Recommended methods, devices, equipment, media, and products for storage management platforms

Abstract

The present application discloses a recommendation method, apparatus, device, medium and product for a storage management platform. According to the historical operation records of the target user on the multiple feature objects, multiple feature objects are sorted, and the content that the target user is most likely to pay attention to can be displayed on the first page first. This personalized display method reduces the time and energy of the user in searching for the required content in massive information, thereby improving the user's work efficiency. In addition, the recommended content is dynamically adjusted according to the user's historical operation records on the multiple feature objects, which can adapt to the operating habits and preferences of different users, making the storage management platform more in line with the actual needs of users and improving users' satisfaction and loyalty to the platform.

Description

Technical Field

[0001] The present application relates to the field of storage management technology, and in particular to methods, devices, equipment, media, and products for recommending storage management platforms. Background Art

[0002] A storage management platform is a user-friendly interface for managing storage devices. It can centrally manage different types of storage devices (such as disk arrays, solid-state storage, network-attached storage (NAS), and storage area networks (SANs). For example, an enterprise might use both traditional mechanical hard drives and high-performance solid-state storage devices. The storage management platform can consolidate these different types of storage devices, making it easier for users to view and allocate storage space.

[0003] In related technologies, the interface elements (such as menus and buttons) on each page of the storage management platform's operational process are fixed. Based on different permissions or different business operations, the system dynamically determines which menu items and buttons are visible. For example, only users with storage pool management permissions can see the "Expand" and "Shrink" buttons. If a user does not have permission for a certain operation, the corresponding button will be hidden or displayed in gray (i.e., unavailable) to prevent user errors. However, current storage management platforms only allow users with the same permissions to view the same information, and can only perform the same operations on all resources, lacking personalized page displays for different users.

[0004] Therefore, how to intuitively provide users with personalized page displays is a problem that needs to be solved urgently. Summary of the Invention

[0005] The present application provides a recommendation method, apparatus, device, medium and product for a storage management platform, so as to at least solve the problem in the related art that the storage management platform lacks personalized page display for different users.

[0006] This application provides a recommended method for a storage management platform, including:

[0007] Receive a login operation from a target user; the login operation is used to log into a storage management platform;

[0008] In response to the login operation, a first page is displayed; the first page includes: multiple feature objects, which are respectively used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

[0009] This application also provides a recommended device for a storage management platform, the device comprising:

[0010] A receiving module, configured to receive a login operation of a target user; the login operation is used to log into the storage management platform;

[0011] A response module is used to display a first page in response to the login operation; the first page includes: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

[0012] The present application also provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of any of the above-mentioned recommended methods for a storage management platform when executing the computer program.

[0013] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned recommendation methods for the storage management platform are implemented.

[0014] The present application also provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned recommended methods for the storage management platform when the computer program is executed by a processor.

[0015] Through the present application, a login operation of a target user is received, wherein the login operation is used to log in to a storage management platform. In response to the login operation of the target user, a first page is displayed, and the first page includes: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform. The display positions of the multiple feature objects in the first page are determined based on the target user's historical operation records on the multiple feature objects. Based on the target user's historical operation records on the multiple feature objects, the multiple feature objects are sorted, and the content that the target user is most likely to pay attention to can be displayed on the first page first. This personalized display method reduces the time and energy of users searching for the required content in massive information, and improves the user's work efficiency. In addition, the recommended content is dynamically adjusted based on the user's historical operation records on multiple feature objects, which can adapt to the operating habits and preferences of different users, making the storage management platform more in line with the user's actual needs and improving the user's satisfaction and loyalty to the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0017] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A flowchart of a recommended method for a storage management platform provided in an embodiment of the present application;

[0019] Figure 2 A schematic diagram of the structure of a recommended device for a storage management platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] It should be noted that, in the description of this application, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. The terms "first," "second," etc., in this application are used to distinguish similar objects, and are not used to describe a particular order or sequence.

[0022] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0023] In the related art, the storage management platform has fixed functions and only displays basic data such as hardware information, alarms, and capacity. Users need to manually jump to module operations, and there is a lack of intelligent recommendations for abnormal alarm states. That is, this method cannot provide users with personalized page recommendation operations, causing users to spend more time searching and performing operations, resulting in low work efficiency. For example, if a storage device has a performance problem, the user needs to first view the alarm information through the alarm module, and then manually enter the performance optimization module to perform operations based on the alarm content. The lack of intelligent recommendations for abnormal alarm states causes users to switch between multiple modules, increasing the complexity and time cost of operations. For another example, permission management only controls the display or hiding of buttons, and cannot dynamically adjust the interface function priority according to the real-time operating status or user habits. Therefore, the current storage management platform is not targeted enough. Users with the same permissions can view the same information and can only perform the same operations on all resources. There is a lack of personalized page display for different users.

[0024] Based on the above problems, an embodiment of the present application provides a recommendation method for a storage management platform, and describes the method in detail in conjunction with the execution process of the recommendation method for the storage management platform.

[0025] Reference Figure 1 As shown, the recommended method of the storage management platform provided by the embodiment of the present invention includes the following steps:

[0026] S11. Receive a login operation from a target user.

[0027] The login operation is used to log into the storage management platform.

[0028] Specifically, the storage management platform receives the target user's login operation. The storage management platform can ask the user whether to remember the target user name when the user logs in for the first time, so that the target user can quickly enter the storage management platform page when logging in later.

[0029] Exemplarily, the target user enters his / her registered user name or email address or other contact information, and login password to complete the login of the storage management platform.

[0030] S12. In response to the login operation, display a first page.

[0031] Among them, the first page includes: multiple feature objects, which are used to trigger the display of different features of the storage management platform respectively, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

[0032] Feature objects can be various functional modules or resources within the storage management platform. For example, feature objects can include volume management, storage pool management, and disk management. Volume management manages operations such as the creation, deletion, and adjustment of storage volumes (vdisks). Storage pool management manages the capacity and performance of storage pools. Disk management monitors and manages disk status and performance.

