Container resource maintenance method and device, equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a container resource maintenance method and device, equipment and a medium, and the method comprises the steps: obtaining a verified resource template deployed in a container arrangement cluster of a target container, and calling a cluster interface to verify the operation state of the target container in the verified resource template; if the running state is a normal running state, determining a resource file corresponding to the target container as a first context input file and determining a preset modification resource file as a second context input file; performing template matching and difference generation on the first context input file and the second context input file to obtain a modification configuration result; and performing format legality verification on the modification configuration result, storing the resource file and the modification configuration result as a deployable file after the verification is passed, and maintaining the resource file of the target container. The method can be applied to a financial science and technology and medical care service program system, the resource maintenance efficiency can be improved, and the risk of manual intervention is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, and in particular to a container resource maintenance method, device, equipment and medium. BACKGROUND

[0002] With the rapid development of financial technology and smart medical and pension industry, the system architecture gradually evolves towards cloud native and microservices, and container orchestration technology has become the core infrastructure supporting high concurrency, sensitive data processing and high availability service deployment. The traditional maintenance method of container resources highly depends on manual operation, which is difficult to meet the challenges of complex resource structure, multiple version coexistence, modification risk and the like under multi-business cluster, especially when batch configuration adjustment is performed, syntax errors or logical conflicts are likely to occur, affecting the stability of core business operation.

[0003] Although the current industry has introduced container automated deployment tools, intelligent processing capabilities are still lacking in specific maintenance links, especially in complex configuration modification and version comparison. In addition, a large number of resource configuration files use structured markup languages, which require high requirements for operation and maintenance personnel and have a high error rate, leading to the interruption of financial risk control systems or medical image services due to configuration errors. Therefore, there is an urgent need for a container resource maintenance method that combines the inference ability of local large models and the linkage of cluster interfaces, which can improve maintenance efficiency and reduce the risk of manual intervention while ensuring configuration compliance and structural safety. SUMMARY

[0004] The present application provides a container resource maintenance method, device, equipment and medium to solve the technical problem of low maintenance efficiency and the need for more manual intervention in related technologies.

[0005] In a first aspect, a container resource maintenance method is provided, which includes:

[0006] An already verified resource template deployed in a container orchestration cluster where a target container is located is obtained, and a cluster interface is called to verify the running state of the target container in the already verified resource template;

[0007] If the running state is a normal running state, a resource file corresponding to the target container is determined as a first context input file, and a preset modified resource file is determined as a second context input file;

[0008] A large model is used to perform template matching and difference generation on the first context input file and the second context input file to obtain a modified configuration result; wherein the modified configuration result includes structure adjustment information, image migration information and parameter repair information;

[0009] The modification configuration result is verified for format legality through a preset interface, and the resource file corresponding to the target container and the modification configuration result are saved as a deployable file after verification, so as to maintain the resource file of the target container.

[0010] In a second aspect, a container resource maintenance apparatus is provided, comprising:

[0011] An acquisition module is configured to acquire a verified resource template deployed in a container orchestration cluster where a target container is located, and call a cluster interface to check a running state of the target container in the verified resource template.

[0012] A determination module is configured to determine a resource file corresponding to the target container as a first context input file and a preset modification resource file as a second context input file if the running state is a normal running state.

[0013] An analysis module is configured to perform template matching and difference generation on the first context input file and the second context input file through a large model to obtain a modification configuration result, wherein the modification configuration result comprises structure adjustment information, image migration information and parameter repair information.

[0014] A resource maintenance module is configured to verify the modification configuration result for format legality through a preset interface, and save the resource file corresponding to the target container and the modification configuration result as a deployable file after verification, so as to maintain the resource file of the target container.

[0015] In a third aspect, a computer device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above container resource maintenance method when executing the computer program.

[0016] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program, and the computer program implements the steps of the above container resource maintenance method when executed by a processor.

