Intent-based server management method, device, medium and product

Abstract

The present invention discloses an intent-based server management method, device, medium and product, and relates to the field of servers. The method includes: receiving server management intent information sent by an administrator; determining target performance data of a business server according to the server management intent information; generating a server management policy based on the target performance data; adjusting the resource configuration, application configuration and / or service tasks of the business server according to the server management policy; obtaining the real-time performance data of the adjusted business server; when the real-time performance data matches the target performance data, returning server management task completion information to the administrator. The present invention automatically adjusts the server configuration to meet performance requirements by accurately matching the administrator's management intent with the target performance data, thereby reducing the difficulty of server management, and confirming the completion of the task to the administrator after the performance reaches the standard, thereby improving the efficiency and accuracy of server management.

Description

Technical Field

[0001] The present invention relates to the field of server technology, and in particular to an intent-based server management method, device, medium and product. Background Art

[0002] With the rapid development of information technology, servers play a core role in enterprise operations and various Internet services, and the complexity and importance of their management are becoming increasingly prominent.

[0003] In the traditional server management model, the normal operation of business servers is mainly maintained by administrator configuration and rule-based policies. This approach has many limitations. On the one hand, in the face of increasingly diverse and dynamically changing business needs, administrators need to have deep professional knowledge and rich experience to accurately configure server resources, optimize application settings, and respond to various emergencies. For example, during e-commerce promotions, server load will increase sharply. Traditional management methods are difficult to quickly and accurately adjust resource allocation to meet the sudden burst of business needs, resulting in slow website response or even paralysis, causing huge economic losses to the company. On the other hand, the manual configuration process is cumbersome and error-prone. Once improperly configured, it may trigger a series of chain reactions, affecting the stability and reliability of the server, increasing the risk of system failure, and thus causing business interruption.

[0004] Therefore, the current server management method is difficult, and the management efficiency and accuracy are low. Summary of the invention

[0005] In view of the above-mentioned technical problems and defects, the purpose of the present invention is to provide an intent-based server management method, device, medium and product, which automatically adjusts the server configuration to meet the performance requirements by accurately matching the administrator's management intent with the target performance data, thereby reducing the difficulty of server management and confirming the completion of the task to the administrator after the performance meets the standards, thereby improving the efficiency and accuracy of server management.

[0006] To achieve the above-mentioned objectives, in a first aspect, the present invention provides an intent-based server management method, comprising: receiving server management intent information sent by an administrator; determining target performance data of a business server based on the server management intent information; generating a server management policy based on the target performance data; adjusting the resource configuration, application configuration and / or service tasks of the business server according to the server management policy; obtaining real-time performance data of the adjusted business server; and returning server management task completion information to the administrator when the real-time performance data matches the target performance data.

[0007] The present invention improves the efficiency and accuracy of server management by receiving server management intention information from the administrator, automatically determining the target performance data of the business server, and generating corresponding management policies. This method not only reduces errors and omissions in manual configuration and reduces the difficulty of service completion management, but also speeds up the response time through automated processes, so that the business server can adapt to changes in business needs more quickly. Through intelligent resource configuration and performance adjustment, this method optimizes resource utilization, reduces energy waste, and reduces operating costs.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of determining the target performance data of the business server based on the server management intent information includes: comparing the server management intent information with the template intent information in the intent information library to obtain semantic similarity; when the semantic similarity is greater than or equal to a set threshold, determining the server performance data corresponding to the template intent information as the target performance data.

[0009] By adopting the technical solution of the above embodiment, an efficient and intelligent method for determining target performance data is provided. By semantically comparing the administrator's management intent with the template intent information in the intent information library, the system can automatically identify the preset performance data that matches the administrator's intent, thereby reducing the workload of manually setting target performance data and reducing target setting errors caused by human factors, thereby improving the accuracy and response speed of server management. This method makes server management more flexible, can quickly adapt to different management needs and business scenarios, and enhances the adaptability and user-friendliness of the system.

[0010] In combination with some embodiments of the first aspect, in some embodiments, when the semantic similarity is greater than or equal to a set threshold, the step of determining the server performance data corresponding to the template intent information as the target performance data includes: when there are multiple template intent information whose semantic similarities are greater than or equal to the set threshold, determining the template intent information with the greatest semantic similarity as the target template intent information; and determining the server performance data corresponding to the target template intent information as the target performance data.

[0011] By adopting the technical solution of the above embodiment, the most matching server performance data can be accurately selected as the target performance data. When there are multiple template intent information and the semantic similarity of the administrator's management intent exceeds the set threshold, the system selects the most matching template intent information by comparing the similarity, thereby ensuring the accuracy and relevance of the target performance data. This method improves the accuracy of the target performance data, making the generated management policy more in line with the administrator's actual intention, thereby improving the quality and efficiency of server management.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the real-time performance data of the business server after adjustment, it also includes: when the real-time performance data does not match the target performance data, determining the abnormal problem of the business server based on a preset performance indicator rule base and the real-time performance data; and generating a problem solution based on the abnormal problem.