[0033] Specifically, the storage management device displays the first page in response to the target user's login operation. Based on the historical operation records, a priority score is calculated for each feature object. For example, the priority score can be determined based on factors such as operation frequency, operation results, user preference settings, etc. According to the calculated priority scores, multiple feature objects are sorted and displayed in order on the first page. For example, feature objects with high priority are displayed in a prominent position on the page (such as the top or left side), and feature objects with low priority are displayed in a less prominent position. The display order of feature objects is dynamically adjusted according to the user's operation history. For example, if the user has frequently accessed the volume management module recently, information related to the volume management module will be automatically moved to a more prominent position.

[0034] In some embodiments, before executing the above step S12 (displaying the first page in response to the login operation), the following steps are further executed:

[0035] (1) Obtain the operation frequency and operation mode of each characteristic object in the historical operation record.

[0036] The operation modes include: page viewing record, page configuration record and command line execution record. For example, view the hard disk status through the page, create a volume through the page, delete the management pool through the command line, etc.

[0037] Operation frequency refers to the number of times the target user operates on each feature object. For example, the number of times the target user accesses the volume management module or checks the hard disk status.

[0038] Specifically, the number of operations on each feature object and the specific method of each operation are obtained through the user's behavior log. In addition, after each operation of the target user, the operation frequency and operation method weight in the database are updated in real time.

[0039] (2) According to the operation frequency and operation mode of each characteristic object, the recommendation degree of each characteristic object is obtained.

[0040] Specifically, the recommendation degree can be calculated based on the weight of the operation frequency and the operation method.

[0041] Optionally, the above step (2) can be implemented as follows:

[0042] Obtaining a first weight, a second weight, and a third weight corresponding to the page viewing record, the page configuration record, and the command line execution record, respectively;

[0043] Obtaining a first operation frequency, a second operation frequency, and a third operation frequency of each characteristic object in the page viewing record, the page configuration record, and the command line execution record operation mode respectively;

[0044] A weighted operation is performed on the first operation frequency and the first weight, the second operation frequency and the second weight, and the third operation frequency and the third weight to obtain a recommendation degree for each characteristic object.

[0045] Specifically, weights reflect the importance of different types of operation records in the recommendation calculation. Assume that the first weight corresponding to page view records is W1, the second weight corresponding to page configuration records is W2, and the third weight corresponding to command line execution records is W3. These weights can be set based on actual application scenarios or historical experience. For example, W1 can be 0.4, W2 can be 0.3, and W3 can be 0.3. Operation frequency refers to the number of operations a user performs on each feature object in different types of operation records. The number of page views, configuration operations, and command line executions for each feature object is obtained from the user's behavior log. Assume that the first operation frequency corresponding to page view records is f1, the second operation frequency corresponding to page configuration records is f2, and the third operation frequency corresponding to command line execution records is f3. For example, a user views the volume management page 10 times, performs configuration operations on the volume management page 5 times, and executes volume management-related commands via the command line 3 times.

[0046] The recommendation degree can be calculated by taking the weighted sum of the frequency and weight of different types of operations. The formula can be expressed as: Recommendation degree = W1×f1+W2×f2+W3×f3.

[0047] (3) Sort the plurality of characteristic objects in descending order according to the recommendation degree of each characteristic object, and obtain a sorting result of the plurality of characteristic objects.

[0048] (4) Determine the display position of each feature object in the first page according to the sorting result.

[0049] For example, assume that the target user's operation records for the following feature objects are as follows: (1) The first operation frequency (page viewing record) of volume management is 10 times, the second operation frequency (page configuration record) is 5 times, and the third operation frequency (command line execution record) is 3 times. Therefore, according to the above formula, the recommendation degree of volume management can be calculated as: 0.4×10+0.3×5+0.3×3=4+1.5+0.9=6.4. (2) The first operation frequency (page viewing record) of hard disk management is 8 times, the second operation frequency (page configuration record) is 2 times, and the third operation frequency (command line execution record) is 1 time. Therefore, according to the above formula, the recommendation degree of hard disk management can be calculated as: 0.4×8+0.3×2+0.3×1=3.2+0.6+0.3=4.1. (3) The first operation frequency of pool management (page viewing record) is 6 times, the second operation frequency (page configuration record) is 4 times, and the third operation frequency (command line execution record) is 2 times. Therefore, according to the above formula, the recommendation degree of pool management can be calculated as: 0.4×6+0.3×4+0.3×2=2.4+1.2+0.6=4.2. According to the calculated recommendation degree, the above three feature objects are sorted in descending order. The sorting results are: volume management, pool management, hard disk management. Therefore, according to the sorting results, the feature objects can be displayed on the first page in descending order of recommendation degree.

[0050] By obtaining the frequency and method of operations from the user's historical operation records, the recommendation level of each feature object is calculated, and the feature objects are sorted in descending order based on the recommendation level, ultimately determining the display position of the feature object on the first page. This personalized display method based on user behavior can significantly improve the user experience, help users quickly find the content they are most interested in, and improve work efficiency.

[0051] By comprehensively analyzing various operation records, such as page viewing records, page configuration records, and command line execution records, and assigning different weights to calculate recommendation levels, the storage management platform can more comprehensively reflect users' actual needs and preferences, thereby providing more accurate personalized recommendations. By prioritizing the display of frequently used and high-priority feature objects, the platform can more effectively highlight important information, reduce users' sense of information overload, and improve the efficiency of resource allocation. As user operating habits change, the storage management platform can dynamically adjust the display order of feature objects to promptly adapt to changes in user needs and maintain the platform's flexibility and adaptability. Moreover, users can quickly find the functional modules they care about most, reduce invalid clicks and browsing on the page, and improve operational efficiency.

