Load balancing service method and system based on SAN storage

Abstract

The application discloses a load balancing service method and system based on SAN storage, relates to the technical field of load balancing, and comprises the following steps: determining required SAN storage capacity and performance requirements; selecting a fiber channel storage area network as a SAN storage environment; setting an access mode and data read-write frequency of a business system; selecting a polling algorithm, a minimum connection number algorithm or a weight-based distribution algorithm as a load balancing algorithm of the SAN storage; creating a virtual IP on a load balancing device; configuring a node pool and adding storage nodes in a SAN network to the node pool of the load balancing device; and monitoring a load condition and a node health condition of the load balancing device in real time. The SAN storage network is constructed through a storage environment construction module, a load balancing algorithm module and an algorithm stability detection module, the sharing and centralized management of storage resources are realized, and the utilization rate and flexibility of the storage resources are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of load balancing, in particular to a load balancing service method and system based on SAN storage. BACKGROUND

[0002] In modern enterprises, with the continuous growth of business volume and the sharp increase of data volume, traditional direct-connection storage has been unable to meet the large-scale and high-performance data storage requirements. As a centralized data storage management solution, storage area network (SAN) can provide efficient and reliable data access and sharing services, and therefore has gradually become the preferred solution for enterprises. In particular, in data storage environments requiring high availability, high throughput and low latency, such as database servers, online transaction processing systems and big data analysis platforms, the application of SAN architecture is particularly widespread.

[0003] The construction of a SAN storage network involves the configuration of various hardware devices and software, such as fiber channel switches, disk arrays, SAN sharing software, etc., and the construction process is complex and prone to errors. During business operation, the access patterns and data read-write frequencies of different business systems may differ greatly, leading to uneven utilization of storage resources. SUMMARY

[0004] To solve the above technical problems, a load balancing service method based on SAN storage is provided, which solves the problems raised in the background technology.

[0005] To achieve the above purposes, the technical scheme adopted by the present application is as follows:

[0006] The load balancing service method based on SAN storage comprises:

[0007] Based on business requirements, determine the required SAN storage capacity and performance requirements;

[0008] Select a fiber channel storage area network as the SAN storage environment, and configure SAN sharing software, node servers, fiber switches and disk array devices to build a SAN storage network;

[0009] Analyze business load, set the access mode and data read-write frequency of the business system, and develop a corresponding load balancing strategy;

[0010] Based on the characteristics of business load, select a round-robin algorithm, a minimum connection number algorithm or a weight-based distribution algorithm as the load balancing algorithm for SAN storage;

[0011] Run the corresponding SAN storage load balancing algorithm;

[0012] configuring a load balancing device in a SAN network and creating a virtual IP on the load balancing device, taking the IP as an access point for clients to access the SAN storage;

[0013] configuring a node pool and adding storage nodes in the SAN network to the node pool of the load balancing device, so that the load balancer schedules the storage nodes to handle requests from clients;

[0014] creating a virtual service on the load balancing device, associating the virtual IP with the storage node pool, and configuring virtual service parameters including port number and protocol type;

[0015] ensuring that the load balancing device is correctly configured and starting the load balancing service;

[0016] monitoring the load and node health of the load balancing device in real time, and adjusting the load balancing strategy in real time based on the monitoring results and changes in business demand.

[0017] Preferably, the analysis of business load, setting the access mode and data read-write frequency of the business system, and formulating the corresponding load balancing strategy specifically includes:

[0018] monitoring the operation data of the business system;

[0019] processing and analyzing the collected operation data to identify peak and valley periods of business load and trends;

[0020] based on the characteristics and needs of the business system, setting the sequential access mode as the access mode;

[0021] based on the sequential access scenario, optimizing disk layout and file system structure to reduce head movement and data transmission delay;

[0022] analyze the characteristics and rules of data read-write frequency, and based on the read-write demand analysis results, formulate data read-write strategy;

[0023] monitoring the read-write performance of the storage system in real time and adjusting and optimizing according to the actual situation;

[0024] obtain the load balancing strategy, which includes round robin algorithm, least connection number algorithm or weight-based distribution algorithm.

