Container health detection method and device, medium and equipment

Abstract

The invention relates to the technical field of container health detection and the field of financial science and technology, and discloses a container health detection method and device, a medium and equipment, and the method comprises the steps: obtaining an api interface of a data cloud platform and each K8s cluster uuid corresponding to the data cloud platform through a detection module; health detection is carried out on each K8s cluster based on a data cloud platform api interface by using a detection module; after the detection module detects health alarm information about the data cloud platform, in response to the health alarm information, determining health alarm parameters corresponding to the health alarm information based on the self-healing platform; and matching a target solution plan corresponding to the health alarm parameter based on the self-healing platform, and repairing an alarm container corresponding to the alarm K8s cluster based on the target solution plan. According to the embodiment, by introducing an automatic container health detection and self-healing mechanism, the operation and maintenance efficiency and the service reliability in the financial science and technology field are remarkably improved, and the management complexity and the operation error risk are reduced.

Description

Technical Field

[0001] The present disclosure relates to the field of container health detection technology and the field of financial technology, and in particular to a container health detection method, device, medium and equipment. Background Art

[0002] In modern financial technology, Pod container health detection is crucial to ensure the stability and security of financial services. The popularity of cloud computing and microservice architecture has led to financial applications involving a large amount of sensitive data and high-frequency transactions, requiring real-time monitoring and efficient management of containers. The health detection mechanism can evaluate the status of containers, discover security risks and performance bottlenecks, and ensure service continuity and data security. Financial institutions often use platforms such as Kubernetes to uniformly configure and manage health detection to improve system reliability.

[0003] At present, the Pod container health detection solutions widely used in the financial technology field mainly include integrating third-party health detection tools (such as healthcheck-daemon), configuring detailed health detection parameters, and performing automated health checks. These tools allow the operation and maintenance team of financial institutions to set key parameters such as inspection cycle, detection interval, and fault tolerance according to business needs to achieve refined management of container health. However, there are still some shortcomings in the relevant solutions: first, the syntax and usage methods of different health detection tools vary greatly, and operation and maintenance personnel must have the skills of multiple tools, which increases the complexity of management; second, when the detection fails, there is a lack of detailed fault handling steps, and the operation and maintenance personnel may be confused, affecting the efficiency of fault response. In addition, most of the current health detection and fault handling rely on manual operations, which leads to inefficiency and prone to errors in large-scale application environments. At the same time, although Kubernetes provides a certain health detection mechanism, it is still insufficient in confirming the nature of the fault, processing health warning information, and remote fault location, resulting in a slow fault recovery process. Summary of the invention

[0004] The embodiments of the present disclosure at least provide a container health detection method, device, medium and equipment, which realize unified, intelligent health detection and fault self-healing of multiple K8s clusters through an integrated detection module and a self-healing platform. The target application status can be quickly grasped without logging into the server, which significantly improves the operation and maintenance efficiency and service reliability in the financial technology field, and reduces management complexity and the risk of operational errors.

[0005] According to one aspect of the present application, a method for detecting container health is provided, the method comprising:

[0006] The detection module is used to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; and the detection module is used to perform health detection on each K8s cluster based on the API interface of the data cloud platform; wherein the data cloud platform includes multiple K8s clusters; the K8s cluster includes multiple containers; the detection module is connected to the self-healing platform;

[0007] After the detection module detects health warning information about the data cloud platform, in response to the health warning information, determining health warning parameters corresponding to the health warning information based on the self-healing platform;

[0008] Based on the self-healing platform, a target solution plan corresponding to the health alarm parameter is matched, and based on the target solution plan, an alarm container corresponding to the alarm K8s cluster is repaired.

[0009] According to another aspect of the present application, a container health detection device is provided, the device comprising:

[0010] A health detection module is used to use the detection module to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; and use the detection module to perform health detection on each K8s cluster based on the API interface of the data cloud platform; wherein the data cloud platform includes multiple K8s clusters; the K8s cluster includes multiple containers; the detection module is connected to the self-healing platform;

[0011] a parameter determination module, configured to determine, after the detection module detects health warning information about the data cloud platform, in response to the health warning information, a health warning parameter corresponding to the health warning information based on the self-healing platform;

[0012] The alarm repair module is used to match the target solution plan corresponding to the health alarm parameter based on the self-healing platform, and repair the alarm container corresponding to the alarm K8s cluster based on the target solution plan.