[0013] The technical solution of the above embodiment is adopted to enhance the system's exception handling capability. After obtaining the adjusted real-time performance data, the system determines the abnormal problems of the business server based on the preset performance indicator rule base and real-time performance data, and generates a problem solution. The system can promptly detect and respond to performance deviations, reducing the risk of service interruption or performance degradation caused by performance problems. This method improves the system's adaptability and reliability, ensures business continuity and service level, and is of great significance for maintaining business stability and user satisfaction.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the step of generating a server management policy based on the target performance data includes: determining the current resource status of the business server; and generating the server management policy based on the target performance data and the current resource status.

[0015] The technical solution of the above embodiment provides a method for generating a server management strategy that comprehensively considers the target performance data and the current resource status. The system not only considers the target performance requirements, but also combines the actual resource status of the server to generate a more reasonable and effective management strategy. This method makes the management strategy more practical, improves the executability and effectiveness of the strategy, ensures the rational use of server resources and performance optimization, and plays an important role in improving server operating efficiency and reducing operation and maintenance costs.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of generating a server management policy based on the target performance data, it also includes: storing the server management policy in a system cache; when other server management intention information with the same semantics is received, retrieving the server management policy from the system cache.

[0017] The technical solution of the above embodiment is adopted to improve the reusability and response speed of the server management policy. By storing the generated management policy in the system cache, when receiving other server management intention information with the same semantics, the system can directly retrieve the corresponding management policy from the cache, avoiding the process of repeatedly generating policies. This method not only improves processing efficiency and reduces the consumption of system resources, but also improves the user experience, allowing the system to quickly respond to similar management needs and enhance the flexibility and practicality of the system.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining the real-time performance data of the business server after adjustment, it also includes: determining the degree of deviation between the real-time performance data and the target performance data; when the degree of deviation exceeds a set range, generating a rollback instruction; sending the rollback instruction to the business server to roll back the business server to the state before the adjustment.

[0019] The technical solution of the above embodiment provides an effective performance guarantee and rollback mechanism. After obtaining the adjusted real-time performance data, the degree of deviation between the real-time performance data and the target performance data is determined, and a rollback instruction is generated when the degree of deviation exceeds the set range. The system can promptly correct configuration adjustments that do not meet expectations and reduce performance problems caused by configuration errors. This method enhances the stability and reliability of the system, protects the normal operation of the business server, and is of great significance for maintaining business continuity and data integrity.

[0020] In a second aspect, an embodiment of the present invention provides an electronic device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation method of the first aspect or the second aspect.

[0021] In a third aspect, the present invention provides a computer-readable storage medium comprising instructions, which, when executed on the electronic device, causes the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation of the first aspect or the second aspect.

[0022] In a fourth aspect, the present invention provides a computer program product comprising instructions, which, when the computer program product is run on the electronic device, enables the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation of the first aspect or the second aspect.

[0023] It is understandable that the electronic device provided in the second aspect, the storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the method provided in the present invention. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0025] 1. Automated and intelligent server management: The present invention realizes intelligent server management by automatically parsing the administrator's management intentions and converting them into specific server management strategies. This automated process not only reduces errors and omissions in manual configuration, but also speeds up response time, allowing the server to adapt to changes in business needs more quickly. Through intelligent resource configuration and performance adjustment, the present invention optimizes resource utilization, reduces energy waste, and reduces operating costs.

[0026] 2. Improve management efficiency and accuracy: This invention uses semantic comparison technology to accurately match the administrator's intention with the preset template, ensuring the accuracy of the target performance data. At the same time, the system can automatically adjust the management strategy or roll back to a stable state based on the matching of real-time performance data and target performance data. This method improves the efficiency and accuracy of server management, ensures the stability and reliability of server performance, and plays an important role in maintaining business continuity and service levels.

[0027] 3. Enhance the adaptability and flexibility of the system: The present invention allows the system to dynamically adjust management strategies based on real-time performance data and can quickly respond to new management intentions, making server management more flexible and able to quickly adapt to different management needs and business scenarios. Through the cache management strategy and fast retrieval mechanism, the system can quickly respond to similar management needs, enhancing the adaptability and flexibility of the system and improving user experience and management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0029] Figure 1 is a schematic diagram of an application scenario of an intent-based server management method according to an embodiment of the present invention;

[0030] Figure 2 is a flow chart of an intent-based server management method according to an embodiment of the present invention;

[0031] Figure 3 is a flow chart of another intent-based server management method according to an embodiment of the present invention;

[0032] Figure 4 It is a schematic diagram of the architecture of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The terms used in the following embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to be limiting of the present invention. As used in the specification of the present invention, the singular expressions "a", "a", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present invention refers to any or all possible combinations comprising one or more of the listed items.