[0025] Preferably, the load balancing algorithm for SAN storage is selected based on the characteristics of the business load, which specifically includes:

[0026] preset the load difference threshold of peak and valley periods of business load and the variance threshold of read-write speed of each node server in the SAN storage network;

[0027] determining whether the load difference between the peak period and the valley period of the service load is greater than a preset load difference threshold, if yes, selecting the weight-based distribution algorithm as the load balancing algorithm of the SAN storage, and if no, not outputting;

[0028] determining whether the variance of the read-write speed of each node server in the SAN storage network is greater than a preset variance threshold, if yes, selecting the least connection number algorithm as the load balancing algorithm of the SAN storage, and if no, selecting the round robin algorithm as the load balancing algorithm of the SAN storage.

[0029] Preferably, the running of the corresponding SAN storage load balancing algorithm specifically comprises:

[0030] the load balancer receives data read-write requests from clients;

[0031] obtaining a preset load balancing algorithm;

[0032] in the round robin algorithm, the load balancer obtains a node server list, and traverses the node server list in a preset order;

[0033] for each received data read-write request, the load balancer distributes it to the currently traversed node server;

[0034] when the last node server in the list is traversed, the load balancer will start traversing from the first node server in the node server list again;

[0035] in the least connection number algorithm, the load balancer obtains the current connection number of each node server;

[0036] the load balancer selects the node server with the least current connection number to process a new data read-write request;

[0037] distributing the data read-write request to the selected node server and updating the connection number of the node server;

[0038] in the weight-based distribution algorithm, an administrator sets a weight value for each node server based on the storage capacity and performance requirements of the node server;

[0039] the load balancer calculates the request proportion of each node server according to the preset weight value;

[0040] the load balancer selects the node server receiving the current data read-write request based on the calculated request proportion;

[0041] distributing the data read-write request to the selected node server and updating the weight value and request proportion of each node server.

[0042] Preferably, the configuring the load balancing device in the SAN network and creating a virtual IP on the load balancing device, which is used as an entry point for the client to access the SAN storage specifically comprises:

[0043] Obtaining login credentials of the load balancing device, the login credentials including a username and a password;

[0044] Logging into a command line interface of the load balancing device by a remote login tool using the login credentials;

[0045] Configuring a network interface on the load balancing device to communicate with other devices in the SAN network;

[0046] Creating a virtual IP address on the load balancing device, which is used as an entry point for the client to access the SAN storage;

[0047] Setting subnet mask and gateway attributes of the virtual IP to communicate with other devices in the SAN network;

[0048] Using a client device to access the SAN storage through the virtual IP address and testing effectiveness of the load balancing configuration;

[0049] Determining whether the request of the client can be correctly distributed to each node server and the returned data is accurate, if yes, no output is made, if not, checking a load balancing algorithm flow of the SAN storage.

[0050] Preferably, the configuring the node pool and adding the storage nodes in the SAN network to the node pool of the load balancing device, the load balancer processing the request of the client by scheduling the storage nodes specifically comprises:

[0051] Scanning devices in the SAN network and obtaining IP addresses and port numbers of the devices;

[0052] Inputting the IP addresses and port numbers of the storage nodes in a configuration interface of the node pool;

[0053] The load balancer receiving the request of the client through the virtual IP address thereof;

[0054] The storage nodes receiving the request, processing the request and returning a result to the load balancer, and the load balancer forwarding the result to the client.

[0055] Preferably, the real-time monitoring of the load balancing device includes monitoring of a load condition and a node health condition of the load balancing device, and real-time adjustment of a load balancing strategy based on monitoring results and changes in business requirements specifically comprises:

[0056] Setting checking frequency and response time threshold parameters in the configuration interface of the node pool and selecting an HTTP request as a checking method.

[0057] The load balancing device sends a health check request to the storage node periodically based on the checking frequency;

[0058] The health state of the storage node is determined based on the response result;

[0059] It is determined whether the storage node cannot respond to the health check request or the response time exceeds a threshold, if yes, the storage node is marked as an unhealthy state, removed from the load balancing algorithm, and maintained, if not, the storage node is marked as a healthy state.

