoft Azure is a registration service that allows users to store and manage Docker image files, and provides backup and security controls.

[0034] Google Cloud Platform (GCP) provides Google Container Registry (GCR), a fully managed Docker image registry service that supports efficient image backup and management.

[0035] Table 6 is an example of distributed container image file manifest module 8.

[0036] Table 6 Web API Categories serial number Web API Examples Detailed description of Web API Docker Registry API 1 docker tag docker-image xxx-cloud / project / docker-image:tag Data in the image file Docker Registry API 2 docker push xxx-cloud / project / docker-image:tag Uploaded image file data Cloud Client Library API 1 curl -H "Authorization: Bearer $(xxx-cloud auth print-access-token)" \ "https: / / xxx-cloud / v2 / project / images" List image files Cloud Client Library API 2 curl -H "Authorization: Bearer $(xxx-cloud auth print-access-token)" \ "https: / / xxx-cloud / v2 / project / image-name / manifests / tag" Get detailed information about the image file

[0037] In one embodiment, the distributed container image backup execution unit 9.3 can utilize the target cloud environment backup operation function to select a target Web API from the Web APIs. For example, if the target cloud environment backup operation function is "Local Site Backup" as shown in Table 5, then the target Web API can be "Docker Registry API" as shown in Table 6. As another example, if the target cloud environment backup operation function is "Hybrid Cloud Off-site Backup" as shown in Table 5, then the target Web API can be both "Docker Registry API" and "Cloud Client Library API" as shown in Table 6.

[0038] Then, the dynamic decision-making automatic backup execution module 7 and the distributed container image file backup module 9 can use the target Web API to perform distributed backup operations on the image file to be backed up to obtain the image file backup result. Next, the distributed container image file backup module 9 can transmit the image file backup result to the security and image file integrity verification module 10.

[0039] In step S603, the security and image file integrity verification module 10 can perform backup result verification operations on the image file backup result and the image file to be backed up. Specifically, the security and image file integrity verification module 10 can obtain detailed information about the image file backup result through API number 2 in the "Cloud Client Library API" shown in Table 6, and compare it with the original image file. More specifically, the security and image file integrity verification module 10 can perform security and integrity verification using the following comparison methods. First, to check and compare the hash code, the security and image file integrity verification module 10 can use a secure hash code algorithm such as SHA-256 to calculate the hash code of the original image file and the image file backup result. The hash code of the original image file is calculated during backup, and then the hash code is calculated and compared again during recovery or backup inspection to ensure the integrity of the image file. Furthermore, the security and image file integrity verification module 10 can perform vulnerability checks on the image file backup result based on container security checks using container security scanning tools (such as Clair, Trivy) to ensure that it is identical to the original image file and does not contain any known security vulnerabilities. Finally, the security and image file integrity verification module 10 can build response data based on the user interface 1.

[0040] In step S604, the security and image file integrity verification module 10 can determine whether the response data has been successfully built.

[0041] If the security and image file integrity verification module 10 determines that the response data has been successfully built (the determination result of step S604 is "yes"), then in step S605, the security and image file integrity verification module 10 can transmit the image file to be backed up and the image file backup result to the user interface 1.

[0042] Figure 7 is a flowchart illustrating a method for backing up image files based on dynamic decision-making according to an embodiment of the present invention, wherein the method can be implemented by the apparatus for backing up image files based on dynamic decision-making shown in Figure 1. In step S71, the system name corresponding to the name of the image file to be backed up is obtained using interpretive data. In step S72, a quantized score corresponding to the system name and the name of the image file to be backed up is obtained using a quantized score. In step S73, the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up is selected using the quantized score. In step S74, a distributed backup operation is performed on the image file to be backed up using a target Web API to obtain the image file backup result, wherein the target Web API corresponds to the target cloud environment backup operation function, and the image file to be backed up corresponds to the name of the image file to be backed up. The method has been described in the foregoing embodiments and will not be repeated here.

[0043] In summary, the apparatus and method for backing up image files based on dynamic decision-making of the present invention can select the target cloud environment backup operation function after obtaining the system name corresponding to the name of the image file to be backed up, and perform a distributed backup operation on the image file to be backed up. That is, the present invention can dynamically determine the backup method of an image file based on the importance of the system executing the backup of a specific image file; for example, it can perform image file backup based on a hybrid cloud off-site backup architecture. Therefore, the present invention can improve the resource utilization efficiency of the system and ensure that important business services are adequately protected.

