Server operation and maintenance management system and method

Abstract

The invention discloses a server operation and maintenance management system and method, and relates to the technical field of server operation and maintenance management, the server operation and maintenance management system comprises a data acquisition unit, a state judgment unit, a resource allocation unit, an alarm triggering unit, a task grading unit, a resource limiting unit and a report generation unit, the state judgment unit calculates the busy degree of a server and judges the running state of the server; the resource allocation unit allocates server resources according to task characteristics; the alarm triggering unit triggers a resource utilization rate abnormity alarm when the resources exceed a limit; the task grading unit distinguishes task priorities; according to the method, resources are intelligently allocated according to the tasks, idle resources are reasonably utilized when the server is in a low load state, key tasks are preferentially completed when the server is in a high load state, the resource utilization rate is increased, and stable and efficient operation of the server is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of server operation and maintenance management, and in particular to a server operation and maintenance management system and method. Background Art

[0002] In today's digital age, servers, as a core component of information technology infrastructure, are responsible for the storage, processing and transmission of massive amounts of data. Their stable and efficient operation is crucial to the business continuity of enterprises and organizations.

[0003] With the continuous growth of business volume and the increasing complexity of application scenarios, servers are facing many challenges. Traditional server operation and maintenance management methods often rely on manual experience and fixed resource allocation strategies, which are difficult to adapt to dynamically changing workloads. For example, during business peaks, server resources may be bottlenecked due to unreasonable allocation, resulting in delayed response of some tasks or even system crashes, affecting user experience and normal business operations.

[0004] At the same time, there are also problems with the utilization of server hardware resources. During low-load periods, a large number of resources are idle, and during high-load periods, resources cannot be allocated in a timely and effective manner, resulting in resource waste and increased operation and maintenance costs. In addition, the monitoring of server operating status and fault warnings are not accurate and timely enough, and effective preventive measures cannot be taken in advance. Once a fault occurs, it will lead to long-term downtime and data loss risks, causing huge economic losses to the company. Summary of the invention

[0005] The purpose of the present invention is to provide a server operation and maintenance management system and method to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a server operation and maintenance management method, comprising the following steps: S1. Preset the collection time interval to collect the operation data of the server; S2. Calculate the server busyness and determine the server operation status based on real-time operation data; S3. When the server is not busy, count the task execution time and expected completion time, analyze the task urgency, and allocate idle resources to the task; S4. When the server is busy, further analyze the server resource usage. When the resource usage of any server is higher than the threshold, trigger an abnormal resource usage alarm. S5. When the resource usage abnormality alarm is triggered, the priority of the task is calculated, and the task is divided into priority completion tasks and non-priority completion tasks; S6. Analyze the usage of task resources and set resource usage caps for non-priority tasks; S7. Record resource usage and store it in the database, and generate reports for regular analysis.

[0007] Furthermore, in step S1, the operation data of the server is collected at a preset collection time interval, and the server operation data includes: CPU occupancy percentage, memory occupancy percentage, disk read and write rate, number of tasks, task information, and the task information includes the task type, estimated completion time and execution time of any task. The task types include: key customer-related tasks, ordinary customer-related tasks and daily operation and maintenance-related tasks.

[0008] Further, in step S2, the operation status includes: low server busyness, normal server busyness and high server busyness, and the server busyness X is calculated: ; A represents the real-time CPU usage percentage, B represents the real-time memory usage percentage, C represents the disk read / write rate, and C0 represents the rated disk read / write rate of the server. The rated disk read / write rate refers to the theoretical maximum read / write data speed that the disk drive can achieve under ideal working conditions and in accordance with the design specifications. It is an important indicator for measuring disk performance and is usually clearly stated by the disk manufacturer in the product specification. The lower limit X1 and the upper limit X2 of the server busyness are set. When X≤X1, the system determines that the server busyness is low; when X1<X≤X2, the system determines that the server busyness is normal; when X>X2, the system determines that the server busyness is high. The server busyness is accurately calculated by considering the CPU, memory and disk read / write rates to achieve the effect of intelligent resource allocation, rationally utilize idle resources when the load is low, prioritize key tasks when the load is high, improve resource utilization, ensure server stability and efficiency, and enhance business continuity.