[0060] Further, a load balancing service system based on SAN storage is provided for implementing the load balancing service method based on SAN storage as described above, comprising:

[0061] A storage environment construction module is configured to determine the required SAN storage capacity and performance requirements based on business requirements, select a fiber channel storage area network as a SAN storage environment, and configure a SAN shared software, a node server, a fiber switch and a disk array device to construct a SAN storage network.

[0062] A load balancing algorithm module is configured to analyze business load, set the access mode and data read-write frequency of a business system, formulate a corresponding load balancing strategy, select a round-robin algorithm, a minimum connection number algorithm or a weight-based distribution algorithm as a load balancing algorithm of the SAN storage based on the business load characteristics, and run the corresponding SAN storage load balancing algorithm.

[0063] An algorithm stability detection module is configured to configure a load balancing device in the SAN network, create a virtual IP on the load balancing device, use the IP as an entry point for the client to access the SAN storage, configure a node pool, and add the storage nodes in the SAN network to the node pool of the load balancing device, the load balancer processes the requests of the client by scheduling the storage nodes, creates a virtual service on the load balancing device, associates the virtual IP with the storage node pool, configures the virtual service parameters, ensures that the load balancing device has been correctly configured and starts the load balancing service, monitors the load and node health status of the load balancing device in real time, and adjusts the load balancing strategy in real time based on the monitoring result and the change of business requirements.

[0064] Compared with the prior art, the present application has the following advantages:

[0065] By setting the storage environment construction module, the load balancing algorithm module and the algorithm stability detection module, the SAN storage network is constructed, the sharing and centralized management of storage resources are realized, the utilization rate and flexibility of storage resources are improved, the stable performance of the storage system under high load is ensured, different business scenarios and demands can be more flexibly coped with, potential problems can be found and solved in time, the stable operation of the storage system is ensured, the fault tolerance of the storage system is improved, various sudden situations and faults can be coped with, and the integrity and safety of data are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0066] Figure 1 The method flow chart for the load balancing service based on the SAN storage of the application;

[0067] Figure 2 The method flow chart for analyzing the business load, setting the access mode of the business system and the data read-write frequency of the application;

[0068] Figure 3 The method flow chart for selecting the load balancing algorithm of the SAN storage of the application;

[0069] Figure 4 The method flow chart for running the corresponding load balancing algorithm of the SAN storage of the application;

[0070] Figure 5 The method flow chart for configuring the load balancing device in the SAN network and creating a virtual IP on the load balancing device of the application;

[0071] Figure 6 The method flow chart for configuring the node pool of the application;

[0072] Figure 7 The method flow chart for monitoring the load condition and node health condition of the load balancing device in real time of the application. DETAILED DESCRIPTION

[0073] The following description is used to disclose the application so that those skilled in the art can implement the application. The preferred embodiments in the following description are only as examples, and other obvious modifications can be thought of by those skilled in the art.

[0074] Referring to Figure 1 The load balancing service method based on the SAN storage, as shown in the figure, comprises:

[0075] Based on the business demand, the required SAN storage capacity and performance requirement are determined;

[0076] The fiber channel storage area network is selected as the SAN storage environment, and the SAN sharing software, the node server, the fiber switch and the disk array device are configured to construct the SAN storage network;

[0077] analyze the business load, set the access mode and data read-write frequency of the business system, and formulate the corresponding load balancing strategy;

[0078] Based on the characteristics of the business load, select the round-robin algorithm, the least connection number algorithm or the weight-based distribution algorithm as the load balancing algorithm of the SAN storage;

[0079] Run the corresponding SAN storage load balancing algorithm;

[0080] Configure the load balancing device in the SAN network, and create a virtual IP on the load balancing device, which is used as the entry point for the client to access the SAN storage;

[0081] Configure the node pool and add the storage nodes in the SAN network to the node pool of the load balancing device, and the load balancer processes the client's request by scheduling the storage nodes;

[0082] Create a virtual service on the load balancing device, associate the virtual IP with the storage node pool, and configure the virtual service parameters, including port number and protocol type;

[0083] Ensure that the load balancing device has been correctly configured and the load balancing service is started;

[0084] Monitor the load and node health of the load balancing device in real time, and adjust the load balancing strategy in real time based on the monitoring results and changes in business demand.