[0052] In some embodiments, the first page further includes: multiple alarm objects and a recommended repair operation control corresponding to each alarm object, and the display positions of the multiple alarm objects in the first page are determined according to the alarm priorities of the multiple alarm objects.

[0053] By sorting alarm objects by priority and displaying them on the first page, users can immediately see the most important alarm information and its repair operations after logging in, without having to manually search for alarms and repair methods, thereby reducing alarm processing time and improving user experience.

[0054] Furthermore, in some embodiments, before executing the above step S12 (displaying the first page in response to the login operation), the following steps are also executed:

[0055] 1) Obtain the alarm characteristics of each alarm object.

[0056] The alarm characteristics include: alarm time, alarm level, and alarm impact range.

[0057] Specifically, currently unrepaired alarm objects are retrieved from the alarm database. Each alarm object contains the following information: alarm ID, alarm description, alarm occurrence time, alarm severity, alarm impact range, and corresponding repair suggestions. The alarm ID uniquely identifies the alarm object, the alarm description describes the specific problem, the alarm occurrence time indicates the timestamp of the alarm occurrence, the alarm severity is generally classified as emergency, major, warning, general, etc., the alarm impact range includes the object and range of the alarm impact, and the repair suggestion is the recommended repair operation.

[0058] 2) Determine the alarm priority of each alarm object based on the impact of the alarm characteristics on the target storage device.

[0059] Specifically, generally speaking, the earlier the alarm occurs, the higher its priority. The higher the alarm severity, the higher its priority. The wider the impact range of the alarm, the higher its priority.

[0060] Optionally, step 2) above can be implemented as follows:

[0061] Determining, based on the degree of impact of the alarm feature on the target storage device, a weight of the alarm time, a weight of the alarm level, and a weight of the alarm impact range;

[0062] Calculate the total weight of each alarm object based on the alarm time, alarm level, alarm impact range, and the weight of the alarm time, alarm level, and alarm impact range of each alarm object;

[0063] The multiple alarm objects are sorted in descending order according to the total weight of each alarm object to obtain the alarm priority of each alarm object.

[0064] Specifically, the alarm time weight can be calculated by normalizing the alarm occurrence time, the alarm level weight can be assigned a fixed value based on the alarm level (such as emergency: 10, important: 5, warning: 3, general: 2), and the alarm impact range weight can be assigned a weight based on the size of the impact range. The calculation formula for the total weight of the alarm object can be expressed as:

[0065] The total weight of the alarm object = W11 × time weight + W21 × level weight + W31 × impact range weight.

[0066] Among them, W11 represents the weight of the alarm time, W21 represents the weight of the alarm level, and W31 represents the weight of the alarm impact range.

[0067] For example, assume that there are currently three alarm objects: 1) Hard disk alarm: The alarm description is that the IOPS of hard disk 0 is too high. The alarm occurred at 10:00 on June 10, 2025, with an alarm level of important. The scope of impact is: the associated pool (Pool1) and volumes (vdisk1, vdisk2). 2) Storage pool alarm: The alarm description is that the available capacity of storage pool 1 is insufficient. The alarm occurred at 14:00 on June 12, 2025, with an alarm level of warning. The scope of impact is: the associated volumes (vdisk1, vdisk3) and the mapped host (host1). 3) Fiber link alarm: The alarm description is that the storage link to the other end is unstable. The alarm occurred at 12:00 on June 11, 2025, with an alarm level of urgent. The scope of impact is: the remotely replicated volumes (vdisk2, vdisk4) and ports. Assuming the current time is 10:00 AM on June 16, 2025, calculate the number of days between each alarm occurrence and the current time and perform maximum-minimum normalization. The time difference between the hard disk alarm and the storage pool alarm is 6 days, the time difference between the storage pool alarm and the fiber link alarm is 4 days, and the time difference between the fiber link alarm and the disk alarm is 5 days. The maximum time difference is 6 days, and the minimum time difference is 4 days. After normalization, thard disk = (6-4) / (6-4) = 1, tstorage pool = (4-4) / (6-4) = 0, and tfiber link = (5-4) / (6-4) = 0.5. Since different alarm levels are assigned values: emergency = 10, major = 5, warning = 3, and general = 2, the hard disk alarm is 5, the storage pool alarm is 3, and the fiber link alarm is 10. Count the number of categories and associated objects associated with each alarm object. For example, the associated category for a hard disk alarm is 2 (pool, volume), and the associated objects are 3 (Pool1, vdisk1, vdisk2). The associated category for a storage pool alarm is 2 (volume, host), and the associated objects are 3 (vdisk1, vdisk3, host1). The associated category for a fiber link alarm is 2 (volume, port), and the associated objects are 3 (vdisk2, vdisk4, port).

[0068] In the embodiment of the present disclosure, the alarm impact range includes: an associated category and an associated object. The above step (calculating the total weight of each alarm object based on the alarm time, alarm level, alarm impact range of each alarm object, and the weight of the alarm time, the weight of the alarm level, and the weight of the alarm impact range) can also be implemented as follows:

[0069] The total weight of each alarm object is calculated based on the alarm time, alarm level, alarm association category, alarm association object, as well as the weight of the alarm time, the weight of the alarm level, the weight of the alarm association category, and the weight of the alarm association object.

[0070] Since the alarm impact range includes associated categories and associated objects, the total weight of the alarm objects can also be expressed as:

[0071] The total weight of the alarm object = W11 × time weight + W21 × level weight + W32 × associated category weight + W33 × associated object weight.

[0072] Among them, W11 represents the weight of the alarm time, W21 represents the weight of the alarm level, W32 represents the weight of the alarm association category, and W33 represents the weight of the alarm association object.