[0013] According to another aspect of the present application, an embodiment of the present disclosure provides a computer device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, when the computer device is running, the processor communicates with the memory through the bus, and when the machine-readable instructions are executed by the processor, the container health detection method described in any possible implementation manner described above is performed.

[0014] According to another aspect of the present application, an embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the container health detection method as described in any possible implementation manner described above is implemented.

[0015] The container health detection method, device, medium and equipment provided in the embodiments of the present invention utilize a detection module to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; and utilize the detection module to perform health detection on each K8s cluster based on the API interface of the data cloud platform; after the detection module detects health warning information about the data cloud platform, in response to the health warning information, determine the health warning parameters corresponding to the health warning information based on the self-healing platform; match the target solution plan corresponding to the health warning parameters based on the self-healing platform, and repair the alarm container corresponding to the alarm K8s cluster based on the target solution plan.

[0016] In this way, the present invention realizes unified, intelligent health detection and fault self-healing of multiple K8s clusters through an integrated detection module and self-healing platform. The target application status can be quickly grasped without logging into the server, which significantly improves the operation and maintenance efficiency and service reliability in the financial technology field, and reduces management complexity and the risk of operational errors.

[0017] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required to be cited in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A schematic diagram of an application environment of a container health detection method provided by an embodiment of the present disclosure is shown;

[0020] Figure 2 A flow chart of a container health detection method provided by an embodiment of the present disclosure is shown;

[0021] Figure 3 A schematic structural diagram of a container health detection device provided by an embodiment of the present disclosure is shown;

[0022] Figure 4 A schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0024] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0025] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0026] To facilitate understanding of this embodiment, the execution subject of the container health detection method provided by the embodiment of the present disclosure is first introduced in detail. The container health detection method provided by the embodiment of the present invention can be applied to Figure 1 In the application environment, the client communicates with the server through the network. The client can be a mobile device, a user terminal, a terminal, a handheld device, a computing device, etc. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, big data and artificial intelligence platforms.

[0027] The container health detection method provided by the embodiment of the present application is described in detail below in conjunction with the accompanying drawings. Figure 2As shown, it is a flow chart of a container health detection method provided by an embodiment of the present disclosure, and the method includes the following S201-S203:

[0028] S201, using the detection module to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; and using the detection module to perform health detection on each K8s cluster based on the API interface of the data cloud platform.

[0029] It is understandable that as a comprehensive data platform, the data cloud platform can serve enterprises, research institutions or individual users, and usually contains multiple K8s clusters, which are used to manage and run the multiple containers (i.e. containerized applications) it includes. Among them, the K8s cluster (i.e. Kubernetes cluster) is an open source container orchestration platform, which consists of a group of physical or virtual machines, which are organized into a single computing resource pool for automatically deploying, scaling and managing containerized applications; container refers to a lightweight, portable software packaging technology that can package applications and their dependencies together and deploy and run them as a separate unit, thereby ensuring the consistency and reliability of applications in different environments. Here, taking a large bank as an example, the bank uses an advanced data cloud platform to support its complex financial business system. The data cloud platform can integrate multiple K8s clusters to manage and run various containerized applications, such as trading systems, risk management modules and customer service applications.

[0030] Specifically, the present disclosure utilizes the detection module to obtain the API interface of the data cloud platform. These interfaces are provided by the data cloud platform to allow users or programs to perform data query, operation and other interactive channels. At the same time, the detection module utilizes the API interface of the data cloud platform to obtain relevant information, including the unique identifier (uuid) of each K8s cluster. Here, uuid is a standard used to ensure uniqueness worldwide, and is used here to uniquely identify each K8s cluster. After the detection module obtains the API interface of the data cloud platform and the uuid of each K8s cluster, the detection module uses the API interface of the data cloud platform to perform regular health detection on each K8s cluster to check the status of the cluster, including the health status of the container.

[0031] Exemplarily, the self-healing platform is used to identify and automatically repair health warning problems in the K8s cluster of the data cloud platform. The self-healing platform has built-in multiple warning resolution plans, which are usually automated repair steps based on past experience and best practices. Each plan is designed for different types of warning parameters, which may include rescheduling containers, increasing resource quotas, restarting containers, modifying configurations, and other operations. Here, the detection module is connected to the self-healing platform to ensure that the health status of the Kubernetes (K8s) cluster in the data cloud platform is monitored and repaired in a timely manner.