[0017] The scheme implemented by the container resource maintenance method, device, computer equipment and storage medium includes: obtaining a verified resource template deployed in a container orchestration cluster where a target container is located, and calling a cluster interface to check a running state of the target container in the verified resource template; if the running state is a normal running state, determining a resource file corresponding to the target container as a first context input file, and determining a preset modified resource file as a second context input file; performing template matching and difference generation on the first context input file and the second context input file by a large model to obtain a modification configuration result; wherein the modification configuration result includes structure adjustment information, image migration information and parameter repair information; performing format legality verification on the modification configuration result by a preset interface, and saving the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, so as to maintain the resource file of the target container. In the present application, by introducing the verified resource template and checking the running state of the target container in real time, it is ensured that the subsequent maintenance operation is only carried out on the premise that the system is stable and the container is normal, and service interruption or configuration error caused by operation in an abnormal state is avoided. On this basis, the large model is used to deeply analyze and template match the existing resource file and the preset modified file, which can accurately identify the differences in structure change, image migration and parameter repair, so as to generate detailed and reasonable modification configuration results. In addition, after the modification configuration result is generated, the format legality verification is performed by the preset interface, which effectively avoids the risks of configuration file syntax error or deployment incompatibility, and ensures that the finally generated deployable file has good stability and adaptability. The whole process realizes the closed-loop management of resource file from state perception, difference identification, configuration modification to deployment landing while ensuring high accuracy, and is especially suitable for key scenarios such as financial systems and medical and health care systems which have high requirements for system continuity and configuration security, and provides a more intelligent, safe and controllable maintenance method for resource configuration. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0019] Figure 1 is an application environment diagram of the container resource maintenance method in an embodiment of the present application;

[0020] Figure 2 is a flow diagram of the container resource maintenance method in an embodiment of the present application;

[0021] Figure 3 is Figure 2 a specific implementation flowchart of step S10 in the embodiment;

[0022] Figure 4 is a structural schematic diagram of a container resource maintenance device in an embodiment of the present application;

[0023] Figure 5 is a structural schematic diagram of a computer device in an embodiment of the present application;

[0024] Figure 6 is another structural schematic diagram of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are 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 work fall within the protection scope of the present application.

[0026] The container resource maintenance method provided by the embodiments of the present application can be applied to, for example, Figure 1In an application environment of the application, the client communicates with the server through a network. The server can obtain a verified resource template deployed in a container orchestration cluster where a target container is located through the client, and call a cluster interface to check a running state of the target container in the verified resource template; if the running state is a normal running state, a resource file corresponding to the target container is determined as a first context input file, and a preset modified resource file is determined as a second context input file; a large model is used to perform template matching and difference generation on the first context input file and the second context input file, to obtain a modification configuration result; the modification configuration result includes structure adjustment information, image migration information and parameter repair information; a preset interface is used to perform format legality verification on the modification configuration result, and after the verification is passed, the resource file corresponding to the target container and the modification configuration result are saved as a deployable file, so as to maintain the resource file of the target container, and the deployable file is fed back to the client. In the application, the running state of the target container is checked in real time by introducing the verified resource template, so that the subsequent maintenance operation is ensured to be performed only under the premise that the system is stable and the container is normal, and service interruption or configuration errors caused by operation in an abnormal state are avoided. On this basis, the large model is used to perform deep analysis and template matching on the existing resource file and the preset modified file, so that multi-dimensional differences such as structure change, image migration and parameter repair can be accurately identified, and detailed and reasonable modification configuration results can be generated. In addition, after the modification configuration result is generated, the format legality verification is performed through the preset interface, so that the risks such as configuration file syntax error or deployment incompatibility are effectively avoided, and the finally generated deployable file has good stability and adaptability. The overall process realizes closed-loop management of resource file from state perception, difference identification, configuration modification to deployment landing while ensuring high accuracy, and is especially suitable for key scenarios such as financial systems and medical and health care systems which have high requirements for system continuity and configuration security, and provides a more intelligent, safe and controllable maintenance method for resource configuration. The client can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers. The application will be described in detail through specific embodiments.