[0009] Furthermore, in step S3, when the server is not busy, it is counted that there are D tasks currently being executed, namely {E1, E2, …, E d ,…,E D}, for the dth task E d Perform analysis, where d=1,2,…,D, and call task E in task information d The execution time Z d and expected completion time d0, the expected completion time is the time interval between the task start execution time and the latest task completion time. d The urgency of the task F d =Z d / d0, the task urgency of D tasks is {F1, F2, …, F D}, and then for task Ed Allocate idle resources, including idle CPU time slices. The number of idle CPU time slices monitored in real time is G. The idle CPU time slices represent the CPU time segments that are not occupied by tasks and can be allocated. Allocate idle resources to task E. d , Task E d The number of idle CPU time slices allocated is H d , calculate H d : ; Where g is the number of reserved time slices. Calculate the number of reserved time slices g: ; At this time, X≤X2, so Gg≥0. When the server is not busy, the urgency is calculated based on the time the task has been executed and the expected completion time, and the idle CPU time slices are intelligently allocated accordingly. Accurately allocate resources, improve task processing efficiency, reduce task backlogs, make full use of idle resources, and enhance the performance and flexibility of the server in low-load scenarios. It not only optimizes the task process, but also enables the server to maintain efficient and stable operation under low load, so as to prepare for resource reserves and coordination in advance for the subsequent complex tasks and reduce overall operating costs.

[0010] Further, in step S4, when the server is highly busy, the resource usage abnormal alarm includes a CPU occupancy abnormal alarm and a memory occupancy abnormal alarm. The CPU occupancy upper limit threshold and the memory occupancy upper limit threshold are set. When the CPU occupancy percentage exceeds the CPU occupancy upper limit threshold, the CPU occupancy abnormal alarm is triggered. When the memory occupancy percentage exceeds the memory occupancy upper limit threshold, the memory occupancy abnormal alarm is triggered. For most conventional servers, the CPU occupancy of the server is usually not higher than 80%, and the memory occupancy is not higher than 80%, that is, the CPU occupancy upper limit threshold is set to 80%, and the memory occupancy upper limit threshold is set to 80%. When the server is highly busy, by setting the CPU and memory occupancy upper limit thresholds to trigger the alarm, resource abnormalities can be quickly detected. This allows operation and maintenance personnel to take timely measures, such as adjusting task resource allocation, optimizing system configuration, etc., to effectively prevent server freezes or freezes due to excessive resource occupation, ensure smooth system operation, reduce business interruption risks, and improve service reliability; Further, in step S5, the system determines the importance of the task according to the task type, and sets the task correlation coefficient according to the importance. For example, the task correlation coefficient for key customer-related tasks is set to R1, the task correlation coefficient for ordinary customer-related tasks is set to R2, and the task correlation coefficient for daily operation and maintenance-related tasks is set to R3, where R1>R2>R3. When the resource utilization abnormality alarm is triggered, the dth task E is calculated. d Priority J d: ; Set the priority threshold to divide the tasks into priority tasks and non-priority tasks. For example, when R1=1.5, R2=1, R3=0.5, considering that 0<F d <1, set the priority threshold to J, J=0.5*(R1+R2)+0.5*(F dmax +F dmin ) = 1.75, where F dmax F d The maximum value that can be achieved, F dmin F d The minimum value that can be achieved. This setting not only ensures the priority of key customer tasks, but also ensures the timely completion of ordinary customer tasks, and obtains the priority completion tasks {Y1, Y2, …, Y P} and non-priority completed tasks {y1,y2,…,y Q}, distinguish task priorities by intelligently setting task correlation coefficients, calculate priority levels, and prioritize key customer tasks while improving resource utilization, taking into account ordinary customers and daily operation and maintenance tasks, optimizing task execution order, reducing delays in critical tasks, improving customer satisfaction, and enhancing the rationality and effectiveness of task scheduling on servers under high loads.

[0011] Further, in step S6, the task resource usage is analyzed, and the non-priority completed tasks {y1, y2, ..., y q} Set the resource usage limit, which includes the CPU usage percentage limit and the memory usage percentage limit. Calculate the CPU usage percentage limit M A : ; Where D q is the qth non-priority completed task, N is the stability coefficient of the server, and the stability coefficient setting method is, for example, calling the number of server alarms in the previous month from the database, n, and the stability coefficient N=1 / n; Similarly, calculate the upper limit M of memory usage percentage B : ; When the load is high, for non-priority tasks, resource caps are set based on CPU and memory usage and stability factors, effectively controlling the resource usage of non-critical tasks to avoid excessive resource consumption, balancing the overall server load, ensuring the resource requirements of priority tasks, improving the stability of the server in a high-pressure environment and the ability to handle key business, and reducing the risk of system crashes; Furthermore, in step S7, a resource usage trend graph showing the CPU occupancy percentage and memory occupancy percentage changing over time is generated, the alarm start time and end time are marked, the alarm duration is calculated and added to the database, and a resource usage report is generated. The resource usage report includes the alarm duration for the day, the number of alarms for the day, the current CPU occupancy percentage of the server, and the current memory occupancy percentage of the server.