[0034] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0035] It should also be noted that, unless otherwise clearly specified and limited, in the embodiments of the present invention, the terms such as "setting" and "connection" should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two components; it can be a wired communication connection or a wireless communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The embodiments of the present invention are described in detail below.

[0036] like Figure 1 As shown, this embodiment provides an intent-based server management method, which is applied to a server management system (hereinafter referred to as the system). This example improves the efficiency and accuracy of server management by receiving server management intent information from an administrator, automatically determining the target performance data of the business server, and generating corresponding management policies. This method not only reduces errors and omissions in manual configuration and reduces the difficulty of service completion management, but also speeds up response time through automated processes, so that business servers can adapt to changes in business needs more quickly. Through intelligent resource allocation and performance adjustment, this method optimizes resource utilization, reduces energy waste, and reduces operating costs.

[0037] At the same time, the real-time monitoring and performance data matching verification of this embodiment ensures the stability and reliability of server performance and improves the availability of the system. The task completion information provided to the administrator enhances the transparency of management, allowing the administrator to rely on the automation system with more confidence. In general, the present invention provides a more advanced and efficient server management solution for data centers and cloud computing environments by simplifying the management process and improving the accuracy and response speed of operations.

[0038] Combine the following Figure 2 To specifically describe the method of this embodiment, the following steps may be included:

[0039] Step 201, receiving server management intention information sent by an administrator.

[0040] The administrator inputs the server management intention information on the interactive terminal of the server management system.

[0041] Among them, server management intention information refers to the administrator's specific requirements and expectations for server performance, configuration, security, etc. This information is provided to the server management system in the form of text, voice or graphics to guide the system to automatically generate and execute corresponding management policies. For example, the administrator may issue an intention message of "ensuring that the response time of the Web server does not exceed 2 seconds during high traffic" or "keeping the disk usage of the database server below 70%". This information is parsed by the system and converted into specific operation instructions to automatically adjust server settings and resource allocation to achieve the administrator's management goals.

[0042] Step 202: determining target performance data of the service server according to the server management intention information.

[0043] Among them, the target performance data are performance indicators and thresholds pre-set according to business needs and service quality requirements, including but not limited to key performance parameters such as response time, throughput, resource utilization (such as CPU, memory, disk I / O and network bandwidth utilization), service availability, etc. These data define the performance level that the server should achieve when operating normally and providing services, and are the benchmark for evaluating server performance and management effectiveness.

[0044] Specifically, the server management system uses natural language processing technology through an integrated analysis engine to conduct in-depth analysis of the management intent information provided by the administrator, identifying key performance indicators (KPIs) and management goals, such as response time, processing capacity, resource utilization, etc. The system uses preset performance benchmarks and historical data, combined with business needs and historical trends, to determine the target performance data that the business server must achieve. These data define the expected performance range and service quality level of the business server operation, providing an accurate reference for subsequent policy generation.

[0045] Step 203: Generate a server management policy based on the target performance data.

[0046] Among them, the server management strategy is a set of clear guidelines and operating procedures to ensure that the server system can run efficiently and stably and meet the established performance goals and service quality requirements. The server management strategy includes the allocation of server resources, the optimization of application configuration, the implementation of security controls, the formulation of fault prevention and recovery plans, and the execution of monitoring and maintenance activities. It aims to automate and simplify the daily management tasks of the server, improve the reliability and responsiveness of the system, and reduce operation and maintenance costs and risks.

[0047] Specifically, the server management system can use a policy generator, which automatically matches and generates corresponding management policies based on the target performance data and the policy library inside the system. This policy library contains a variety of predefined policy templates and best practices. The policy generator selects the appropriate template based on the target performance data and adjusts the policy parameters according to the current state of the server and environmental variables to ensure that the generated management policy can accurately meet the administrator's management intent and optimize the performance and resource utilization of the server.

[0048] In this embodiment, the policy generator is an automated tool that dynamically generates and adjusts server management policies based on predefined rules, templates, and business objectives, as well as real-time performance data and system status. It usually includes a decision engine that can parse the administrator's management intent, evaluate the server's performance indicators, match the most appropriate management policy template, and automatically fill in parameters and configuration details based on the current system environment and business requirements to output customized management policies to achieve goals such as server performance optimization, resource allocation, and fault prevention.