[0027] Referring to Figure 2 , it is shown that Figure 2 A flowchart of a container resource maintenance method provided by an embodiment of the application is shown. The method includes the following steps:

[0028] S10: Obtain a verified resource template deployed in a container orchestration cluster where a target container is located, and call a cluster interface to check a running state of the target container in the verified resource template.

[0029] For example, in step S10, by accessing the container orchestration cluster to which the target container belongs, a verified resource template can be obtained first to ensure the reliability and consistency of the template used. Subsequently, the interface provided by the cluster is called to verify the current running status of the target container in the template, thereby determining whether the container is in a normal running state.

[0030] The aforementioned technical methods not only confirm the validity of resource templates, but also ensure that maintenance operations are performed under the premise of stable container operation, which helps to reduce the risk of configuration conflicts or service interruptions. They are particularly suitable for scenarios in the medical and financial fields that are highly sensitive to system stability.

[0031] Among them, such as Figure 3 As shown, step S10, which involves calling the cluster interface to verify the running status of the target container in the verified resource template, includes the following steps:

[0032] S11: Send a status query request to the container orchestration cluster through the cluster interface to extract the current running information of the target container; wherein, the current running information includes the number of restarts and fault logs.

[0033] S12: Parse the current running information and verify whether the target container is in a normal running state based on the parsing result.

[0034] For example, in step S11, a status query request can be initiated to the container orchestration cluster via the cluster interface to dynamically extract the current running information of the target container. This running information typically includes the number of restarts since the container started and detailed fault logs, used to comprehensively reflect the container's operational stability and potential abnormal behavior. This real-time data acquisition method ensures that subsequent maintenance operations are based on the latest running status, which is particularly suitable for financial transaction systems or medical diagnostic service platforms with strict requirements for service stability.

[0035] Furthermore, in step S12, the acquired operational information can be structured and parsed. For example, it can be analyzed whether the number of restarts exceeds a preset threshold, whether the fault log contains key error keywords, etc., and based on this, it can be determined whether the target container is currently in a normal operating state. If the parsing result shows that the container is running normally, subsequent resource configuration and maintenance can be safely performed; if an anomaly is found, the system can stop the maintenance process or issue an early warning to avoid introducing further risks.

[0036] This data-driven state verification mechanism helps improve the intelligence level and risk control capabilities of container resource management, and ensures the continuous and stable operation of financial account systems or telemedicine services.

[0037] In some embodiments, the verifying whether the running state of the target container is in the normal running state based on the analysis result comprises: if the analysis result shows that the target container is in the ready state and continuously runs for more than a preset time threshold, determining that the running state of the target container is in the normal running state; and if the analysis result shows that the target container is not in the ready state and / or the continuous running time is not more than the preset time threshold, determining that the running state of the target container is in an abnormal running state.

[0038] For example, in order to more accurately evaluate the running state of the target container, not only basic information such as fault logs and restart times can be relied on, but also the ready state and continuous running time can be introduced as core judgment basis. The ready state is used to indicate whether the container has completed initialization and can stably provide services to the outside, and the continuous running time is used to judge whether the container has continuously and stably run for more than a set time threshold without interruption. If the analysis result shows that the container is in the ready state and its running time has been stable for more than the threshold, it can be reasonably judged that the current running state of the container is normal and has the premise of continuing to perform maintenance operations.

[0039] On the contrary, if it is found after analysis that the container is not in the ready state, for example, it is still initializing, is frequently restarted, or although it is ready, the running time does not reach the set standard, it means that the container may have potential faults or is not stable. In this case, the running state is determined to be an abnormal state, which helps the system to stop the current maintenance operation and prevent introducing new configuration changes when the container is not stable, thereby reducing the risk of the system. This mechanism based on cross verification of multiple conditions is particularly suitable for application in scenarios such as financial risk control engines and remote diagnosis backends, which have very high requirements for high availability and continuous stability.