[0073] Assuming that the value of W11 is 0.4, the value of W21 is 0.4, the value of W32 is 0.1, and the value of W33 is 0.1, the combined weight of each alarm object is calculated according to the following formula: the combined weight of disk alarms is: 0.4 × 1 + 0.4 × 5 + 0.1 × 2 + 0.1 × 3 = 0.4 + 2 + 0.2 + 0.3 = 2.9; the combined weight of storage pool alarms is: 0.4 × 0 + 0.4 × 3 + 0.1 × 2 + 0.1 × 3 = 0 + 1.2 + 0.2 + 0.3 = 1.7; and the combined weight of fiber link alarms is: 0.4 × 0.5 + 0.4 × 10 + 0.1 × 2 + 0.1 × 3 = 0.2 + 4 + 0.2 + 0.3 = 4.7. The multiple alarm objects are sorted in descending order according to the total weight of each alarm object to obtain the alarm priority of each alarm object. That is, the alarm priority sorting result is: optical fiber link alarm, hard disk alarm, storage pool alarm.

[0074] By considering both the associated category and associated objects of an alarm, we can more accurately identify which alarms require priority. For example, even if an alarm for a critical business or high-value data store doesn't have the highest severity level, it may be assigned a higher overall weight due to the importance of the associated objects. By calculating the total weight of alarms, monitoring and response resources can be allocated more efficiently. High-weighted alarms are prioritized, ensuring that critical issues are resolved promptly, thereby reducing potential business disruptions and data loss.

[0075] 3) Sort the multiple alarm objects in descending order according to the alarm priority, and obtain a sorting result of the multiple alarm objects.

[0076] 4) Determine display positions of the multiple alarm objects on the first page according to the sorting results of the multiple alarm objects.

[0077] Specifically, the alarm objects are sorted in descending order based on the calculated alarm priority. Alarm objects with higher priorities are placed first, while alarm objects with lower priorities are placed last. The sorted alarm objects are displayed in order on the first page. A corresponding recommended repair action control (such as a repair button) is displayed next to each alarm object.

[0078] It is understood that the first page can be divided into two main areas: the feature object area, which is used to display the user's most frequently used feature objects, sorted by recommendation; and the alarm object area, which is used to display currently unrepaired alarm objects, sorted by alarm priority. In addition, the alarm objects can be displayed in a list format, and each alarm object can display key information (such as alarm description, alarm level, occurrence time, etc.). At least one repair control can be displayed next to each alarm object, which can be used to perform the repair operation or enter the repair wizard after clicking the repair control.

[0079] By prioritizing alarms and displaying them on the front page, users can quickly identify and address the most important alarms, reducing alarm processing time and improving system stability and reliability. Furthermore, upon logging in, users can immediately see the most important alarm information and remediation actions, eliminating the need to manually search for alarms and remediation methods, thus improving the user experience.

[0080] By comprehensively considering the time, level and impact range of the alarm to calculate the priority, the alarm objects are sorted by priority and displayed on the first page. Users can quickly identify and handle the most important alarms, reduce alarm processing time, and improve system stability and reliability.

[0081] In some embodiments, after executing the above step S12 (displaying the first page in response to the login operation), the following steps may also be executed:

[0082] receiving a first operation of the target user on the target characteristic object on the first page;

[0083] In response to the first operation, obtaining target attribute information of the target characteristic object, and determining whether an attribute value corresponding to the target attribute information exceeds an alarm threshold;

[0084] If the attribute value corresponding to the target attribute information exceeds the alarm threshold, displaying the attribute value corresponding to the target attribute information and a recommended repair control corresponding to the target attribute information on the first page;

[0085] If the attribute value corresponding to the target attribute information does not exceed the alarm threshold, the attribute value corresponding to the target attribute information is displayed on the first page.

[0086] Specifically, when the user operates a target feature object on the first page, the platform needs to receive and identify the operation. For example, the user clicks on a feature object (such as volume management, hard disk management, etc.). The storage management platform responds to the user's operation and obtains relevant attribute information of the target feature object. The attribute information may include: attribute name, current attribute value, and alarm threshold. The alarm threshold is used to determine whether the attribute value is abnormal and can be preset according to the specific application scenario. Determine whether the current attribute value exceeds the alarm threshold. If the current attribute value exceeds the alarm threshold, the alarm logic is triggered; if the current attribute value does not exceed the alarm threshold, the attribute value is displayed normally. If the target attribute value exceeds the alarm threshold, the current attribute value and the recommended repair control are displayed on the first page. The recommended repair control can be an operation button or link for providing repair suggestions.

[0087] Exemplarily, the platform obtains the current attribute value and alarm threshold of the target attribute object from a database or real-time monitoring system. For example: Target attribute object: volume vdisk1, target attribute: IOPS (Input / Output Operations Per Second), which describes the number of read and write operations a storage device can handle in one second, current attribute value: 1500 IOPS, alarm threshold: 1000 IOPS. Because the current attribute value exceeds the alarm threshold, the attribute value: 1500 IOPS is displayed on the first page, along with a recommended repair control: a "Repair IOPS Too High" button. If the current attribute value is 500 IOPS, only the current attribute value: 500 IOPS is displayed on the first page.

[0088] By receiving user operations, obtaining target attribute information, determining whether the attribute value exceeds the alarm threshold, and dynamically adjusting the display content of the first page, the storage management platform can monitor the attribute values ​​of feature objects in real time and immediately notify users when the attribute value exceeds the alarm threshold, helping users to discover and handle problems in a timely manner.