[0085] Referring to Figure 2 , analyzing the business load, setting the access mode and data read-write frequency of the business system, and formulating the corresponding load balancing strategy specifically includes:

[0086] Monitor the running data of the business system;

[0087] Process and analyze the collected running data to identify the peak and trough periods of the business load and the change trend;

[0088] Based on the characteristics and needs of the business system, set the sequential access mode as the access mode;

[0089] Based on the sequential access scenario, optimize the disk layout and file system structure to reduce head movement and data transmission delay;

[0090] Analyze the characteristics and rules of data read-write frequency, and based on the read-write demand analysis results, formulate the data read-write strategy;

[0091] Monitor the read-write performance of the storage system in real time, and adjust and optimize according to the actual situation;

[0092] obtaining a load balancing strategy, the load balancing strategy comprising a round robin algorithm, a least connection algorithm, or a weight-based distribution algorithm.

[0093] The collected operation data is cleaned and preprocessed to remove outliers and invalid data. The preprocessed data is analyzed in depth using data analysis tools to identify peak and trough periods of business load and trends. The analysis results are visualized and displayed in charts such as line charts, bar charts, and pie charts to facilitate intuitive understanding of business load conditions.

[0094] Referring to Figure 3 Based on the characteristics of business load, the round robin algorithm, the least connection algorithm, or the weight-based distribution algorithm is selected as the load balancing algorithm for the SAN storage, and specifically comprises:

[0095] The load difference threshold of the peak and trough periods of the business load and the variance threshold of the read-write speed of each node server in the SAN storage network are pre-set;

[0096] It is determined whether the load difference of the peak and trough periods of the business load is greater than the pre-set load difference threshold. If yes, the weight-based distribution algorithm is selected as the load balancing algorithm for the SAN storage, and if no, no output is made;

[0097] It is determined whether the variance of the read-write speed of each node server in the SAN storage network is greater than the pre-set variance threshold. If yes, the least connection algorithm is selected as the load balancing algorithm for the SAN storage, and if no, the round robin algorithm is selected as the load balancing algorithm for the SAN storage.

[0098] According to historical business load data, the load difference threshold of the peak and trough periods of the business load is pre-set, which is used to determine whether the fluctuation of the business load is significant. The variance threshold of the read-write speed of each node server in the SAN storage network is pre-set, which is used to evaluate whether the performance difference between the node servers is significant.

[0099] Referring to Figure 4 The corresponding SAN storage load balancing algorithm is run, and specifically comprises:

[0100] The load balancer receives data read-write requests from the client;

[0101] The pre-set load balancing algorithm is obtained;

[0102] In the round robin algorithm, the load balancer obtains a list of node servers and traverses the list of node servers in a pre-set order;

[0103] For each received data read-write request, the load balancer distributes it to the currently traversed node server;

[0104] When traversing to the last node server of the list, the load balancer re-traverses from the first node server of the list;

[0105] In the least connection number algorithm, the load balancer obtains the current connection number of each node server;

[0106] The load balancer selects the node server with the least current connection number to process the new data read / write request;

[0107] The data read / write request is distributed to the selected node server, and the connection number of the node server is updated;

[0108] In the weight-based allocation algorithm, the administrator sets a weight value for each node server based on the storage capacity and performance requirements of the node server;

[0109] The load balancer calculates the request proportion received by each node server according to the preset weight value;

[0110] The load balancer selects the node server receiving the current data read / write request based on the calculated request proportion received;

[0111] The data read / write request is distributed to the selected node server, and the weight value and request proportion of each node server are updated.

[0112] The load balancer maintains a configuration inside to specify the currently used load balancing algorithm. When receiving a request, the load balancer first reads this configuration to determine the algorithm to be used (round robin algorithm, least connection number algorithm or weight-based allocation algorithm).