[0040] S20: If the running state is a normal running state, determining the resource file corresponding to the target container as a first context input file, and determining a preset modified resource file as a second context input file.

[0041] For example, in step S20, when it is confirmed that the target container is in a normal running state, the configuration maintenance preparation phase is entered. First, the actual resource file currently corresponding to the container is extracted and defined as a first context input file, which is used as a basic configuration reference. At the same time, a preset modified resource file can be called as a second context input file, which is used to express the target intention of adjusting the existing configuration. By separating the existing state and the preset modification and explicitly defining them as two context input files, a data foundation is laid for subsequent large model difference analysis and template matching, which helps to accurately generate a configuration modification scheme with reasonable structure and controllable risk, and is particularly suitable for scenarios in medical and financial systems where configuration changes need to be highly traceable and auditable.

[0042] S30: performing template matching and difference generation on the first context input file and the second context input file by a large model to obtain a modification configuration result; wherein the modification configuration result comprises structure adjustment information, image migration information, and parameter repair information.

[0043] In some embodiments, the performing template matching and difference generation on the first context input file and the second context input file by a large model to obtain a modification configuration result comprises: respectively analyzing first structure information in the first context input file and second structure information in the second context input file based on a preset prompt word template by the large model; comparing the first structure information and the second structure information by the large model to obtain a difference field; and sequentially performing structure filling and value replacement on the difference field to obtain the modification configuration result.

[0044] For example, in step S30, a large model can be introduced to deeply analyze the first context input file (i.e., the current resource file) and the second context input file (i.e., the preset modification file), and generate a modification configuration result through template matching and difference identification. Specifically, the structure information in the two context files can be analyzed respectively by using the prompt word template built in the large model, and the corresponding first structure information and second structure information can be extracted. This processing method not only improves the semantic understanding ability of analysis, but also accurately identifies complex fields involved in container configuration, such as service port, storage volume mounting path, image version, etc., providing a high-quality data basis for subsequent difference comparison.

[0045] Further, the large model can finely compare the two types of structure information extracted, identify the difference field, and perform structure filling and value replacement according to these fields. For example, if it is found that a parameter value is inconsistent or an image version has migrated, structure adjustment information, image migration information, and parameter repair information, etc. can be generated accordingly, and finally a complete modification configuration result is formed.

[0046] The above processing process realizes intelligent response and automatic generation of container configuration modification requirements, and is especially suitable for application scenarios in the financial and medical and health care fields where configuration changes frequently but reliability and explainability are highly required. Through the participation of the large model, not only the operation and maintenance efficiency is improved, but also the probability of human operation error is greatly reduced.

[0047] S40: verifying the format legality of the modification configuration result through a preset interface, and saving the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, so as to maintain the resource file of the target container.

[0048] In some embodiments, the format legality verification of the modified configuration result is performed through the preset interface, and the resource file corresponding to the target container and the modified configuration result are saved as a deployable file after the verification is passed, including: performing syntax scanning on each field in the modified configuration result through the preset interface to obtain a syntax scanning result; if the syntax scanning result shows that the syntax is correct, performing structure matching checking on the modified configuration result to obtain a checking result; if the checking result is no error, it is determined that the modified configuration result is verified, and the resource file corresponding to the target container and the modified configuration result are saved as the deployable file.

[0049] For example, in step S40, in order to ensure that the generated modified configuration result can be deployed safely and correctly parsed by the container orchestration system, the format legality verification of the configuration result can be performed through the preset interface. First, syntax scanning can be performed on each field in the modified configuration result to check whether there is a spelling error, a missing symbol, an illegal format, and the like, so as to ensure that all fields meet the container configuration syntax specification. This process can be automatically performed with the help of regular expressions, configuration language parsers and the like, effectively avoiding the situation that the deployment fails due to syntax errors, and is particularly suitable for application in financial core processing platforms and remote medical instruction scheduling systems with low system fault tolerance requirements.