[0089] It should be noted that before determining whether the attribute value corresponding to the target attribute information exceeds the alarm threshold, the relationship between the fields in the command line column and the page column is first learned based on static knowledge. Then, through training on real data returned by the command line, the relationship between dynamic objects is verified and learned, thereby obtaining the associated objects of the attribute objects. Specifically, each page of the storage management platform is traversed to examine the fields displayed in the list. For example, on the volume (vdisk) list page of the storage management platform, fields may include vdiskName (volume name) and poolName (pool name); on the pool list page, fields may include poolName and mdiskName (physical disk name). By comparing these page list fields with the fields returned by the command line, the relationship between the page list fields and the command line fields is determined. For example, if the poolName field in the volume list on the page corresponds to the poolName field returned by the command line "lsvdisk", a one-to-one relationship between the page list column and the command line field can be determined. If a page list field may correspond to multiple command line fields, i.e. a one-to-many relationship, this relationship is also recorded. By analyzing the fields returned by different command lines, the relationship between the fields can be inferred. For example, the lsvdisk command returns the vdiskName and poolName fields, while the lspool command returns the poolName and mdiskName fields. From the association of these fields in different commands, we can infer that the relationship between volumes (vdisks) and pools (pools) is many-to-one (multiple volumes can correspond to one pool), and that the relationship between pools and physical disks (mdisks) may also be many-to-one or one-to-many.

[0090] However, relying solely on command-line parameters and return columns limits the knowledge learned. For example, the command lsvdisk returns fields such as vdiskName (virtual disk name) and poolName (storage pool name); lspool returns fields such as poolName (storage pool name) and mdiskName (physical disk group name); and lsmdisk returns fields such as mdiskName (physical disk group name) and diskType (disk type). Therefore, it's necessary to learn from real-world command-line data. For example, lsvdisk returns rows of data such as: vdisk1, pool1; vdisk2, pool2; vdisk3, pool1; lspool returns rows of data such as: pool1, mdisk1; pool2, mdisk2; and lsmdisk returns rows of data such as: mdisk1, HDD; mdisk2, SSD. The relationship between command-line fields inferred by the model is verified by checking whether a specific real-world name appears in each command line. The associated categories of each feature object and the associated objects within each category are also recorded.

[0091] For example, when traversing the data returned by all the current query commands, when traversing lsvdisk, you can get the associative array of vdisk1: {pool:[pool1]}, the associative array of vdisk2: {pool:[pool2]}, the associative array of vdisk3: {pool:[pool1]}, and according to the data returned by lsvdisk, you can get the associative array of pool1: {vdisk:[vdisk1,vdisk3]}, the associative array of pool2: {vdisk :[vdisk2]}. When traversing lspool, the data of the vdisks associated with the pools in lsvdisk is merged, resulting in an associative array for pool1: {mdisk:[mdisk1], vdisk:[vdisk1, vdisk3]}; an associative array for pool2: {mdisk:[mdisk2], vdisk:[vdisk2]}; and an associative array for pool3: {mdisk:[], vdisk:[]}. This indicates that pool3 is an empty pool. When pool3 is selected on the page, the recommended action is to add an mdisk. This verifies the relationship between the vdiskName, poolName, and mdiskName fields in the command line, and indicates which vdisks are associated with which pools, and which pools are associated with which mdisks, in the actual storage environment. This lays the foundation for resolving the alarm.

[0092] Furthermore, in some embodiments, in response to the target user's operation on the recommended repair control, a repair strategy of the recommended repair control is acquired; and a repair operation is performed according to the repair strategy.

[0093] Specifically, the storage management platform needs to monitor the target user's click event on the recommended repair control (such as the "Repair High IOPS" button). When the user clicks the repair control, the storage management platform captures the event and triggers the subsequent repair process.

[0094] For example, when a user clicks a repair control, the platform needs to obtain the control's unique identifier (such as the repair control ID or the associated alarm ID). Based on the repair control identifier or the associated alarm ID, it retrieves the corresponding repair strategy from a static knowledge base. After obtaining the repair strategy, the platform combines current real-time data (such as the status of associated objects and system configuration) to generate specific repair steps. The platform automatically executes the repair operation based on the generated repair steps. The repair operation can be implemented by calling a background script (such as a Shell script or Python script) to execute the repair operation, or by calling the storage system's API to execute the repair operation.

[0095] By responding to user operations on recommended repair controls, the storage management platform can automatically obtain repair strategies and execute repair operations, reducing the time and workload of users' manual repairs and improving repair efficiency.

[0096] In some embodiments, the first page further includes: a plurality of jump controls, and the plurality of jump controls are respectively used to trigger a jump to a different performance monitoring page.

[0097] receiving an operation of the target user on the first jump control;

[0098] In response to the target user's operation on the first jump control, jump to the first performance monitoring page; the first performance monitoring page includes: multiple operation controls corresponding to multiple attributes of the first performance, the first performance is the performance corresponding to the first performance monitoring page, and the operation control is used to trigger the display of different attributes of the first performance. The display positions of the multiple operation controls of each attribute in the first performance monitoring page are determined based on the page configuration records and command line execution records of the target user for the multiple operation controls.

[0099] Specifically, when the user clicks the first jump control, the platform responds to the operation and jumps the user from the current page (such as the first page) to the first performance monitoring page. The first performance monitoring page is specifically used to display multiple performance-related properties and their operation controls. The first performance monitoring page contains multiple operation controls, each of which corresponds to an attribute of the first performance. For example, CPU usage, memory usage, throughput, latency, etc. The operation control for each attribute can be a button, drop-down box or other interactive element to trigger a detailed display of the attribute. The display position of the operation control in the first performance monitoring page is dynamically determined based on the target user's historical operation records of these operation controls (page configuration records and command line execution records).

[0100] The storage management platform analyzes user behavior data and dynamically adjusts the display order of operation controls, thereby improving its intelligence level and better meeting users' personalized needs.