[0032] In some other embodiments, the detection module can also be used as a separate atom, not connected to the self-healing platform. In this case, the detection module can still play the basic function of health detection, providing operation and maintenance personnel with real-time monitoring information on the health status of the cluster, helping them to discover and solve potential problems in a timely manner. This flexibility allows the detection module to adapt to data cloud platform environments of different scales and complexities.

[0033] S202, after the detection module detects health warning information about the data cloud platform, in response to the health warning information, determine health warning parameters corresponding to the health warning information based on the self-healing platform.

[0034] It is understandable that when the detection module finds that the health status of the K8s cluster is abnormal during the detection process, the detection module will transmit the generated health warning information to the self-healing platform, and the self-healing platform will determine the health warning parameters corresponding to the information based on the received health warning information. Here, the health warning information includes the uuid of the alarm K8s cluster, that is, after the self-healing platform receives the health warning information, it will identify the specific container with the problem based on the uuid of the K8s cluster contained in the health warning information.

[0035] Specifically, when using the self-healing platform to determine the health alarm parameters corresponding to the health alarm information, the self-healing platform will first determine the alarm cluster through the uuid, and then the self-healing platform will query all containers in the alarm cluster to obtain the operating status information of each container, including whether it is running normally, crashed, overloaded, etc. Through this query, the self-healing platform can clearly identify which containers have problems, so as to accurately locate the alarm container. After the self-healing platform locates the alarm container, it will confirm the health alarm parameters related to it according to the alarm information, such as the alarm type, alarm level, affected container or cluster node, etc.

[0036] In the disclosed embodiment, the detection module promptly detects health anomalies and transmits alarm information to the self-healing platform. The self-healing platform can use the uuid in the alarm information to accurately identify the K8s cluster and specific container where the problem is located, and then query and analyze the running status information of the container, accurately locate the alarm container and its related health alarm parameters. In this way, not only the accuracy and efficiency of problem diagnosis are improved, but also it is ensured that the subsequent self-healing platform can take appropriate treatment measures for specific problems, effectively maintaining the stability and reliability of the K8s cluster.

[0037] Exemplarily, after the self-healing platform determines the alarm container and the health alarm parameters corresponding to the alarm container, if the health alarm parameters corresponding to the alarm container indicate that the alarm type of the alarm container is a restart alarm, it means that the container may automatically restart or need to be restarted to restore its normal operation state for some reason. At this time, the self-healing platform will query and record the historical status information of the alarm container, which includes but is not limited to the number of restarts, the restart interval, the resource usage before and after the restart (such as CPU, memory occupancy), and possible error logs. Based on the historical status information, the self-healing platform will evaluate whether the current restart alarm belongs to the occasional restart type, for example: the self-healing platform may analyze whether the number of restarts of the container in the past period of time is far below the set threshold, such as no more than three times a month; or, determine whether the restart interval is relatively long, whether there is a frequent continuous restart trend; or, the self-healing platform can also check the resource usage before and after the restart, such as whether the CPU and memory occupancy have returned to normal, and whether there is a continuous high load phenomenon; or, by checking the error log, analyze whether there are known and self-repairable temporary problems, such as occasional network jitter or slight resource contention. In this way, through analysis, the self-healing platform can evaluate whether the current restart alarm belongs to the type of sporadic restart. Here, sporadic restart usually refers to non-continuous, low-frequency restart events caused by temporary resource contention, network fluctuations, or minor configuration errors. Such events can often be resolved by themselves in a short time without additional manual or automated intervention.

[0038] It is understandable that if, based on the evaluation of historical status information, the restart behavior of the alarm container meets the characteristics of an occasional restart, that is, it occurs occasionally, is not continuous, and can recover by itself, then the self-healing platform will determine that the current restart alarm is an occasional restart type, and decide to end the further processing process of the current health alarm information accordingly.

[0039] In the present disclosure, the alarm container and its health alarm parameters are identified, combined with historical status analysis to determine whether the restart alarm is an occasional type, and the handling process is ended after confirming that it is an occasional restart type, thereby effectively avoiding unnecessary intervention, improving the accuracy and efficiency of system self-healing, optimizing resource utilization, and enhancing the stability of the container environment and the intelligent level of operation and maintenance.

[0040] S203, matching a target solution plan corresponding to the health alarm parameter based on the self-healing platform, and repairing an alarm container corresponding to the alarm K8s cluster based on the target solution plan.