[0050] After the syntax verification is passed, structure matching checking can be further performed, that is, it is confirmed whether the configuration structure level is complete, the field nesting relationship is correct, and the key dependent items are missing, so as to ensure that the entire configuration file is logically clear and structurally reasonable. If the structure checking result shows no error, it is determined that the modified configuration result is verified, and then it is saved together with the resource file of the target container as a deployable file. This file will become the configuration basis used in formal deployment, marking the completion of the resource maintenance operation.

[0051] The above double verification mechanism not only improves the system security, but also enhances the auditability and traceability of the configuration version, greatly meeting the actual needs of key industries such as finance and medical and health care for high reliability and high stability configuration delivery.

[0052] In some embodiments, the method further includes: after the modified configuration result is generated, annotating the modified configuration result according to a business type to obtain an annotation result; wherein the annotation result includes a financial resource or a medical resource; generating a corresponding difference description file based on the annotation result and a preset audit template, and performing pre-audit processing on the difference description file to obtain a pre-audit result; if the pre-audit result is pre-audit passed, applying the modified configuration result to the target container for gray release.

[0053] For example, to achieve fine management of container resource modification in different business scenarios, the configuration result can be intelligently annotated according to the business type after being generated. By analyzing the resource name, the service module to which it belongs, and the calling interface characteristics, it can be determined whether the modification belongs to financial resources or medical resources, and the corresponding annotation result can be generated accordingly. Subsequently, combined with the annotation result and the corresponding preset audit template, a difference description file is automatically generated, which lists the fields of the modification content, the change direction, and its impact range in the current business in detail, providing a basis for subsequent compliance review and manual intervention, especially suitable for application scenarios with strict requirements for financial compliance audit or medical data governance.

[0054] Further, after the difference description file is generated, it can also be submitted to the audit module for pre-audit processing, mainly to verify whether the modification content meets the industry standards, safety policies, and data integrity requirements. For example, in the financial industry, it may involve preventing data leakage and compliance risk configuration restrictions, and in the medical field, it may include patient privacy protection and treatment plan consistency verification. If the pre-audit result shows that the configuration modification meets the requirements, the modification configuration result can be deployed to the target container in a gray mode for gradual verification and observation, avoiding system instability caused by one-time changes. This scheme of introducing business type annotation and pre-audit mechanism not only improves the safety and compliance of configuration changes, but also makes configuration maintenance more in line with the specific regulatory requirements of key industries.

[0055] In some embodiments, the method further comprises: identifying deployment instances in the container orchestration cluster, and constructing a task list of resources to be modified based on the deployment instances; determining the modification priority of the task list according to the update frequency of the resource configuration, and modifying the deployment instances based on the modification priority to obtain a modified resource configuration file.

[0056] For example, to improve the systematicness and execution efficiency of resource configuration maintenance, all deployment instances in the container orchestration cluster can be identified first, and based on the resource configuration differences existing in these instances, a clear task list of resources to be modified can be constructed. This task list not only lists the specific resource items that need to be modified, but also associates the running state, configuration version, and business module of each instance, facilitating orderly progress in the actual modification process. Such a mechanism is particularly suitable for medical resource scheduling clusters or financial distributed ledger systems, where the number of deployment instances is large and the resource configuration is highly heterogeneous. Without clear task planning, it will be easy to cause management confusion and configuration conflicts.

[0057] Furthermore, by combining historical configuration change records with current resource usage frequency, the update frequency of each configuration item in the task list can be statistically analyzed, and modification priorities can be assigned accordingly. For example, frequently changing resource items such as dynamic image paths or high-concurrency interface parameters will be given higher priority, while infrequently updated static configurations will be processed later. After determining the priorities, modification operations can be performed on each deployment instance in sequence, ultimately generating a modified resource configuration file.

[0058] The above methods not only optimize the execution path of resource maintenance, but also enhance the ability to respond quickly to configuration peaks, making them particularly suitable for application in financial transaction matching systems or remote medical clusters where the continuity of critical business operations is critical.