[0101] Optionally, before jumping to the first performance monitoring page in response to the target user's operation on the first jump control, the following steps may be further performed:

[0102] Obtaining page configuration records and command line execution records of each operation control by the target user on the first performance monitoring page;

[0103] respectively obtaining the operation frequency of each operation control in the page configuration record and the command line execution record;

[0104] Obtaining a recommendation degree for each operation control according to the operation frequency;

[0105] sorting the plurality of operation controls in descending order according to the recommendation degree of each operation control, and obtaining a sorting result of the plurality of operation controls;

[0106] According to the sorting result of the multiple operation controls, display positions of the multiple operation controls of the respective attributes in the first performance monitoring page are determined.

[0107] Exemplarily, the configuration operation records of the user on the first performance monitoring page are obtained from the database. These records include the number of configuration operations performed by the user on each operation control, for example: the user adjusts the frequency of IOPS display: 5 times, the user configures the display mode of throughput: 3 times, and the user adjusts the display setting of latency: 2 times. The records of performance-related operations performed by the user through the command line are obtained from the database. These records include the number of command line operations performed by the user on each operation control. For example: the number of times the user queries IOPS through the command line: 3 times, the user adjusts the throughput configuration through the command line: 2 times, and the number of times the user checks the latency through the command line: 1 time. The recommendation formula for the operation control can be expressed as:

[0108] Recommendation degree = W21 × page configuration operation frequency + W22 × command line execution operation frequency.

[0109] W21 represents the weight of the page configuration operation frequency, and W22 represents the weight of the command line execution operation frequency. Assuming W21 is 0.6 and W22 is 0.4, the recommendation level for each control is calculated using the following formula: the IOPS control's recommendation level is: 0.6 × 5 + 0.4 × 3 = 3 + 1.2 = 4.2; the throughput control's recommendation level is: 0.6 × 3 + 0.4 × 2 = 1.8 + 0.8 = 2.6; and the latency control's recommendation level is: 0.6 × 2 + 0.4 × 1 = 1.2 + 0.4 = 1.6. The control levels are sorted in descending order based on the calculated recommendation levels: IOPS control, throughput control, and latency control. Based on the sorting results, the control levels are displayed on the first performance monitoring page in descending order of recommendation level.

[0110] Furthermore, in some embodiments, an operation of the target user on the target attribute on the first performance monitoring page is received; and in response to the operation on the target attribute, a plurality of operation controls corresponding to the target attribute are displayed on the first performance monitoring page.

[0111] For example, assuming that the user clicks the "View IOPS Details" button on the first performance monitoring page, the storage management platform needs to perform the following steps: the storage management platform detects that the user has clicked the "View IOPS Details" button and identifies the target attribute as IOPS. Operation controls related to the IOPS attribute are obtained from the configuration file or database: a button to view IOPS historical data, a button to adjust IOPS thresholds, and a button to export IOPS data. These operation controls are dynamically rendered on the first performance monitoring page. For example, a "View IOPS Historical Data" button is displayed in a certain area of ​​the page, an "Adjust IOPS Thresholds" button is displayed in another area of ​​the page, and an "Export IOPS Data" button is displayed in another area of ​​the page.

[0112] The storage management platform recommendation method provided by the embodiment of the present disclosure receives a login operation of a target user, wherein the login operation is used to log in to the storage management platform, and in response to the login operation of the target user, displays a first page, the first page including: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the target user's historical operation records on the multiple feature objects. Based on the target user's historical operation records on the multiple feature objects, the multiple feature objects are sorted, and the content that the target user is most likely to pay attention to can be displayed on the first page first. This personalized display method reduces the time and energy of users searching for the required content in massive information, and improves the user's work efficiency. In addition, the recommended content is dynamically adjusted based on the user's historical operation records on the multiple feature objects, which can adapt to the operating habits and preferences of different users, making the storage management platform more in line with the actual needs of users and improving users' satisfaction and loyalty to the platform.

[0113] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.

[0114] Figure 2 This is a structural diagram of a storage management platform recommendation device 200 provided by the present disclosure, such as Figure 2 As shown, the device of this embodiment includes:

[0115] Receiving module 210, configured to receive a login operation of a target user; the login operation is used to log into the storage management platform;

[0116] The response module 220 is used to display a first page in response to the login operation; the first page includes: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

[0117] As an optional implementation of the embodiment of the present disclosure, the apparatus further includes a first determining module, the first determining module including:

[0118] an acquisition unit, configured to acquire the operation frequency and operation mode of each characteristic object in the historical operation record;

[0119] a calculation unit, configured to obtain a recommendation degree of each characteristic object according to an operation frequency and an operation mode of each characteristic object;

[0120] a first sorting unit, configured to sort the plurality of characteristic objects in descending order according to the recommendation degree of each characteristic object, and obtain a sorting result of the plurality of characteristic objects;

[0121] The first determining unit is configured to determine a display position of each characteristic object in the first page according to the sorting result.

[0122] As an optional implementation of the embodiment of the present disclosure, the operation mode includes: page viewing record, page configuration record and command line execution record;

[0123] The computing unit is specifically configured to:

[0124] Obtaining a first weight, a second weight, and a third weight corresponding to the page viewing record, the page configuration record, and the command line execution record, respectively;

[0125] Obtaining a first operation frequency, a second operation frequency, and a third operation frequency of each characteristic object in the page viewing record, the page configuration record, and the command line execution record operation mode respectively;

[0126] A weighted operation is performed on the first operation frequency and the first weight, the second operation frequency and the second weight, and the third operation frequency and the third weight to obtain a recommendation degree for each characteristic object.

[0127] As an optional implementation of the embodiment of the present disclosure, the first page also includes: multiple alarm objects and recommended repair operation controls corresponding to each alarm object, and the display positions of the multiple alarm objects in the first page are determined according to the alarm priorities of the multiple alarm objects.