[0041] It is understandable that health warning parameters may also include abnormal conditions of performance indicators such as CPU, memory, and network of the container or error status of the application in the container. After the self-healing platform determines the warning container and the health warning parameters corresponding to the warning container, the self-healing platform will compare the current health warning parameters with the preset solution plan to obtain a suitable repair strategy (i.e., the target solution plan) to effectively solve the current health problem.

[0042] At this time, after the self-healing platform matches the target solution plan corresponding to the health alarm parameters, the self-healing platform can send the health alarm parameters and the target solution plan to the operation platform. Here, the operation platform, as an interactive interface for operation and maintenance personnel, can further confirm and feedback the alarm parameters and plans. Among them, the operation platform can be an internal public account or applet, through which operation and maintenance personnel can view specific alarm parameters, solution plans and other details that need attention, and provide feedback information based on the judgment of the operation and maintenance personnel themselves. The feedback information may include whether to agree to execute the plan, whether the plan strategy needs to be adjusted, or whether other potential problems are found.

[0043] Specifically, after the self-healing platform receives the feedback plan from the operating platform, if the feedback confirms that the target solution plan can solve the current problem and there is no need for further adjustment, the self-healing platform will start the corresponding repair operation according to the execution order of the multiple solution processes included in the target solution plan. Here, the execution order corresponding to the multiple solution processes can be fixed or flexibly adjusted according to different situations to improve the repair efficiency and success rate. For example: first expand resources and then restart the container, or first restart the application container and then expand resources to repair the alarm container.

[0044] In this disclosure, through the intelligent matching of solution plans by the self-healing platform and the interactive design between the self-healing platform and the operating platform, the operation and maintenance personnel can quickly and accurately know the overall operating status of the target application without logging into the server, and then automatically execute the repair process to ensure that the problem of the alarm container in the K8s cluster is solved in a timely and effective manner.

[0045] In some other embodiments, there may also be a situation where the target solution plan corresponding to the health alarm parameters is not matched in the self-healing platform. At this time, the self-healing platform will send the matching failure information and the health alarm parameters to the operating platform, and request the operation and maintenance personnel to provide feedback solutions. The operation and maintenance personnel formulate a repair plan based on professional knowledge and experience and the alarm details, and submit it through the operating platform. After receiving the feedback solution, the self-healing platform will repair the alarm container according to the execution order corresponding to the multiple feedback solution processes in the solution. Among them, the feedback solution includes multiple feedback solution processes, and the execution order corresponding to the multiple feedback solution processes includes multiple sorting schemes.

[0046] In addition, the self-healing platform also has the ability to self-learn and optimize, and can continuously optimize its early warning and repair strategies based on actual operating conditions and feedback to improve the stability and reliability of the system. Therefore, after the self-healing platform receives the feedback solution, it will also add this solution as a solution corresponding to the health alarm parameter to the self-healing platform's solution library, so that similar problems can be automatically matched and quickly resolved in the future.

[0047] In the disclosed embodiment, by introducing a feedback mechanism for operation and maintenance personnel and the self-learning optimization capability of the self-healing platform, it is ensured that repair plans can be effectively formulated and executed when faced with unmatched warnings. At the same time, solutions are accumulated to optimize future warning and repair efficiency, thereby comprehensively improving system stability and reliability.

[0048] It is understandable that after the alarm container corresponding to the alarm K8s cluster is repaired, the detection module is used to re-detect the health of the alarm K8s cluster according to the repair result to determine whether the alarm has been successfully lifted. In the case of determining that the alarm is lifted, based on the detection module according to the health alarm parameters corresponding to the alarm container, the abnormal log of the alarm container and the historical status of the alarm container are queried on the data cloud platform, and the historical behavior and abnormal information of the alarm container are deeply analyzed. Among them, the abnormal log records the abnormal events that occur during the operation of the container, and the historical status reflects the complete state transition process of the container from creation to the current moment. After obtaining the abnormal log and historical status information, the fault knowledge base is used to analyze the cause of the fault. Here, the fault knowledge base is a database that integrates a large number of known fault modes, causes and solutions. By matching the abnormal log and historical status of the alarm container with the information in the knowledge base, the most likely cause of the fault can be identified.

[0049] In this disclosure, after completing the repair of the alarm container in the alarm K8s cluster, the alarm is lifted by re-detection, and the data cloud platform is used to query the abnormal logs and historical status for in-depth analysis. Then, with the help of the integrated fault knowledge base, the cause of the fault is quickly identified, which effectively improves the system stability and troubleshooting efficiency.