[0059] As can be seen, the above solution, by introducing verified resource templates and verifying the running status of the target container in real time, ensures that subsequent maintenance operations are only performed under the premise that the system is stable and the container is normal, avoiding service interruptions or configuration errors caused by operations under abnormal conditions. Based on this, a large model is used to perform in-depth analysis and template matching of existing resource files and preset modification files, accurately identifying differences in multiple dimensions such as structural changes, image migration, and parameter repair, thereby generating detailed and reasonable modified configuration results. Furthermore, after generating the modified configuration results, the solution performs format validity verification through a preset interface, effectively avoiding risks such as configuration file syntax errors or deployment incompatibility, ensuring that the final deployable file has good stability and adaptability. The overall process, while ensuring high accuracy, achieves closed-loop management of resource files from status awareness, difference identification, configuration modification to deployment, making it particularly suitable for critical scenarios with extremely high requirements for system continuity and configuration security, such as financial systems and healthcare / elderly care, providing a more intelligent, secure, and controllable maintenance method for resource configuration.

[0060] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0061] In one embodiment, a container resource maintenance device is provided, which corresponds one-to-one with the container resource maintenance methods described in the above embodiments. For example... Figure 4 As shown, the container resource maintenance device includes an acquisition module 101, a determination module 102, an analysis module 103, and a resource maintenance module 104. Detailed descriptions of each functional module are as follows:

[0062] The acquisition module 101 is used to acquire the verified resource template deployed in the container orchestration cluster where the target container is located, and call the cluster interface to verify the running status of the target container in the verified resource template;

[0063] The determining module 102 is configured to determine the resource file corresponding to the target container as a first context input file and determine a preset modified resource file as a second context input file if the running state is a normal running state.

[0064] The analysis module 103 is configured to perform template matching and difference generation on the first context input file and the second context input file through a large model to obtain a modification configuration result, wherein the modification configuration result includes structure adjustment information, image migration information and parameter repair information.

[0065] The resource maintenance module 104 is configured to perform format legality verification on the modification configuration result through a preset interface, and save the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, so as to maintain the resource file of the target container.

[0066] The obtaining module 101 is configured to send a state query request to the container orchestration cluster through the cluster interface, and extract the current running information of the target container, wherein the current running information includes the number of restarts and the fault log; analyze the current running information, and verify whether the running state of the target container is in a normal running state based on the analysis result.

[0067] The determining module 102 is configured to determine that the running state of the target container is in the normal running state if the analysis result shows that the target container is in a ready state and continuously runs for more than a preset time threshold; and determine that the running state of the target container is in an abnormal running state if the analysis result shows that the target container is not in a ready state and / or the continuous running time is not more than a preset time threshold.

[0068] The analysis module 103 is configured to analyze first structure information in the first context input file and second structure information in the second context input file based on a preset prompt word template through the large model; compare the first structure information and the second structure information through the large model to obtain a difference field; and sequentially perform structure filling and value replacement on the difference field to obtain the modification configuration result.

[0069] The resource maintenance module 104 is configured to perform syntax scanning on each field in the modification configuration result through the preset interface to obtain a syntax scanning result; perform structure matching checking on the modification configuration result to obtain a checking result if the syntax scanning result shows that the syntax is correct; determine that the modification configuration result passes the verification if the checking result is correct, and save the resource file corresponding to the target container and the modification configuration result as the deployable file.

[0070] In an embodiment, the resource maintenance module 104 is further configured to: obtain a training data set and a pre-trained model; wherein the training data set comprises a plurality of agricultural sample image data; label the training data set to obtain a labeling result, wherein the labeling result comprises disaster feature labels corresponding to the agricultural sample image data; and train the pre-trained model based on the training data set and the labeling result to obtain the image recognition model.

[0071] In an embodiment, the resource maintenance module 104 is further configured to: after generating the modified configuration result, label the modified configuration result according to a business type to obtain a labeling result; wherein the labeling result comprises financial resources or medical resources; generate a difference description file corresponding to the labeling result based on a preset audit template, and perform pre-audit processing on the difference description file to obtain a pre-audit result; and if the pre-audit result is pre-audit passed, apply the modified configuration result to the target container for gray release.