[0113] Referring to Figure 5 The load balancing device is configured in the SAN network, and a virtual IP is created on the load balancing device, which is used as an entry point for clients to access SAN storage. Specifically, it includes:

[0114] Obtain the login credentials of the load balancing device, including the username and password;

[0115] Use the login credentials to log in to the command line interface of the load balancing device through a remote login tool;

[0116] Configure the network interface on the load balancing device to communicate data with other devices in the SAN network;

[0117] On the load balancing device, create a virtual IP address, which is used as an entry point for clients to access SAN storage;

[0118] Set the subnet mask and gateway attributes of the virtual IP to communicate data with other devices in the SAN network;

[0119] Using a client device, accessing the SAN storage through a virtual IP address, and testing the effectiveness of the load balancing configuration;

[0120] Determining whether the client's request can be correctly distributed to each node server and the returned data is accurate, if yes, no output is made, if not, checking the load balancing algorithm process of the SAN storage.

[0121] During the entire configuration process, it is necessary to keep a backup of the configuration so that it can be quickly restored in case of problems, when verifying the load balancing configuration, it is recommended to use multiple different types of client requests to ensure the comprehensiveness of the test, monitoring and logging are important means to verify the effectiveness of the load balancing configuration, and it is necessary to enable and check regularly.

[0122] Referring to Figure 6 , configuring a node pool and adding storage nodes in the SAN network to the node pool of the load balancing device, the load balancer processes the client's request by scheduling the storage nodes, specifically including:

[0123] Scanning the devices in the SAN network and obtaining their IP addresses and port number information;

[0124] Entering the IP addresses and port number information of the storage nodes in the configuration interface of the node pool;

[0125] The load balancer receives the client's request through its virtual IP address;

[0126] After the storage node receives the request, it processes the request and returns the result to the load balancer, and the load balancer forwards the result to the client.

[0127] Using the monitoring function of the load balancer, real-time monitoring of the state of the storage node and the performance indicators of the load balancer, configuring a failover mechanism, when a certain storage node fails, the load balancer can automatically switch the request to other healthy storage nodes, regularly checking the configuration and state of the storage node and the load balancer to ensure system stability and reliability.

[0128] Referring to Figure 7 , real-time monitoring of the load condition of the load balancing device and the node health status, and based on the monitoring results and changes in business requirements, real-time adjustment of the load balancing strategy, specifically including:

[0129] In the configuration interface of the node pool, set the check frequency and response time threshold parameters, and select HTTP request as the check method;

[0130] The load balancing device sends a health check request to the storage node based on the check frequency;

[0131] Judge the health state of the storage node based on the response result;

[0132] Judge whether the storage node cannot respond to the health check request or the response time exceeds the threshold, if yes, mark the storage node as an unhealthy state, remove it from the load balancing algorithm, and perform maintenance, if not, mark the storage node as a healthy state.

[0133] According to the change of business demand and the current load condition, the system administrator can adjust the load balancing strategy, such as changing the load balancing algorithm, adjusting the weight distribution, etc., to optimize the request processing and resource utilization.

[0134] Further, based on the same inventive concept as the above SAN storage-based load balancing service method, the present scheme also proposes a SAN storage-based load balancing service system, comprising:

[0135] A storage environment construction module is configured to determine the required SAN storage capacity and performance requirements based on business demand, select a fiber channel storage area network as a SAN storage environment, and configure SAN shared software, node servers, fiber switches and disk array devices to construct a SAN storage network.

[0136] A load balancing algorithm module is configured to analyze business load, set access mode and data read-write frequency of business system, formulate corresponding load balancing strategy, select round robin algorithm, least connection number algorithm or weight-based distribution algorithm as SAN storage load balancing algorithm based on business load characteristics, and run corresponding SAN storage load balancing algorithm.

[0137] An algorithm stability detection module is configured to configure a load balancing device in the SAN network, create a virtual IP on the load balancing device, use the IP as an entry point for clients to access the SAN storage, configure a node pool, and add storage nodes in the SAN network to the node pool of the load balancing device. The load balancer processes the requests of the clients by scheduling the storage nodes, creates a virtual service on the load balancing device, associates the virtual IP with the storage node pool, configures the virtual service parameters, ensures that the load balancing device has been correctly configured and starts the load balancing service, monitors the load condition and node health status of the load balancing device in real time, and adjusts the load balancing strategy in real time based on the monitoring result and the change of business demand.

[0138] Further, the present scheme also proposes a computer readable storage medium having a computer readable program stored thereon, which executes the above-mentioned production tax and value-added tax approximate estimation method based on big data service when invoked.