[0012] A server operation and maintenance management system, the system comprising: a data collection unit, a state judgment unit, a resource allocation unit, an alarm triggering unit, a task classification unit, a resource restriction unit and a report generation unit; The data collection unit presets a collection time interval to collect the operation data of the server; The state judgment unit calculates the server busyness and judges the server operation state based on the real-time operation data; When the server is not busy, the resource allocation unit counts the task execution time and expected completion time, analyzes the task urgency, and allocates idle resources to the task; The alarm triggering unit further analyzes the server resource usage when the server is busy, and triggers an abnormal resource usage alarm when the resource usage of any server is higher than a threshold; When the task classification unit triggers an alarm for abnormal resource usage, the system calculates the priority of the tasks and divides the tasks into priority tasks and non-priority tasks; The resource restriction unit analyzes the usage of task resources and sets an upper limit on the occupied resources for non-priority tasks; The report generation unit records resource usage and stores it in a database, and generates reports for regular analysis.

[0013] Compared with the prior art, the beneficial effects achieved by the present invention are: on the one hand, it uses artificial intelligence to analyze server load in real time, allocates idle resources according to the urgency of tasks when the load is low, and gives priority to key task resources when the load is high, thus avoiding idle resources or competition, improving resource utilization, reducing energy consumption costs, and maximizing resource utilization; On the one hand, through real-time monitoring and intelligent algorithms, we can accurately judge the server's busyness, prevent performance bottlenecks and crash risks in advance, ensure rapid task response during business peaks, maintain stable daily operations, reduce the probability of downtime, and ensure business continuity.

[0014] On the other hand, artificial intelligence realizes operation and maintenance automation, reduces manual intervention, lowers labor costs, and accurately warns and prevents faults to avoid data loss and business losses, providing a strong data foundation for CPU and memory data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural diagram of a server operation and maintenance management system of the present invention; Figure 2 It is a flow chart of a server operation and maintenance management method of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1 and Figure 2 The present invention provides a technical solution: a server operation and maintenance management method, comprising the following steps: S1. Preset the collection time interval to collect the operation data of the server; S2. Calculate the server busyness and determine the server operation status based on real-time operation data; S3. When the server is not busy, count the task execution time and expected completion time, analyze the task urgency, and allocate idle resources to the task; S4. When the server is busy, further analyze the server resource usage. When the resource usage of any server is higher than the threshold, trigger an abnormal resource usage alarm. S5. When the resource usage abnormality alarm is triggered, the priority of the task is calculated, and the task is divided into priority completion tasks and non-priority completion tasks; S6. Analyze the usage of task resources and set resource usage caps for non-priority tasks; S7. Record resource usage and store it in the database, and generate reports for regular analysis.

[0018] In step S1, the operation data of the server is collected at a preset collection time interval, and the server operation data includes: CPU occupancy percentage, memory occupancy percentage, disk read and write rate, number of tasks, and task information. The task information includes the task type, estimated completion time, and executed time of any task. The task types include: key customer-related tasks, ordinary customer-related tasks, and daily operation and maintenance-related tasks; In step S2, the operation status includes: low server busyness, normal server busyness and high server busyness, and the server busyness X is calculated: ; A represents the real-time CPU usage percentage, B represents the real-time memory usage percentage, C represents the disk read / write rate, and C0 represents the rated disk read / write rate of the server. The rated disk read / write rate refers to the theoretical maximum read / write data speed that the disk drive can achieve under ideal working conditions and in accordance with the design specifications. It is an important indicator for measuring disk performance and is usually clearly stated by the disk manufacturer in the product specification. The lower limit X1 and the upper limit X2 of the server busyness are set. When X≤X1, the system determines that the server busyness is low; when X1<X≤X2, the system determines that the server busyness is normal; when X>X2, the system determines that the server busyness is high. The server busyness is accurately calculated by considering the CPU, memory and disk read / write rates to achieve the effect of intelligent resource allocation, rationally utilize idle resources when the load is low, prioritize key tasks when the load is high, improve resource utilization, ensure server stability and efficiency, and enhance business continuity.