[0072] In an embodiment, the resource maintenance module 104 is configured to identify a deployment instance in the container orchestration cluster, and construct a task list of resources to be modified based on the deployment instance; determine a modification priority of the task list according to an update frequency of resource configuration, and modify the deployment instance based on the modification priority to obtain a modified resource configuration file.

[0073] The present application provides a container resource maintenance device, which introduces a verified resource template and real-time checks the running state of the target container to ensure that subsequent maintenance operations are only performed under the premise that the system is stable and the container is normal, avoiding service interruption or configuration errors caused by abnormal state operations. On this basis, the existing resource file and the preset modification file are analyzed and matched using a large model, which can accurately identify multi-dimensional differences such as structural changes, image migration, and parameter repair, thereby generating detailed and reasonable modification configuration results. In addition, the scheme verifies the format legality of the generated modification configuration result through a preset interface, effectively avoiding configuration file syntax errors or deployment incompatibility risks, ensuring that the finally generated deployable file has good stability and adaptability. The overall process ensures high accuracy while realizing closed-loop management of resource files from state perception, difference identification, configuration modification to deployment landing, and is particularly suitable for key scenarios such as financial systems and medical and health care systems that require high system continuity and configuration security, providing a more intelligent, safe, and controllable maintenance method for resource configuration.

[0074] The specific limitation of the container resource maintenance apparatus can refer to the limitation of the container resource maintenance method, which will not be repeated here. Each module in the container resource maintenance apparatus can be realized by software, hardware, and a combination thereof, in whole or in part. Each module can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so that the processor can call and execute the operation corresponding to each module.

[0075] In one embodiment, a computer device is provided, which can be a server, and an internal structure diagram thereof can be as shown in Figure 5 The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is configured to communicate with an external client through a network connection. The computer program is executed by the processor to implement the functions or steps of the container resource maintenance method on the server side.

[0076] In one embodiment, a computer device is provided, which can be a client, and an internal structure diagram thereof can be as shown in Figure 6 The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is configured to communicate with an external server through a network connection. The computer program is executed by the processor to implement the functions or steps of the container resource maintenance method on the client side

[0077] In one embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the following steps:

[0078] An already-verified resource template deployed in a container orchestration cluster where the target container is located is obtained, and a cluster interface is called to verify the running state of the target container in the already-verified resource template;

[0079] If the running state is a normal running state, the resource file corresponding to the target container is determined as a first context input file, and a preset modified resource file is determined as a second context input file;

[0080] The first context input file and the second context input file are subjected to template matching and difference generation by a large model to obtain a modification configuration result; wherein the modification configuration result includes structure adjustment information, image migration information, and parameter repair information;

[0081] The modification configuration result is subjected to format legality verification through a preset interface, and after verification, the resource file corresponding to the target container and the modification configuration result are saved as a deployable file to maintain the resource file of the target container.

[0082] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0083] An already verified resource template deployed in a container orchestration cluster where a target container is located is acquired, and a cluster interface is called to check a running state of the target container in the already verified resource template;

[0084] If the running state is a normal running state, the resource file corresponding to the target container is determined as a first context input file, and a preset modified resource file is determined as a second context input file;

[0085] The first context input file and the second context input file are subjected to template matching and difference generation by a large model to obtain a modification configuration result; wherein the modification configuration result includes structure adjustment information, image migration information, and parameter repair information;

[0086] The modification configuration result is subjected to format legality verification through a preset interface, and after verification, the resource file corresponding to the target container and the modification configuration result are saved as a deployable file to maintain the resource file of the target container.

[0087] It should be noted that the functions or steps that the computer readable storage medium or the computer device can implement correspond to the related descriptions of the server side and the client side in the foregoing method embodiments, and to avoid repetition, they will not be described one by one here.