[0049] The process of building a policy library involves collecting and organizing best practices, industry standards, historical operation and maintenance data, and expert experience from multiple sources, and converting this information into a series of standardized server management policy templates. Each template contains predefined operating steps, configuration parameters, and performance indicators to address common server management scenarios and problems. Then, through continuous monitoring of actual operation and maintenance results and feedback, these templates are continuously adjusted and optimized to ensure that the policy library always reflects the latest technological advances and business needs, so that it can flexibly adapt to different server environments and management goals.

[0050] Step 204: Adjust resource configuration, application configuration and / or service tasks of the business server according to the server management policy.

[0051] Resource configuration refers to the allocation and setting of server hardware resources and system resources, including the allocation of CPU cores, setting of memory size, mounting of storage space, and configuration of network resources. Correct resource configuration can ensure that the server has sufficient processing power to meet the running requirements of the application while avoiding resource waste or bottlenecks.

[0052] Application configuration involves setting up and managing software applications running on the server, which may include database connection parameters, port numbers for application services, security authentication mechanisms, and other parameters related to the runtime behavior of the application. Good application configuration can improve application performance, enhance user experience, and ensure application security and reliability.

[0053] Service tasks refer to various services and background tasks running on the server, such as Web services, database services, and mail services. Service task management includes monitoring service status, scheduling task execution, processing service requests, and maintaining high service availability. Effective service task management is essential to ensure that the server can provide services continuously and stably.

[0054] In this embodiment, the server management system uses integrated automation tools and API calls to adjust the resource configuration of the business server according to the specific instructions in the generated management policy, such as allocating or releasing CPU and memory resources; updating application configuration, such as modifying the database connection pool size or adjusting the concurrency level of application services; and reallocating or optimizing service tasks, such as load balancing and task scheduling. These adjustment operations are automatically executed through scripts to ensure the accuracy and timeliness of configuration changes to achieve the performance and service level goals defined in the management policy.

[0055] Step 205: Obtain the real-time performance data of the service server after adjustment.

[0056] Among them, the server management system deploys a monitoring component, which uses built-in monitoring tools or third-party monitoring solutions to collect real-time performance data of business servers in real time.

[0057] Real-time performance data is used to indicate the performance of business servers in actual operations, including key indicators such as response time, transaction processing rate, system throughput and error rate. Real-time performance data can directly reflect the server's processing capacity and efficiency for user requests, and is the key to evaluating whether the server meets business needs and performance goals. Real-time performance data is continuously captured through preset monitoring points and transmitted to the central monitoring system for analysis to ensure that any performance deviations or anomalies can be detected in a timely manner, providing real-time data support for subsequent performance evaluation and decision-making.

[0058] Step 206: When the real-time performance data matches the target performance data, server management task completion information is returned to the administrator.

[0059] Specifically, the server management system compares the above real-time performance data with the target performance data expected by the administrator. If it is found that the performance indicator matches the target data within a predetermined threshold, the system will automatically verify the successful execution of the management task.

[0060] After confirming that the real-time performance data matches the target performance data, the system will send the administrator information about the completion of the server management task, including detailed results of the task execution and any related performance reports, through email, SMS, application notifications, or status updates on the management dashboard, thereby ensuring that the administrator can promptly understand the performance status of the business server and the results of the management system's operations.

[0061] In some embodiments, when the real-time performance data does not match the target performance data, the system immediately starts a comprehensive diagnosis and adjustment mechanism. First, quickly collect detailed operating information of the server at the current moment, including but not limited to the resource usage of all processes, network connection status, I / O operations of storage devices, and internal operation logs of applications. Through in-depth analysis of these data, combined with pre-established server performance models and fault feature libraries, intelligent algorithms (such as rule-based reasoning, machine learning classification models, etc.) are used to accurately locate the root cause of performance mismatch. Possible causes include hardware failures (such as memory leaks, hard disk read and write failures), software configuration errors (such as unreasonable thread pool parameters, database connection settings), network congestion, or performance bottlenecks of the application itself (such as inefficient algorithms, frequent synchronization operations), etc.

[0062] Once the root cause of the problem is determined, the system quickly formulates targeted adjustment strategies. If it is a hardware problem, the hardware detection and repair process is automatically triggered, such as starting the memory diagnostic tool, checking the health status of the hard disk, and performing hot-swap replacement or notifying the administrator to perform physical device maintenance when necessary; for software configuration errors, according to best practices and performance optimization principles, the correct configuration parameter adjustment script is automatically generated and executed; for network congestion, the network routing strategy is dynamically adjusted, bandwidth allocation is optimized, or flow control mechanisms are enabled; if it is an application performance bottleneck, the code execution path is deeply analyzed, and code optimization techniques (such as cache optimization, algorithm improvement) are tried or the application resource allocation strategy is automatically adjusted (such as increasing or limiting the CPU time slice and memory quota of a specific process).