[0050] In order to deeply understand the solution proposed in this disclosure, the following is an example in the financial field. The IT department of a financial enterprise uses a special detection module to obtain the unique identifier (uuid) of all K8s clusters it manages with the help of the API interface of the data cloud platform. Each K8s cluster contains multiple containers that run specific business logic and carries various financial applications and services such as trading systems and risk control platforms. The detection module is closely connected to the self-healing platform to monitor the health status of each K8s cluster in real time. One day, the detection module captured a health alarm message sent by a K8s cluster through the data cloud platform, which contained the uuid of the alarm cluster. The self-healing platform responded quickly, located the alarm K8s cluster according to the alarm cluster uuid in the health alarm message, and checked the container status in the cluster one by one, and finally determined one or more alarm containers and their health alarm parameters (such as high CPU usage, memory leak, etc.). If the alarm type is a restart alarm, the self-healing platform will query the historical status of the alarm container to determine whether the restart is sporadic. Sporadic restarts may be caused by short-term network fluctuations or resource contention, and the self-healing platform will choose to continue monitoring without taking action. Non-incidental alarms trigger the self-healing platform to match the target solution plan. In complex situations, if the self-healing platform cannot match the target solution plan, it will send the matching failure information and alarm parameters to the manual operation platform, and the operation and maintenance team will provide a solution and add it to the plan library of the self-healing platform. Once the repair plan is determined, whether it is automatically matched or provided manually, the self-healing platform will obtain feedback from the operation platform and repair the alarm container according to the process specified by the solution (which may include different execution orders), and flexibly adjust the process order according to actual conditions to ensure efficiency. After the repair, the detection module detects the health status of the alarm container again to verify the repair effect. After the alarm is lifted, the self-healing platform uses the detection module to obtain the abnormal log and historical status information of the alarm container from the data cloud platform, and sends it to the fault knowledge base for intelligent analysis to determine the root cause of the fault, which is crucial to preventing similar faults in the future and optimizing the stability and performance of financial applications.

[0051] The container health detection method, device, medium and equipment provided in the embodiments of the present disclosure use the detection module to obtain the API interface of the data cloud platform and the UUID of each K8s cluster corresponding to the data cloud platform; and use the detection module to perform health detection on each K8s cluster based on the API interface of the data cloud platform; after the detection module detects the health warning information about the data cloud platform, in response to the health warning information, the health warning parameters corresponding to the health warning information are determined based on the self-healing platform; the target solution plan corresponding to the health warning parameters is matched based on the self-healing platform, and the alarm container corresponding to the alarm K8s cluster is repaired based on the target solution plan. In this way, the present disclosure realizes unified, intelligent health detection and fault self-healing of multiple K8s clusters through the integrated detection module and the self-healing platform, and the target application status can be quickly grasped without logging into the server, which significantly improves the operation and maintenance efficiency and service reliability in the financial technology field, and reduces the management complexity and the risk of operational errors.

[0052] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0053] Based on the same inventive concept, the embodiment of the present disclosure also provides a container health detection device corresponding to the container health detection method. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the above-mentioned container health detection method in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0054] Reference Figure 3 FIG. 1 is a schematic diagram of a container health detection device 300 provided in an embodiment of the present disclosure, wherein the device comprises:

[0055] The health detection module 301 is used to use the detection module to obtain the API interface of the data cloud platform and the uuid of each K8s cluster corresponding to the data cloud platform; and use the detection module to perform health detection on each K8s cluster based on the API interface of the data cloud platform; wherein the data cloud platform includes multiple K8s clusters; the K8s cluster includes multiple containers; the detection module is connected to the self-healing platform;

[0056] A parameter determination module 302, configured to determine a health warning parameter corresponding to the health warning information based on the self-healing platform in response to the health warning information after the detection module detects the health warning information about the data cloud platform;

[0057] The alarm repair module 303 is used to match the target solution plan corresponding to the health alarm parameter based on the self-healing platform, and repair the alarm container corresponding to the alarm K8s cluster based on the target solution plan.

[0058] In some possible embodiments, the health warning information includes the uuid of the warning K8s cluster; the parameter determination module 302 is specifically used to:

[0059] Based on the self-healing platform, the alarm cluster is determined according to the uuid of the alarm K8s cluster; and the container status corresponding to each container in the alarm K8s cluster is queried using the self-healing platform, and the alarm container and the health alarm parameters corresponding to the alarm container are determined based on the query results.