[0139] It can be understood that the storage medium can be a magnetic medium, for example, a floppy disk, a hard disk, a magnetic tape, an optical medium, for example, a DVD, or a semiconductor medium, for example, a solid state disk (SSD) and the like.

[0140] In summary, the application has the advantages that: by setting the storage environment construction module, the load balancing algorithm module and the algorithm stability detection module to construct the SAN storage network, the sharing and centralized management of the storage resources are realized, the utilization rate and flexibility of the storage resources are improved, the stable performance of the storage system under high load is ensured, different business scenarios and demands can be more flexibly coped with, potential problems can be found and solved in time, the stable operation of the storage system is ensured, the fault tolerance of the storage system is improved, various sudden situations and faults can be coped with, and the integrity and security of data are ensured.

[0141] The basic principles, main features and advantages of the application are shown and described above. It should be understood by those skilled in the art that the application is not limited by the above examples, and the above examples and descriptions in the specification are only the principles of the application. Without departing from the spirit and scope of the application, various changes and improvements can be made to the application, and these changes and improvements all fall within the scope of the claimed application. The scope of protection required by the application is defined by the appended claims and their equivalents.

Claims

1. A load balancing service method based on SAN storage, characterized in that, The method comprises the following steps: determining the required SAN storage capacity and performance requirements based on business needs; selecting a fiber channel storage area network as the SAN storage environment, and configuring SAN shared software, node servers, fiber switches and disk array devices to build a SAN storage network; analyzing business load, setting access mode and data read-write frequency of the business system, and formulating corresponding load balancing strategies; selecting a round-robin algorithm, a minimum connection number algorithm or a weight-based distribution algorithm as the load balancing algorithm for the SAN storage based on the characteristics of the business load; running the corresponding SAN storage load balancing algorithm; configuring a load balancing device in the SAN network, and creating a virtual IP on the load balancing device, which is used as the entry point for the client to access the SAN storage; configuring a node pool and adding the storage nodes in the SAN network to the node pool of the load balancing device, so that the load balancer schedules the storage nodes to handle the requests from the client; creating a virtual service on the load balancing device, associating the virtual IP with the storage node pool, and configuring virtual service parameters including port number and protocol type; ensuring that the load balancing device has been correctly configured and started the load balancing service; monitoring the load and node health status of the load balancing device in real time, and adjusting the load balancing strategy in real time based on the monitoring results and changes in business needs; The analysis of business load, setting access mode and data read-write frequency of the business system, and formulating corresponding load balancing strategies specifically comprises: monitoring the operation data of the business system; processing and analyzing the collected operation data to identify the peak and valley periods of the business load and the change trend; setting the sequential access mode as the access mode based on the characteristics and needs of the business system; optimizing the disk layout and file system structure based on the sequential access scenario to reduce head movement and data transmission delay; analyzing the characteristics and rules of data read-write frequency, and formulating data read-write strategies based on the read-write demand analysis results; monitoring the read-write performance of the storage system in real time and adjusting and optimizing it according to the actual situation; obtaining the load balancing strategy, which includes a round-robin algorithm, a minimum connection number algorithm or a weight-based distribution algorithm; The selection of a round-robin algorithm, a minimum connection number algorithm or a weight-based distribution algorithm as the load balancing algorithm for the SAN storage based on the characteristics of the business load specifically comprises: presetting the load difference threshold of the peak and valley periods of the business load and the variance threshold of the read-write speed of each node server in the SAN storage network; determining whether the load difference of the peak and valley periods of the business load is greater than the preset load difference threshold, if yes, selecting the weight-based distribution algorithm as the load balancing algorithm for the SAN storage, and if not, not outputting; determining whether the variance of the read-write speed of each node server in the SAN storage network is greater than the preset variance threshold, if yes, selecting the minimum connection number algorithm as the load balancing algorithm for the SAN storage, and if not, selecting the round-robin algorithm as the load balancing algorithm for the SAN storage; The running of the corresponding SAN storage load balancing algorithm specifically comprises: the load balancer receives data read-write requests from the client; Obtaining a preset load balancing algorithm; In the round-robin algorithm, the load balancer obtains a list of node servers, and traverses the list in a preset order; For each received data read-write request, the load balancer distributes it to the currently traversed node server; When the last node server in the list is traversed, the load balancer starts traversing from the first node server in the list again; In the least connection number algorithm, the load balancer obtains the current connection number of each node server; The load balancer selects the node server with the least current connection number to process a new data read-write request; The data read-write request is distributed to the selected node server, and the connection number of the node server is updated; In the weight-based allocation algorithm, an administrator sets a weight value for each node server based on the storage capacity and performance requirements of the node server; The load balancer calculates the request proportion of each node server based on the preset weight value; The load balancer selects a node server to receive the current data read-write request based on the calculated request proportion; The data read-write request is distributed to the selected node server, and the weight value and request proportion of each node server are updated.