[0063] During the execution of the adjustment strategy, the server performance changes are continuously monitored in real time to evaluate the effectiveness of the adjustment measures. If the performance after adjustment still does not meet the target requirements, the system automatically back-analyzes the adjustment process, further optimizes the strategy or tries other possible solutions. At the same time, the entire mismatch event and processing process are recorded in detail in the system log for subsequent analysis and learning, so as to continuously improve the system's fault diagnosis and processing capabilities, improve the efficiency and accuracy of dealing with similar problems in the future, and ensure that the server always runs stably towards the target performance data set to meet the management intent.

[0064] This embodiment adopts the above method steps, and the server management system can realize automated and intelligent server performance management, ensuring that the resource configuration, application configuration and service tasks of the business server accurately match the target performance data set by the administrator. Through real-time monitoring and dynamic adjustment, the system not only improves the response speed and operating efficiency of the server, but also optimizes resource utilization, reduces human errors and operation and maintenance costs, and ultimately achieves efficient completion of server management tasks. It can also provide timely feedback of management results to the administrator, enhancing the transparency and trust of management.

[0065] Combine the following Figure 3 To further illustrate the method of this embodiment, it specifically includes the following steps.

[0066] Step 301, receiving server management intention information sent by an administrator.

[0067] The implementation of this step may refer to the description in the above embodiment and will not be repeated here.

[0068] Step 302, compare the server management intent information with the template intent information in the intent information library to obtain semantic similarity.

[0069] Semantic similarity refers to the degree of similarity between two text fragments in terms of semantic content. It converts text into numerical vectors through a specific algorithm (such as the vector space model) and calculates the distance or angle between these vectors to quantify their semantic differences. The calculation result of semantic similarity is usually a value between 0 and 1. The closer the value is to 1, the more similar the semantics of the two text fragments are, and the closer the value is to 0, the greater their semantic difference is.

[0070] Specifically, the system can compare the server management intention information entered by the administrator with the template intention information pre-stored in the intention information library through the integrated natural language processing (NLP) module. This process involves text processing and semantic analysis technology. The system uses algorithms such as vector space models to convert text into numerical vectors, and calculates the semantic similarity between the administrator's intention and the template in the library through similarity measurement methods such as cosine similarity to quantify the degree of semantic matching between the two.

[0071] Step 303: When the semantic similarity is greater than or equal to a set threshold, the server performance data corresponding to the template intent information is determined as the target performance data.

[0072] Specifically, the system sets a threshold to determine whether the administrator's intent matches the template in the library sufficiently. When the calculated semantic similarity is greater than or equal to the preset threshold, the system automatically uses the server performance data associated with the template intent information as the target performance data, thereby simplifying the performance data determination process and ensuring that the generation of management policies can be based on verified and standardized performance indicators, improving the accuracy and effectiveness of management policies.

[0073] For example, suppose an administrator enters a server management intention message: "I hope the query response time of the database server does not exceed 300 milliseconds." The system compares this message with the template intention in the intention information library and finds that the semantic similarity with a template intention message marked as "Optimize database response time" is 0.85. Since the semantic similarity threshold set by the system is 0.8, the similarity between the administrator's intention and the template intention exceeds the threshold, so the system automatically sets the target performance data corresponding to the template, that is, the query response time standard of the database server, as the target performance data of the business server, and will subsequently generate corresponding management policies based on this data.

[0074] In some embodiments, step 303 may further include: when there are multiple template intent information whose semantic similarity is greater than or equal to a set threshold, determining the template intent information with the greatest semantic similarity as the target template intent information; and determining the server performance data corresponding to the target template intent information as the target performance data.

[0075] Specifically, when the system identifies that the semantic similarity of multiple template intent information is greater than or equal to the set threshold, the system will perform a selection process to find the template that best matches the intent information input by the administrator, that is, the template with the largest semantic similarity value, and thus determine it as the "target template intent information". This step ensures that the system can select the most relevant template from multiple candidates for subsequent performance data matching and policy generation.

[0076] After determining the target template intent information, the system will use the server performance data corresponding to the template as the target performance data of the business server. This means that the system will set specific performance goals that the business server should achieve based on the performance indicators and parameters predefined in the target template intent information. These goals will guide subsequent server configuration adjustments and performance optimization work to ensure that the server's operating status can meet the administrator's management intent and business needs.

[0077] For example, suppose an administrator enters an intent message: "I need to ensure that the throughput of the Web server reaches at least 100 requests / second during peak traffic periods." The system finds through comparison that the semantic similarities of three template intent messages all exceed the set threshold of 0.8, namely 0.83, 0.88 and 0.92. The system will select the third template with the highest semantic similarity, that is, the template with a similarity of 0.92, and determine it as the "target template intent information." Subsequently, the system will extract the performance data corresponding to the target template - in this example, "Web server throughput is at least 100 requests / second" - as the target performance data, which is used to generate and adjust management policies to ensure that the Web server can meet this performance target during high traffic periods.