[0019] When the server is not busy, it is counted that there are D tasks currently being executed, namely {E1, E2, …, E d ,…,E D}, for the dth task E d Perform analysis, where d=1,2,…,D, and call task E in task information d The execution time Z d and expected completion time d0, the expected completion time is the time interval between the task start execution time and the latest task completion time. d The urgency of the task F d =Z d / d0, the task urgency of D tasks is {F1, F2, …, F D}, and then for task E d Allocate idle resources, including idle CPU time slices. The number of idle CPU time slices monitored in real time is G. The idle CPU time slices represent the CPU time segments that are not occupied by tasks and can be allocated. Allocate idle resources to task E. d , Task E d The number of idle CPU time slices allocated is H d , calculate H d : ; Where g is the number of reserved time slices. Calculate the number of reserved time slices g: ; When the server is not busy, the urgency is calculated based on the time the task has been executed and the expected completion time, and the idle CPU time slices are intelligently allocated accordingly. Accurately allocate resources, improve task processing efficiency, reduce task backlogs, make full use of idle resources, and enhance the performance and flexibility of the server in low-load scenarios. It not only optimizes the task process, but also enables the server to maintain efficient and stable operation under low load, so as to prepare for resource reserves and coordination in advance for the subsequent complex tasks and reduce overall operating costs.

[0020] In step S4, when the server is busy, the resource usage abnormal alarm includes CPU occupancy abnormal alarm and memory occupancy abnormal alarm. The CPU occupancy upper limit threshold and the memory occupancy upper limit threshold are set. When the CPU occupancy percentage exceeds the CPU occupancy upper limit threshold, the CPU occupancy abnormal alarm is triggered. When the memory occupancy percentage exceeds the memory occupancy upper limit threshold, the memory occupancy abnormal alarm is triggered. For most conventional servers, the CPU occupancy of the server is usually not higher than 80%, and the memory occupancy is not higher than 80%, that is, the CPU occupancy upper limit threshold is set to 80%, and the memory occupancy upper limit threshold is set to 80%. When the server is busy, by setting the CPU and memory occupancy upper limit thresholds to trigger the alarm, resource abnormalities can be quickly detected. This allows operation and maintenance personnel to take timely measures, such as adjusting task resource allocation, optimizing system configuration, etc., to effectively prevent server freezes or crashes caused by excessive resource occupation, ensure the smooth operation of the system, reduce the risk of business interruption, and improve service reliability.

[0021] Further, in step S5, the system determines the importance of the task according to the task type, and sets the task correlation coefficient according to the importance. For example, the task correlation coefficient for key customer-related tasks is set to R1, the task correlation coefficient for ordinary customer-related tasks is set to R2, and the task correlation coefficient for daily operation and maintenance-related tasks is set to R3, where R1>R2>R3. When the resource utilization abnormality alarm is triggered, the dth task E is calculated. d Priority J d : ; Set the priority threshold to divide the tasks into priority tasks and non-priority tasks. For example, when R1=1.5, R2=1, R3=0.5, considering that 0<F d <1, set the priority threshold to J, J=0.5*(R1+R2)+0.5*(F dmax +F dmin ) = 1.75, where F dmax F d The maximum value that can be achieved, F dmin Fd The minimum value that can be achieved. This setting not only ensures the priority of key customer tasks, but also ensures the timely completion of ordinary customer tasks, and obtains the priority completion tasks {Y1, Y2, …, Y P} and non-priority completed tasks {y1,y2,…,y Q}, distinguish task priorities by intelligently setting task correlation coefficients, calculate priority levels, and prioritize key customer tasks while improving resource utilization, taking into account ordinary customers and daily operation and maintenance tasks, optimizing task execution order, reducing delays in critical tasks, improving customer satisfaction, and enhancing the rationality and effectiveness of task scheduling on servers under high loads.

[0022] Further, in step S6, the task resource usage is analyzed, and the non-priority completed tasks {y1, y2, ..., y q} Set the resource usage limit, which includes the CPU usage percentage limit and the memory usage percentage limit. Calculate the CPU usage percentage limit M A : ; Where D q is the qth non-priority completed task, N is the stability coefficient of the server, and the stability coefficient setting method is, for example, calling the number of server alarms in the previous month from the database, n, and the stability coefficient N=1 / n; Similarly, calculate the upper limit M of memory usage percentage B : ; When the load is high, resource limits are set for non-priority tasks based on CPU and memory usage and stability factors, effectively controlling resource usage of non-critical tasks to avoid excessive resource consumption, balancing the overall server load, ensuring resource requirements for priority tasks, improving server stability and key business processing capabilities in high-pressure environments, and reducing the risk of system crashes.