[0088] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchl ink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0090] The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, but not limit it. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features. The modification or replacement does not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method of maintaining a container resource, characterized by, The method comprises: acquiring a verified resource template deployed in a container orchestration cluster where a target container is located, and calling a cluster interface to check a running state of the target container in the verified resource template; if the running state is a normal running state, determining a resource file corresponding to the target container as a first context input file, and determining a preset modified resource file as a second context input file; performing template matching and difference generation on the first context input file and the second context input file by a large model to obtain a modification configuration result; wherein the modification configuration result comprises structure adjustment information, image migration information and parameter repair information; performing format legality verification on the modification configuration result by a preset interface, and saving the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, so as to maintain the resource file of the target container.

2. The method of claim 1, wherein, The calling of the cluster interface to check the running state of the target container in the verified resource template comprises: sending a state query request to the container orchestration cluster through the cluster interface to extract current running information of the target container; wherein the current running information comprises a restart number and a fault log; analyzing the current running information, and verifying whether the running state of the target container is in a normal running state based on the analysis result.

3. The method of claim 2, wherein, The verification of whether the running state of the target container is in a normal running state based on the analysis result comprises: if the analysis result shows that the target container is in a ready state and continuously runs for more than a preset time threshold, it is determined that the running state of the target container is in the normal running state; if the analysis result shows that the target container is not in a ready state and / or continuously runs for less than a preset time threshold, it is determined that the running state of the target container is in an abnormal running state.

4. The method of claim 1, wherein, The performing of template matching and difference generation on the first context input file and the second context input file by the large model to obtain a modification configuration result comprises: analyzing first structure information in the first context input file and second structure information in the second context input file based on a preset prompt word template by the large model; comparing the first structure information and the second structure information by the large model to obtain a difference field; performing structure filling and value replacement on the difference field in sequence to obtain the modification configuration result.

5. The method of claim 1, wherein, The performing of format legality verification on the modification configuration result by the preset interface, and saving the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, comprises: performing syntax scanning on each field in the modification configuration result by the preset interface to obtain a syntax scanning result; if the syntax scanning result shows that the syntax is correct, performing structure matching inspection on the modification configuration result to obtain an inspection result; If the check result is no error, it is determined that the modification configuration result is verified, and the resource file corresponding to the target container and the modification configuration result are saved as the deployable file.

6. The method of claim 1, wherein, The method further comprises: After generating the modification configuration result, the modification configuration result is labeled according to the business type to obtain a labeled result; wherein the labeled result includes financial resources or medical resources; Based on the labeled result and a preset audit template, a corresponding difference description file is generated, and the difference description file is pre-audited to obtain a pre-audit result; If the pre-audit result is pre-audit passed, the modification configuration result is applied to the target container for gray release.

7. The method of claim 1, wherein, The method further comprises: A deployment instance in the container orchestration cluster is identified, and a task list of resources to be modified is constructed based on the deployment instance; The modification priority of the task list is determined according to the update frequency of the resource configuration, and the deployment instance is modified based on the modification priority to obtain a modified resource configuration file.

8. A container resource maintenance apparatus characterized by comprising: The container resource maintenance device comprises: An acquisition module is configured to acquire a verified resource template deployed in a container orchestration cluster where a target container is located, and call a cluster interface to check a running state of the target container in the verified resource template; A determination module is configured to determine that a resource file corresponding to the target container is a first context input file if the running state is a normal running state, and determine that a preset modification resource file is a second context input file; An analysis module is configured to perform template matching and difference generation on the first context input file and the second context input file through a large model to obtain a modification configuration result; wherein the modification configuration result includes structure adjustment information, image migration information, and parameter repair information; A resource maintenance module is configured to perform format legality verification on the modification configuration result through a preset interface, and save the resource file corresponding to the target container and the modification configuration result as a deployable file after the verification is passed, so as to maintain the resource file of the target container.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the container resource maintenance method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the steps of the container resource maintenance method according to any one of claims 1 to 7.

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