[0078] Step 304: determine the current resource status of the service server.

[0079] Specifically, the system collects the current resource status of the business server in real time through built-in monitoring tools and resource management modules. The current resource status includes key indicators such as CPU usage, memory usage, disk I / O performance, and network bandwidth usage. These data are obtained by directly interacting with the server's operating system and hardware interface, ensuring the accuracy and real-time nature of the information, and providing detailed basic data for subsequent resource optimization and performance adjustment.

[0080] Step 305: Generate the server management policy according to the target performance data and the current resource status.

[0081] Specifically, the system first evaluates the target performance data to identify the specific business requirements for server performance, such as specific response time or processing power. Then, the system analyzes the current resource status, including the use of resources such as CPU, memory, storage, and network, to determine whether the resources meet the performance goals. Based on these analyses, the system uses built-in algorithms and preset management logic to automatically generate a series of optimization measures, which may include dynamic allocation of resources, adjustment of configuration parameters, application of load balancing strategies, etc., to ensure that the server can reach or approach the target performance level under the current resource conditions.

[0082] In addition, the system may also predict changes in resource requirements and automatically expand or reduce resources to adapt to fluctuations in business load, ensuring stable server performance and cost-effectiveness.

[0083] For example, suppose an administrator sets a target performance data, requiring the business server to increase its processing capacity by 20% in the next quarter to cope with the upcoming peak sales season.

[0084] Then, the system discovered through monitoring tools that in the current resource status of the current server, the CPU usage has reached 85%, the memory usage is 70%, and there is a bottleneck in the disk I / O.

[0085] Next, the system automatically generates a comprehensive management strategy based on these current resource conditions and target performance data. The strategy includes adding additional CPU cores, expanding memory capacity, and optimizing the storage system to improve I / O performance, ensuring that the server can meet the demand for increased processing power while maintaining cost-effectiveness and system stability.

[0086] In some embodiments, the server management policy may be stored in a system cache. When other server management intention information with the same semantics is received, the server management policy is retrieved from the system cache.

[0087] Specifically, after generating a server management policy, the system will store the policy in a high-speed system cache for quick access. When other server management intention information with the same or highly similar semantics is subsequently received, the system will confirm the consistency of the intention through comparison. Once the semantics are confirmed to be the same, the system will directly retrieve the previously stored server management policy from the cache, avoiding repeated policy generation processes, thereby improving response speed and processing efficiency, and ensuring rapid response and consistent processing of similar management needs.

[0088] Step 306: Adjust resource configuration, application configuration and / or service tasks of the business server according to the server management policy.

[0089] The implementation of this step may refer to the description in the above embodiment and will not be repeated here.

[0090] Step 307: Obtain the real-time performance data of the service server after adjustment.

[0091] The implementation of this step may refer to the description in the above embodiment and will not be repeated here.

[0092] Step 308, determining whether the real-time performance data matches the target performance data.

[0093] Specifically, the system collects the performance data of the business server through real-time monitoring tools and compares it with the preset target performance data to determine whether it matches within an acceptable error range. Specifically, the system sets thresholds for a series of performance indicators, such as response time, throughput, etc., and tracks the actual performance of these indicators in real time.

[0094] If the actual performance data matches the target performance data within the set threshold, it is considered that the two match, indicating that the server management strategy has achieved the expected effect, and then proceed to step 311.

[0095] If the real-time performance data does not match the target performance data, proceed to step 309 .

[0096] Step 309: Determine the abnormal problem of the business server based on the preset performance indicator rule library and the real-time performance data.

[0097] Specifically, the system has a built-in preset performance indicator rule base, which contains the normal range and abnormal patterns of various performance indicators. When real-time performance data is collected, the system automatically compares this data with the thresholds and patterns defined in the performance indicator rule base. If the real-time performance data exceeds the normal range or matches a certain abnormal pattern, the system will determine whether there is an abnormal problem with the business server based on these preset rules and identify the specific problem type, such as performance bottlenecks, resource overloads, or configuration errors.

[0098] For example, in an online trading platform, the preset performance indicator rule base stipulates that the response time of the transaction processing service shall not exceed 200 milliseconds. When the real-time performance data shows that the response time of the service soars to 500 milliseconds during peak hours, the system identifies the abnormal problem of service response delay by comparing the real-time data with the threshold in the rule base.

[0099] Step 310: Generate a solution to the problem based on the abnormal problem.