[0060] In some possible embodiments, the parameter determination module 302 is further configured to:

[0061] In a case where the health alarm parameter corresponding to the alarm container indicates that the alarm type of the alarm container is a restart alarm, querying the historical state of the alarm container, and judging whether the restart type corresponding to the restart alarm is an occasional restart type based on the historical state;

[0062] When the restart type corresponding to the restart alarm is an accidental restart type, the processing flow of the health alarm information is terminated.

[0063] In some possible embodiments, the alarm repair module 303 is further used to:

[0064] Sending the health warning parameters and the target solution plan to an operation platform, and obtaining a feedback plan based on the operation platform;

[0065] The alarm container corresponding to the alarm K8s cluster is repaired based on the target solution and the feedback solution.

[0066] In some possible embodiments, the alarm repair module 303 is further used to:

[0067] In the case that the self-healing platform fails to match the target solution corresponding to the health warning parameter, the matching failure information and the health warning parameter are sent to the operation platform, and a feedback solution is obtained based on the operation platform;

[0068] Based on the feedback solution, the alarm container corresponding to the alarm K8s cluster is repaired; and the feedback solution corresponding to the health alarm parameter is added to the self-healing platform.

[0069] In some possible embodiments, the target solution plan includes multiple solution processes, and the alarm repair module 303 is specifically used to:

[0070] In the case where the feedback scheme indicates that the alarm container corresponding to the alarm K8s cluster is to be repaired based on the target solution plan, the alarm container corresponding to the alarm K8s cluster is repaired based on the execution order corresponding to the multiple solution processes; wherein the execution order corresponding to the multiple solution processes includes multiple sorting schemes;

[0071] The feedback solution includes multiple feedback solution processes, and the alarm repair module 303 is specifically used to:

[0072] The alarm container corresponding to the alarm K8s cluster is repaired based on the execution order corresponding to the multiple feedback solution processes; wherein the execution order corresponding to the multiple feedback solution processes includes multiple sorting schemes.

[0073] In some possible embodiments, the alarm repair module 303 is further used to:

[0074] According to the repair result, based on the detection module, a health detection is performed again on the repaired alarm container to determine whether the alarm is cleared;

[0075] When it is determined that the alarm is lifted, querying the abnormal log of the alarm container and the historical status of the alarm container on the data cloud platform based on the detection module and the health alarm parameters corresponding to the alarm container;

[0076] According to the fault knowledge base, the cause of the fault is determined based on the abnormal log and the historical status.

[0077] Based on the same technical concept, the embodiment of the present disclosure also provides a computer device. Figure 4 4 is a schematic diagram of the structure of a computer device 400 provided in an embodiment of the present disclosure, including a processor 401, a memory 402, and a bus 403. The memory 402 is used to store execution instructions, including a memory 4021 and an external memory 4022; the memory 4021 is also called an internal memory, which is used to temporarily store the operation data in the processor 401 and the data exchanged with the external memory 4022 such as a hard disk. The processor 401 exchanges data with the external memory 4022 through the memory 4021.

[0078] In the embodiment of the present application, the memory 402 is specifically used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. That is, when the computer device 400 is running, the processor 401 communicates with the memory 402 through the bus 403, so that the processor 401 executes the application code stored in the memory 402, and then executes the method described in any of the above embodiments.

[0079] Among them, the memory 402 can be, but is not limited to, random access memory (Random Access Memory, RAM), read only memory (Read Only Memory, ROM), programmable read-only memory (Programmable Read-Only Memory, PROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable read-only memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

[0080] Processor 401 may be an integrated circuit chip with signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present invention may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0081] It is to be understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the computer device 400. In other embodiments of the present application, the computer device 400 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0082] The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the container health detection method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0083] The embodiments of the present disclosure also provide a computer program product, which carries a program code. The instructions included in the program code can be used to execute the steps of the container health detection method described in the above method embodiment. For details, please refer to the above method embodiment, which will not be repeated here.

[0084] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is implemented as a computer storage medium. In another optional embodiment, the computer program product is implemented as a software product, such as a software development kit (SDK).