[0044] 1: User Interface 2: Response Module 3: Image File Resource Collection Module 4: Environmental Importance Indicator Collection Module 5: Environmental and Resource Importance Assessment Module 5.1: Image File Conversion Unit 5.2: Image File Data Management Unit 5.3: Linked Data Management Unit 5.4: Key Business Indicators Unit 5.5: Service Availability Metrics Unit 5.6: Compliance and Security Indicators Unit 6: Customizable cloud environment backup operation function 7: Dynamic Decision-Making Automatic Backup Execution Module 7.1: Decision Analysis and Quantitative Calculation Unit 7.2: Image File Backup Selection Unit 7.3: Link Data Management Unit 8: Distributed Container Image File List Module 9: Distributed container image backup module 9.1: Backup Decision Link Management Unit 9.2: Distributed Container Image File Selection Unit 9.3: Distributed Container Image Backup Execution Unit 10: Security and Image File Integrity Verification Module 10 S501~S505, S601~S605, S71~S74: Steps

Claims

1. An apparatus for backing up image files based on dynamic decision-making, comprising: Environmental importance indicator collection module; Environmental and resource importance assessment module; The device includes a dynamic decision-making automatic backup execution module, wherein the environmental importance index collection module uses interpretive data to obtain the system name corresponding to the name of the image file to be backed up; the environmental and resource importance assessment module uses quantitative scores to obtain a totalized quantitative score corresponding to the system name and the name of the image file to be backed up; the dynamic decision-making automatic backup execution module uses the totalized quantitative score to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up; the dynamic decision-making automatic backup execution module uses a target Web API to perform distributed backup operations on the image file to be backed up to obtain the image file backup result, wherein the target Web API corresponds to the target cloud environment backup operation function, wherein the image file to be backed up corresponds to the name of the image file to be backed up, and the device further includes an image file resource collection module, wherein the image file resource collection module uses the name of the image file to be backed up to obtain the interpretive data, wherein the interpretive data includes Tag Name, Create Time, Image Audit Log, Image Digest, and Vulnerability Scan Report.

2. The apparatus as described in claim 1 further includes a user interface, wherein the user interface receives the name of the image file to be backed up.

3. The apparatus as claimed in claim 2 further includes a response module, wherein the response module receives the name of the image file to be backed up from the user interface.

4. The apparatus as described in claim 1, wherein the environmental and resource importance assessment module includes a business criticality indicator unit, a service availability indicator unit, and a compliance and security indicator unit, wherein the quantified scores include a first quantified score, a second quantified score, and a third quantified score, wherein the system name corresponds to a system identification code, wherein the business criticality indicator unit obtains the first quantified score using financial impact, user impact, dependent systems, transaction volume and processing volume, and operating costs corresponding to the system identification code; the service availability indicator unit obtains the second quantified score using availability targets (SLA), mean time to repair (MTTR), mean time between failures (MTBF), recovery point objective (RPO) / recovery time objective (RTO), and fault impact range corresponding to the system identification code; and the compliance and security indicator unit obtains the third quantified score using compliance requirements, data sensitivity, security threats, access control and auditing, and encryption requirements corresponding to the system identification code.

5. The apparatus of claim 4, wherein the environment and resource importance assessment module uses the first quantization score, the second quantization score, and the third quantization score to obtain the aggregated quantization score corresponding to the system name and the name of the image file to be backed up.

6. The apparatus as described in claim 1 further includes a customized cloud environment backup operation function, wherein the dynamic decision-making automatic backup execution module includes a decision analysis and quantification calculation unit and an image file backup selection unit, wherein the decision analysis and quantification calculation unit performs decision analysis and quantification calculation operations on the totalized quantification score to obtain the totalized quantification score after the decision analysis and quantification calculation operations; and the image file backup selection unit uses the totalized quantification score after the decision analysis and quantification calculation operations to select the target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up from the customized cloud environment backup operation functions.

7. The apparatus as described in claim 6, wherein the custom cloud environment backup operation function includes local machine backup, regional multi-host backup, hybrid cloud off-site backup, and full cloud incremental backup.

8. The apparatus as claimed in claim 1, further comprising a distributed container image file inventory module and a distributed container image file backup module, wherein the distributed container image file inventory module includes a Web API, and the distributed container image file backup module includes a distributed container image file backup execution unit, wherein the distributed container image file backup execution unit uses the target cloud environment backup operation function to select the target Web API from the Web APIs; the dynamic decision automatic backup execution module and the distributed container image file backup module use the target Web API to perform the distributed backup operation on the image file to be backed up to obtain the image file backup result.

9. The apparatus of claim 1 further includes a security and image file integrity verification module, wherein the security and image file integrity verification module performs a backup result verification operation on the image file backup result and the image file to be backed up.

10. A method for backing up image files based on dynamic decision-making, suitable for an apparatus including an environmental importance index collection module, an environmental and resource importance assessment module, and a dynamic decision-making automatic backup execution module, wherein the method includes the following steps: the environmental importance index collection module uses interpretive data to obtain a system name corresponding to the name of the image file to be backed up; the environmental and resource importance assessment module uses quantitative scores to obtain a totalized quantitative score corresponding to the system name and the name of the image file to be backed up; the dynamic decision-making automatic backup execution module uses the totalized quantitative score to select a target cloud environment backup operation function corresponding to the system name and the name of the image file to be backed up; and the dynamic decision-making automatic backup execution module uses a target Web API to perform a distributed backup operation on the image file to be backed up to obtain an image file backup result, wherein the target Web API corresponds to a target cloud environment backup operation function, and the image file to be backed up corresponds to the name of the image file to be backed up, wherein the apparatus further includes an image file resource collection module, and the method further includes the following steps: the image file resource collection module uses the name of the image file to be backed up to obtain the interpretive data, wherein the interpretive data includes Tag Name, Create Time, Image Audit Log, and Image File Identifier (Image). Digest) and vulnerability scan report.

Images