[0100] Specifically, the system will use the built-in knowledge base or decision support system to automatically generate corresponding problem solutions based on the nature and severity of the abnormal problem. This solution may include a series of operational steps, such as restarting the service, increasing resource allocation, optimizing configuration parameters, or performing specific maintenance tasks. The system may also provide multiple solutions for the administrator to choose from, or directly execute the preset automatic repair process to restore the normal operation and performance of the server as soon as possible.

[0101] Continuing with the above example, after identifying the abnormal problem of service response delay, the system automatically analyzes and generates a solution to the problem, which may include temporarily increasing the number of instances of the transaction processing service, optimizing database queries, adjusting the resource allocation of the service, or enabling a caching mechanism to reduce the load and restore the service to normal response time, ensuring the performance stability and user experience of the trading platform.

[0102] After resolving the above abnormal problems, the system returns to step 307, and the system will continue to monitor the performance data after the implementation of the adjustment to verify the effectiveness of the solution and ensure that the server performance is restored to or reaches the target performance standard. If the performance still does not meet the standard after the solution is implemented, the system may further analyze the cause, generate a new solution, or prompt the administrator to manually intervene until the problem is properly resolved.

[0103] In some embodiments, it also includes: determining the degree of deviation between the real-time performance data and the target performance data; when the degree of deviation exceeds a set range, generating a rollback instruction; sending the rollback instruction to the business server to roll back the business server to a state before adjustment.

[0104] The degree of deviation refers to the difference between the actual performance data and the target performance data. It is quantified by calculating the deviation between the actual performance indicators (such as response time, throughput, etc.) and the preset target values. It is usually expressed in the form of percentage, absolute value or standard deviation, so as to evaluate whether the server performance is within an acceptable range and whether adjustment measures are needed to correct the deviation.

[0105] The system first continuously collects the performance data of the business server through real-time monitoring tools and compares it with the preset target performance data. The system calculates the deviation between the two, such as the degree of deviation of key indicators such as response time and throughput, and evaluates whether these deviations are within the acceptable performance fluctuation range, thereby quantifying the degree of performance deviation.

[0106] If the system evaluates that the real-time performance data deviates from the target performance data beyond the preset performance tolerance range, such as the response time being 20% ​​higher than the target value, the system will automatically trigger an emergency response mechanism and generate rollback instructions. These instructions are designed to undo the recent configuration changes made to the server to restore to a previously known stable state.

[0107] Once the rollback instructions are generated, the system will send them to the business server through the management interface. After receiving the rollback instructions, the server will perform corresponding operations, such as restoring configuration files, undoing code deployment, or resetting parameter settings, to ensure that the server's operating status is rolled back to the state before the adjustment, thereby trying to restore the expected performance level and reduce performance issues caused by configuration changes.

[0108] In some embodiments, if the deviation between the real-time performance data and the target performance data does not exceed the set range, the system will consider that the server performance is within an acceptable fluctuation range. At this time, the system will not trigger any rollback operation, but will continue to monitor the server performance and dynamically adjust the management policy based on the continuously collected data to ensure that the server continues to maintain or optimize to the target performance level in future operations. At the same time, the system may record the results of this performance evaluation for future performance trend analysis and policy optimization.

[0109] Step 311, returning the server management task completion information to the administrator.

[0110] The implementation of this step may refer to the description in the above embodiment and will not be repeated here.

[0111] The embodiment of the present invention proposes an intent-based server management method, which aims to improve the efficiency and accuracy of server management through intelligent and automated means. First, the server management intent information issued by the administrator in natural language is received, and then the semantic similarity is calculated by semantically comparing it with the template intent information in the intent information library. When the similarity reaches or exceeds the preset threshold, the system will automatically identify and use the server performance data corresponding to the template intent information as the target performance data. This process not only reduces the workload of manually setting the target performance data, but also improves the accuracy of target setting.

[0112] Next, the system will automatically generate the corresponding server management strategy based on the current resource status and target performance data of the business server. This strategy generation process takes into account the actual performance of the server and the management intention of the administrator, ensuring the scientific nature and effectiveness of the management strategy. After the strategy is executed, the system will monitor the performance data of the business server in real time and match it with the target performance data for verification. If the performance data meets the target, the system will return the task completion information to the administrator, indicating that the management task has been successfully executed.

[0113] Furthermore, if the real-time performance data does not match the target performance data, the system will automatically determine the abnormal problem of the business server based on the preset performance indicator rule base and real-time performance data, and generate corresponding problem solutions to quickly respond to and solve the performance deviation problem. In addition, the system will also store the generated management policy in the cache so that when receiving other server management intention information with the same semantics, it can quickly retrieve the corresponding management policy from the cache, thereby improving response speed and processing efficiency.