[0128] As an optional implementation of the embodiment of the present disclosure, the apparatus further includes a second determining module, and the second determining module includes:

[0129] A feature acquisition unit is used to acquire the alarm features of each alarm object; the alarm features include: alarm time, alarm level, and alarm impact range;

[0130] a priority determination unit, configured to determine the alarm priority of each alarm object according to the degree of influence of the alarm characteristics on the target storage device;

[0131] A second sorting unit is configured to sort the multiple alarm objects in descending order according to the alarm priorities, and obtain a sorting result of the multiple alarm objects;

[0132] The second determining unit is configured to determine display positions of the multiple alarm objects on the first page according to the sorting results of the multiple alarm objects.

[0133] As an optional implementation of the embodiment of the present disclosure, the priority determination unit is specifically configured to:

[0134] Determining, based on the degree of impact of the alarm feature on the target storage device, a weight of the alarm time, a weight of the alarm level, and a weight of the alarm impact range;

[0135] Calculate the total weight of each alarm object based on the alarm time, alarm level, alarm impact range, and the weight of the alarm time, alarm level, and alarm impact range of each alarm object;

[0136] The multiple alarm objects are sorted in descending order according to the total weight of each alarm object to obtain the alarm priority of each alarm object.

[0137] As an optional implementation of the embodiment of the present disclosure, the device further includes a judgment module, which is specifically configured to:

[0138] receiving a first operation of the target user on the target characteristic object on the first page;

[0139] In response to the first operation, obtaining target attribute information of the target characteristic object, and determining whether an attribute value corresponding to the target attribute information exceeds an alarm threshold;

[0140] If the attribute value corresponding to the target attribute information exceeds the alarm threshold, displaying the attribute value corresponding to the target attribute information and a recommended repair control corresponding to the target attribute information on the first page;

[0141] If the attribute value corresponding to the target attribute information does not exceed the alarm threshold, the attribute value corresponding to the target attribute information is displayed on the first page.

[0142] As an optional implementation of the embodiment of the present disclosure, the device further includes a repair module, which is specifically configured to:

[0143] In response to the target user's operation on the recommended repair control, obtaining a repair strategy for the recommended repair control;

[0144] Perform a repair operation according to the repair strategy.

[0145] As an optional implementation of the embodiment of the present disclosure, the first page further includes: multiple jump controls, each of which is used to trigger a jump to a different performance monitoring page; the device further includes a jump module, which is specifically used to:

[0146] receiving an operation of the target user on the first jump control;

[0147] In response to the target user's operation on the first jump control, jump to the first performance monitoring page; the first performance monitoring page includes: multiple operation controls corresponding to multiple attributes of the first performance, the first performance is the performance corresponding to the first performance monitoring page, and the operation control is used to trigger the display of different attributes of the first performance. The display positions of the multiple operation controls of each attribute in the first performance monitoring page are determined based on the page configuration records and command line execution records of the target user for the multiple operation controls.

[0148] As an optional implementation of the embodiment of the present disclosure, the apparatus further includes a third determining module, wherein the third determining module is specifically configured to:

[0149] Obtaining page configuration records and command line execution records of each operation control by the target user on the first performance monitoring page;

[0150] respectively obtaining the operation frequency of each operation control in the page configuration record and the command line execution record;

[0151] Obtaining a recommendation degree for each operation control according to the operation frequency;

[0152] sorting the plurality of operation controls in descending order according to the recommendation degree of each operation control, and obtaining a sorting result of the plurality of operation controls;

[0153] According to the sorting result of the multiple operation controls, display positions of the multiple operation controls of the respective attributes in the first performance monitoring page are determined.

[0154] As an optional implementation of the embodiment of the present disclosure, the device further includes a display module, and the display module is specifically configured to:

[0155] receiving an operation of the target user on the target attribute on the first performance monitoring page;

[0156] In response to the operation on the target attribute, multiple operation controls corresponding to the target attribute are displayed on the first performance monitoring page.

[0157] For the description of the features in the embodiment corresponding to the recommendation device 200 of the storage management platform, please refer to the relevant description of the embodiment corresponding to the recommendation method of the storage management platform, which will not be repeated here.

[0158] The recommendation device of the storage management platform provided by the embodiment of the present disclosure receives a login operation of a target user, wherein the login operation is used to log in to the storage management platform, and in response to the login operation of the target user, displays a first page, the first page including: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects. Based on the historical operation records of the target user on the multiple feature objects, the multiple feature objects are sorted, and the content that the target user is most likely to pay attention to can be displayed on the first page first. This personalized display method reduces the time and energy of users searching for the required content in massive information, thereby improving the work efficiency of users. In addition, the recommended content is dynamically adjusted based on the historical operation records of the user on the multiple feature objects, which can adapt to the operating habits and preferences of different users, making the storage management platform more in line with the actual needs of users and improving users' satisfaction and loyalty to the platform.

[0159] An embodiment of the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above-mentioned recommended method embodiments of the storage management platform.

[0160] An embodiment of the present application further provides a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps of any of the above-mentioned recommended method embodiments of the storage management platform when running.

[0161] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0162] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps in any of the above-mentioned recommended method embodiments of the storage management platform are implemented.

[0163] An embodiment of the present application also provides another computer program product, including a non-volatile computer-readable storage medium, the non-volatile computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, implementing the steps in any of the above-mentioned recommended method embodiments of the storage management platform.

[0164] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0165] The above is a detailed introduction to the recommended methods, devices, equipment, media and products of a storage management platform provided by this application. Specific examples are used herein to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the methods and core ideas of this application. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the scope of protection of the claims of this application.