[0023] Furthermore, in step S7, a resource usage trend graph showing the CPU occupancy percentage and memory occupancy percentage changing over time is generated, the alarm start time and end time are marked, the alarm duration is calculated and added to the database, and a resource usage report is generated. The resource usage report includes the alarm duration for the day, the number of alarms for the day, the current CPU occupancy percentage of the server, and the current memory occupancy percentage of the server.

[0024] A server operation and maintenance management system, the system comprising: a data collection unit, a state judgment unit, a resource allocation unit, an alarm triggering unit, a task classification unit, a resource restriction unit and a report generation unit; The data collection unit presets a collection time interval to collect the operation data of the server; The state judgment unit calculates the server busyness and judges the server operation state based on the real-time operation data; When the server is not busy, the resource allocation unit counts the task execution time and expected completion time, analyzes the task urgency, and allocates idle resources to the task; The alarm triggering unit further analyzes the server resource usage when the server is busy, and triggers an abnormal resource usage alarm when the resource usage of any server is higher than a threshold; When the task classification unit triggers an alarm for abnormal resource usage, the system calculates the priority of the tasks and divides the tasks into priority tasks and non-priority tasks; The resource restriction unit analyzes the usage of task resources and sets an upper limit on the occupied resources for non-priority tasks; The report generation unit records resource usage and stores it in a database, and generates reports for regular analysis.

[0025] Example 1: When providing services to multiple different types of customers, some customers suddenly have high traffic demands. Website hosting services for a large e-commerce customer (key customer task correlation coefficient, R1=2), daily office application hosting services for small and medium-sized enterprises (ordinary customer task correlation coefficient, R2=1.3), and security scanning tasks for their own servers (daily operation and maintenance task correlation coefficient, R3=0.7). When the server resource usage rate soars and triggers an alarm, the priority J is accurately calculated. d To allocate resources. A large e-commerce customer orders E d The urgency of the task d =0.7, calculate the optimization degree J of the order d =2+0.7=2.7, which is higher than the priority threshold of 1.6, so task E is judged d In order to give priority to completing tasks, the office applications of small and medium-sized enterprises can also run normally under reasonable resource allocation, and the server's own security scans are carried out in an orderly manner with low resource usage, ensuring the stability and reliability of cloud computing services.

[0026] Example 2: When a large-scale promotional activity is carried out on an e-commerce platform, server traffic increases dramatically. Through this operation and maintenance management system, it is preset to collect server operation data every 5 minutes. At a certain moment after the start of the activity, the server busyness is calculated to be higher than the upper limit of the server busyness, and the resource utilization abnormality alarm is triggered at this time. The system recognizes that the processing order payment related tasks are key customer tasks (correlation coefficient R1=1.5), product recommendations are ordinary customer tasks (correlation coefficient R2=1), and data backup is a daily operation and maintenance task (correlation coefficient R3=0.5). After calculating the priority of each task, the order payment task is listed as a priority task, and the non-priority tasks such as product recommendations are calculated based on the stability coefficient (10 alarms in the previous month, the stability coefficient N=1 / 10 can be obtained) to calculate the upper limit of the CPU occupancy percentage, and reasonably limit its resource use, ensuring the rapid processing of order payments, while maintaining the stable operation of the server, and no system crashes occur. During the event, the overall performance of the server is good and the business is carried out smoothly.

[0027] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A server operation and maintenance management method, characterized in that: The method comprises the following steps: S1. Preset the collection time interval to collect the operation data of the server; S2. Calculate the server busyness and determine the server operation status based on real-time operation data; S3. When the server is not busy, count the task execution time and expected completion time, analyze the task urgency, and allocate idle resources to the task; S4. When the server is busy, further analyze the server resource usage. When the resource usage of any server is higher than the threshold, trigger an abnormal resource usage alarm. S5. When the resource usage abnormality alarm is triggered, the priority of the task is calculated, and the task is divided into priority completion tasks and non-priority completion tasks; S6. Analyze the usage of task resources and set resource usage caps for non-priority tasks; S7. Record resource usage and store it in the database, and generate reports for regular analysis.

2. A server operation and maintenance management method according to claim 1, characterized in that: In step S1, the server operation data is collected at a preset collection time interval, and the server operation data includes: CPU occupancy percentage, memory occupancy percentage, disk read and write rate, number of tasks, task information, and the task information includes the task type, estimated completion time, and execution time of any task.