[0114] Finally, this embodiment also includes a performance monitoring and rollback mechanism. After obtaining the adjusted real-time performance data of the business server, the system will determine the degree of deviation between the real-time performance data and the target performance data. If the degree of deviation exceeds the set range, the system will automatically generate a rollback instruction and send the instruction to the business server to roll back the server to the state before the adjustment to ensure the stability and reliability of the system.

[0115] To sum up, the overall technical solution of this embodiment realizes the automation and intelligence of server management through intelligent intent analysis, policy generation, performance monitoring and exception handling, improves management efficiency, reduces human errors, ensures the stability and reliability of server performance, and provides an advanced server management solution for data centers and cloud computing environments.

[0116] The method provided in the above embodiment can be executed by a server management system, which includes an electronic device. The electronic device in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 4 , is a schematic diagram of a physical device structure of an electronic device in an embodiment of the present invention.

[0117] It should be noted that Figure 4 The structure of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0118] like Figure 4 As shown, the electronic device includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In RAM 403, various programs and data required for system operation are also stored. CPU 401, ROM 402 and RAM 403 are connected to each other through bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0119] The following components are connected to the I / O interface 405: an input section 406 including an audio input device, a button switch, etc.; an output section 407 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0120] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the present invention are performed.

[0121] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0123] Specifically, the electronic device of this embodiment includes a processor and a memory, the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the electronic device to execute the method provided by the above embodiment.

[0124] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the electronic device, the electronic device implements the method provided in the above embodiment.

[0125] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

[0126] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0127] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. An intent-based server management method, characterized in that: include: Receive server management intention information from an administrator, where the server management intention information refers to the administrator's specific requirements and expectations for server performance, configuration, and security; Determine target performance data of the service server according to the server management intention information, wherein the target performance data is a performance indicator and threshold value pre-set according to the business needs and service quality requirements, and the target performance data includes response time, throughput, resource utilization and service availability; A policy generator is used to generate a server management policy based on the target performance data and a policy library within the system; the server management policy includes allocation of server resources, optimization of application configuration, implementation of security controls, formulation of fault prevention and recovery plans, and execution of monitoring and maintenance activities; the policy library includes a variety of predefined policy templates and best practices, and the policy templates include predefined operating steps, configuration parameters, and performance indicators to address common server management scenarios and issues; Adjusting resource configuration, application configuration and / or service tasks of the business server according to the server management strategy, wherein the resource configuration includes allocation of CPU cores, setting of memory size, mounting of storage space and configuration of network resources; Obtaining real-time performance data of the business server after adjustment; When the real-time performance data matches the target performance data, returning server management task completion information to the administrator; When the real-time performance data does not match the target performance data, collecting detailed operation information of the business server at the current moment, the detailed operation information including resource occupancy, network connection status, I / O operation of storage devices, and internal operation log of application programs; Based on the detailed operation information, combined with a pre-established server performance model and a fault feature library, an intelligent algorithm is used to locate the root cause of the problem that causes the performance mismatch, wherein the intelligent algorithm includes a rule-based reasoning and a machine learning classification model; Develop targeted adjustment strategies based on the root causes of the problems.

2. The method according to claim 1, characterized in that The step of determining target performance data of the service server according to the server management intention information comprises: Comparing the server management intent information with the template intent information in the intent information library to obtain semantic similarity; When the semantic similarity is greater than or equal to a set threshold, the server performance data corresponding to the template intent information is determined as the target performance data.

3. The method according to claim 2, characterized in that The step of determining the server performance data corresponding to the template intent information as the target performance data when the semantic similarity is greater than or equal to a set threshold comprises: When the semantic similarity of multiple template intent information is greater than or equal to a set threshold, the template intent information with the greatest semantic similarity is determined as the target template intent information; The server performance data corresponding to the target template intent information is determined as the target performance data.

4. The method according to claim 1, characterized in that: The step of using a policy generator to generate a server management policy based on the target performance data and a policy library within the system includes: Determining the current resource status of the service server; The server management policy is generated according to the target performance data and the current resource status.

5. The method according to claim 1, characterized in that: After the step of using the policy generator to generate the server management policy based on the target performance data and the policy library inside the system, the method further includes: Storing the server management policy in a system cache; When other server management intention information with the same semantics is received, the server management policy is retrieved from the system cache.

6. The method according to claim 1, characterized in that After the step of obtaining the adjusted real-time performance data of the service server, the method further includes: Determining a degree of deviation between the real-time performance data and the target performance data; When the degree of deviation exceeds a set range, a rollback instruction is generated; The rollback instruction is sent to the service server to roll back the service server to a state before the adjustment.

7. An electronic device, characterized in that: including one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method according to any one of claims 1 to 6.

8. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are executed on an electronic device, the electronic device is caused to execute the method as claimed in any one of claims 1 to 6.

9. A computer program product, characterized in that When the computer program product is executed on an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 6.

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