2. The SAN storage based load balancing service method of claim 1, wherein, The configuration of the load balancing device in the SAN network and the creation of a virtual IP on the load balancing device, which is used as an entry point for clients to access the SAN storage, specifically includes: Obtaining login credentials for the load balancing device, including a username and password; Logging into the command line interface of the load balancing device using the login credentials through a remote login tool; Configuring the network interface on the load balancing device to communicate data with other devices in the SAN network; Creating a virtual IP address on the load balancing device, which is used as an entry point for clients to access the SAN storage; Setting the subnet mask and gateway attributes of the virtual IP to enable data communication with other devices in the SAN network; Using a client device to access the SAN storage through the virtual IP address and testing the effectiveness of the load balancing configuration; Determining whether the client's request can be correctly distributed to each node server and the returned data is accurate, if yes, no output is made, if not, checking the load balancing algorithm flow of the SAN storage.

3. The SAN storage based load balancing service method of claim 2, wherein, The configuration of the node pool and the addition of the storage nodes in the SAN network to the node pool of the load balancing device, and the load balancer schedules the storage nodes to process the client's request specifically includes: Scanning the devices in the SAN network and obtaining their IP addresses and port number information; Entering the IP address and port number information of the storage node in the configuration interface of the node pool; The load balancer receives the client's request through its virtual IP address; After receiving the request, the storage node processes the request and returns the result to the load balancer, which then forwards the result to the client.

4. The SAN storage based load balancing service method of claim 3, wherein, Real-time monitoring of the load condition of the load balancing device and the node health status, and real-time adjustment of the load balancing strategy based on the monitoring results and changes in business requirements specifically includes: In the configuration interface of the node pool, set the check frequency and response time threshold parameters, and select HTTP request as the check method; The load balancing device sends health check requests to the storage nodes periodically based on the check frequency; Determine the health status of the storage nodes based on the response results; Determine whether the storage nodes cannot respond to the health check requests or the response time exceeds the threshold, and if so, mark the storage nodes as unhealthy, remove them from the load balancing algorithm, and perform maintenance.

5. A load balancing service system based on SAN storage for implementing the load balancing service method based on SAN storage according to any one of claims 1 to 4, characterized in that, Comprise: A storage environment construction module for determining the required SAN storage capacity and performance requirements based on business needs, selecting a fiber channel storage area network as a SAN storage environment, and configuring SAN shared software, node servers, fiber switches, and disk array devices to build a SAN storage network; A load balancing algorithm module for analyzing business load, setting access mode and data read-write frequency of business system, formulating corresponding load balancing strategy, selecting round robin algorithm, least connection number algorithm or weight-based distribution algorithm as SAN storage load balancing algorithm based on business load characteristics, and running corresponding SAN storage load balancing algorithm; An algorithm stability detection module for configuring a load balancing device in the SAN network, creating a virtual IP on the load balancing device, using the IP as the entry point for clients to access the SAN storage, configuring a node pool, and adding storage nodes in the SAN network to the node pool of the load balancing device. The load balancer processes client requests by scheduling the storage nodes. Create a virtual service on the load balancing device, associate the virtual IP with the storage node pool, configure the virtual service parameters, ensure that the load balancing device has been correctly configured and started the load balancing service, monitor the load and node health status of the load balancing device in real time, and adjust the load balancing strategy in real time based on the monitoring results and changes in business needs.

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