3. A server operation and maintenance management method according to claim 2, characterized in that: In step S2, the operation status includes: low server busyness, normal server busyness and high server busyness, and the server busyness X is calculated: ； A represents the real-time CPU usage percentage, B represents the real-time memory usage percentage, C represents the disk read / write rate, C0 represents the rated disk read / write rate of the server, and the server busyness lower limit X1 and server busyness upper limit X2 are set. When X≤X1, the server busyness is judged to be low; when X1<X≤X2, the server busyness is judged to be normal; when X>X2, the server busyness is judged to be high.

4. A server operation and maintenance management method according to claim 3, characterized in that: In step S3, when the server is not busy, it is counted that there are D tasks currently being executed, namely {E1, E2, …, E d ,…,E D }, for the dth task E d Perform analysis, where d=1,2,…,D, and call task E in task information d The execution time Z d and expected completion time d0, the expected completion time is the time interval between the task start execution time and the latest task completion time. d The urgency of the task F d =Z d / d0, the task urgency of the D tasks is {F1, F2, …, F D }, and then for task E d Perform idle resource allocation, the idle resources include idle CPU time slices, the number of idle CPU time slices monitored in real time is G, and idle resources are allocated to task E. Task E d The number of idle CPU time slices allocated is H d , calculate H d : ； Where g is the number of reserved time slices.

5. A server operation and maintenance management method according to claim 4, characterized in that: In step S4, when the server is very busy, the resource usage abnormal alarm includes a CPU occupancy abnormal alarm and a memory occupancy abnormal alarm. The CPU occupancy upper limit threshold and the memory occupancy upper limit threshold are set. When the CPU occupancy percentage exceeds the CPU occupancy upper limit threshold, the CPU occupancy abnormal alarm is triggered. When the memory occupancy percentage exceeds the memory occupancy upper limit threshold, the memory occupancy abnormal alarm is triggered.

6. A server operation and maintenance management method according to claim 5, characterized in that: In step S5, the task correlation coefficient is set according to the task type. When the resource usage abnormality alarm is triggered, the dth task E is calculated. d Priority J d : ； Where L d For Task E d The task correlation coefficient is set to set the priority threshold J. When J d >J, judge task E d To complete the task first, when J d ≤J, judge task E d For non-priority tasks, we get priority tasks {Y1,Y2,…,Y P } and non-priority completed tasks {y1,y2,…,y Q }, P represents the number of tasks that are completed with priority, and Q represents the number of tasks that are not completed with priority.

7. A server operation and maintenance management method according to claim 6, characterized in that: In step S6, according to the real-time CPU occupancy percentage A and memory occupancy percentage B, the resource occupancy upper limit of the non-priority completed task is set, and the resource occupancy upper limit includes the CPU occupancy percentage upper limit and the memory occupancy percentage upper limit. The CPU occupancy percentage upper limit M is calculated. A : ； where F q is the task urgency of the qth non-priority task, and N is the stability coefficient of the server.

8. A server operation and maintenance management method according to claim 7, characterized in that: In step S7, a resource usage trend graph showing the CPU occupancy percentage and memory occupancy percentage changing over time is generated, the alarm start time and end time are marked, the alarm duration is calculated and added to the database, and a resource usage report is generated. The resource usage report includes the alarm duration for the day, the number of alarms for the day, the current CPU occupancy percentage of the server, and the current memory occupancy percentage of the server.

9. A server operation and maintenance management system, the system being applied to a server operation and maintenance management method according to any one of claims 1 to 8, characterized in that: The system comprises: a data collection unit, a state judgment unit, a resource allocation unit, an alarm triggering unit, a task classification unit, a resource restriction unit and a report generation unit; The data collection unit presets a collection time interval to collect the operation data of the server; The state judgment unit calculates the server busyness and judges the server operation state based on the real-time operation data; When the server is not busy, the resource allocation unit counts the task execution time and expected completion time, analyzes the task urgency, and allocates idle resources to the task; The alarm triggering unit further analyzes the server resource usage when the server is busy, and triggers an abnormal resource usage alarm when the resource usage of any server is higher than a threshold; When the task classification unit triggers an alarm for abnormal resource usage, the system calculates the priority of the tasks and divides the tasks into priority tasks and non-priority tasks; The resource restriction unit analyzes the usage of task resources and sets an upper limit on the occupied resources for non-priority tasks; The report generation unit records resource usage and stores it in a database, and generates reports for regular analysis.

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