[0085] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0088] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0089] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A container health detection method, characterized in that: include: Use the detection module to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; The detection module is used to perform health detection on each K8s cluster based on the data cloud platform API interface; wherein the data cloud platform includes multiple K8s clusters; the K8s cluster includes multiple containers; the detection module is connected to the self-healing platform; After the detection module detects health warning information about the data cloud platform, in response to the health warning information, determining health warning parameters corresponding to the health warning information based on the self-healing platform; Based on the self-healing platform, a target solution plan corresponding to the health alarm parameter is matched, and based on the target solution plan, an alarm container corresponding to the alarm K8s cluster is repaired.

2. The method according to claim 1, characterized in that The health warning information includes the uuid of the warning K8s cluster; The determining, based on the self-healing platform, a health warning parameter corresponding to the health warning information includes: Determine the alarm cluster based on the self-healing platform according to the uuid of the alarm K8s cluster; The self-healing platform is used to query the container status corresponding to each container in the alarm K8s cluster, and the alarm container and the health alarm parameters corresponding to the alarm container are determined based on the query result.

3. The method according to claim 2, characterized in that After determining the alarm container and the health alarm parameter corresponding to the alarm container based on the query result, the method further includes: In a case where the health alarm parameter corresponding to the alarm container indicates that the alarm type of the alarm container is a restart alarm, querying the historical state of the alarm container, and judging whether the restart type corresponding to the restart alarm is an occasional restart type based on the historical state; When the restart type corresponding to the restart alarm is an accidental restart type, the processing flow of the health alarm information is terminated.

4. The method according to claim 1, characterized in that: After the target solution plan corresponding to the health warning parameter is matched based on the self-healing platform, the method includes: Sending the health warning parameters and the target solution plan to an operation platform, and obtaining a feedback plan based on the operation platform; The alarm container corresponding to the alarm K8s cluster is repaired based on the target solution and the feedback solution.

5. The method according to claim 4, characterized in that The target solution plan based on matching the self-healing platform with the health warning parameter also includes: In the case that the self-healing platform fails to match the target solution corresponding to the health warning parameter, the matching failure information and the health warning parameter are sent to the operation platform, and a feedback solution is obtained based on the operation platform; Based on the feedback solution, the alarm container corresponding to the alarm K8s cluster is repaired; and the feedback solution corresponding to the health alarm parameter is added to the self-healing platform.

6. The method according to claim 5, characterized in that The target solution plan includes multiple solution processes, and the repairing of the alarm container corresponding to the alarm K8s cluster based on the target solution plan and the feedback solution includes: In the case where the feedback scheme indicates that the alarm container corresponding to the alarm K8s cluster is to be repaired based on the target solution plan, the alarm container corresponding to the alarm K8s cluster is repaired based on the execution order corresponding to the multiple solution processes; wherein the execution order corresponding to the multiple solution processes includes multiple sorting schemes; The feedback solution includes multiple feedback resolution processes, and the repairing of the alarm container corresponding to the alarm K8s cluster based on the feedback solution includes: The alarm container corresponding to the alarm K8s cluster is repaired based on the execution order corresponding to the multiple feedback solution processes; wherein the execution order corresponding to the multiple feedback solution processes includes multiple sorting schemes.

7. The method according to any one of claims 1 to 6, characterized in that After repairing the alarm container corresponding to the alarm K8s cluster based on the target solution plan, it includes: According to the repair result, based on the detection module, a health detection is performed again on the repaired alarm container to determine whether the alarm is cleared; When it is determined that the alarm is lifted, querying the abnormal log of the alarm container and the historical status of the alarm container on the data cloud platform based on the detection module and the health alarm parameters corresponding to the alarm container; According to the fault knowledge base, the cause of the fault is determined based on the abnormal log and the historical status.

8. A container health detection device, characterized in that: include: A health detection module is used to use the detection module to obtain the API interface of the data cloud platform and the uuids of each K8s cluster corresponding to the data cloud platform; The detection module is used to perform health detection on each K8s cluster based on the data cloud platform API interface; wherein the data cloud platform includes multiple K8s clusters; the K8s cluster includes multiple containers; the detection module is connected to the self-healing platform; a parameter determination module, configured to determine, after the detection module detects health warning information about the data cloud platform, in response to the health warning information, a health warning parameter corresponding to the health warning information based on the self-healing platform; The alarm repair module is used to match the target solution plan corresponding to the health alarm parameter based on the self-healing platform, and repair the alarm container corresponding to the alarm K8s cluster based on the target solution plan.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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