Claims

1. A method for recommending a storage management platform, characterized in that: The method comprises: Receive a login operation from a target user; the login operation is used to log into a storage management platform; Obtain the operation frequency and operation mode of each feature object in the historical operation record; the operation mode includes: page viewing record, page configuration record and command line execution record; Obtaining a first weight, a second weight, and a third weight corresponding to the page viewing record, the page configuration record, and the command line execution record, respectively; Obtaining a first operation frequency, a second operation frequency, and a third operation frequency of each characteristic object in the page viewing record, the page configuration record, and the command line execution record operation mode respectively; Performing a weighted operation on the first operation frequency and the first weight, the second operation frequency and the second weight, and the third operation frequency and the third weight to obtain a recommendation degree for each characteristic object; Sort the characteristic objects in descending order according to their recommendation degrees, and obtain a sorting result of the plurality of characteristic objects; Determining a display position of each feature object on the first page according to the sorting result; In response to the login operation, a first page is displayed; the first page includes: multiple feature objects, which are respectively used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

2. The storage management platform recommendation method according to claim 1, characterized in that: The first page further includes: multiple alarm objects and a recommended repair operation control corresponding to each alarm object. The display positions of the multiple alarm objects in the first page are determined according to the alarm priorities of the multiple alarm objects.

3. The storage management platform recommendation method according to claim 2, characterized in that: Before displaying the first page, the method further includes: Acquire alarm characteristics of each alarm object; the alarm characteristics include: alarm time, alarm level, and alarm impact range; Determining the alarm priority of each alarm object according to the impact of the alarm characteristics on the target storage device; Sort the multiple alarm objects in descending order according to the alarm priorities, and obtain a sorting result of the multiple alarm objects; According to the sorting results of the multiple alarm objects, display positions of the multiple alarm objects on the first page are determined.

4. The storage management platform recommendation method according to claim 3, characterized in that: Determining the alarm priority of each alarm object according to the impact degree of the alarm characteristics on the target storage device includes: Determining, based on the degree of impact of the alarm feature on the target storage device, a weight of the alarm time, a weight of the alarm level, and a weight of the alarm impact range; Calculate the total weight of each alarm object based on the alarm time, alarm level, alarm impact range, and the weight of the alarm time, alarm level, and alarm impact range of each alarm object; The multiple alarm objects are sorted in descending order according to the total weight of each alarm object to obtain the alarm priority of each alarm object.

5. The storage management platform recommendation method according to claim 1, characterized in that: In response to the login operation, after displaying the first page, the method further includes: receiving a first operation of the target user on the target characteristic object on the first page; In response to the first operation, obtaining target attribute information of the target characteristic object, and determining whether an attribute value corresponding to the target attribute information exceeds an alarm threshold; If the attribute value corresponding to the target attribute information exceeds the alarm threshold, displaying the attribute value corresponding to the target attribute information and a recommended repair control corresponding to the target attribute information on the first page; If the attribute value corresponding to the target attribute information does not exceed the alarm threshold, the attribute value corresponding to the target attribute information is displayed on the first page.

6. The storage management platform recommendation method according to claim 5, characterized in that: The method further comprises: In response to the target user's operation on the recommended repair control, obtaining a repair strategy for the recommended repair control; Perform a repair operation according to the repair strategy.

7. The storage management platform recommendation method according to claim 1, characterized in that: The first page further includes: a plurality of jump controls, each of which is used to trigger a jump to a different performance monitoring page; the method further includes: receiving an operation of the target user on the first jump control; In response to the target user's operation on the first jump control, jump to the first performance monitoring page; the first performance monitoring page includes: multiple operation controls corresponding to multiple attributes of the first performance, the first performance is the performance corresponding to the first performance monitoring page, and the operation control is used to trigger the display of different attributes of the first performance. The display positions of the multiple operation controls of each attribute in the first performance monitoring page are determined based on the page configuration records and command line execution records of the target user for the multiple operation controls.

8. The storage management platform recommendation method according to claim 7, characterized in that: Before jumping to the first performance monitoring page in response to the target user's operation on the first jump control, the method further includes: Obtaining page configuration records and command line execution records of each operation control by the target user on the first performance monitoring page; respectively obtaining the operation frequency of each operation control in the page configuration record and the command line execution record; Obtaining a recommendation degree for each operation control according to the operation frequency; sorting the plurality of operation controls in descending order according to the recommendation degree of each operation control, and obtaining a sorting result of the plurality of operation controls; According to the sorting result of the multiple operation controls, display positions of the multiple operation controls of the respective attributes in the first performance monitoring page are determined.

9. The storage management platform recommendation method according to claim 8, characterized in that: The method further comprises: receiving an operation of the target user on the target attribute on the first performance monitoring page; In response to the operation on the target attribute, multiple operation controls corresponding to the target attribute are displayed on the first performance monitoring page.

10. A recommendation device for a storage management platform, characterized in that: The device comprises: A receiving module, configured to receive a login operation of a target user; the login operation is used to log into the storage management platform; The first determination module is used to obtain the operation frequency and operation mode of each characteristic object in the historical operation record; the operation mode includes: page viewing record, page configuration record and command line execution record; Obtaining a first weight, a second weight, and a third weight corresponding to the page viewing record, the page configuration record, and the command line execution record, respectively; Obtaining a first operation frequency, a second operation frequency, and a third operation frequency of each characteristic object in the page viewing record, the page configuration record, and the command line execution record operation mode respectively; Performing a weighted operation on the first operation frequency and the first weight, the second operation frequency and the second weight, and the third operation frequency and the third weight to obtain a recommendation degree for each characteristic object; Sort the characteristic objects in descending order according to their recommendation degrees, and obtain a sorting result of the plurality of characteristic objects; Determining a display position of each feature object on the first page according to the sorting result; A response module is used to display a first page in response to the login operation; the first page includes: multiple feature objects, each of which is used to trigger the display of different features of the storage management platform, and the display positions of the multiple feature objects in the first page are determined based on the historical operation records of the target user on the multiple feature objects.

11. An electronic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the recommended method for the storage management platform as claimed in any one of claims 1 to 9 when executing the computer program.

12. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method for recommending a storage management platform according to any one of claims 1 to 9 are implemented.

13. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for recommending a storage management platform according to any one of claims 1 to 9 are implemented.

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