Information recommendation method, data processing method, equipment and storage medium

Abstract

The embodiment of the invention provides an information recommendation method, a data processing method, equipment and a storage medium. The method comprises the following steps: acquiring historical use data of a cloud disk; the cloud disk is configured with pre-configured read-write performance and burst read-write performance; the pre-configured read-write performance is charged according to a pre-configured performance value and a charging duration; the burst read-write performance is charged according to the burst read-write frequency of the cloud disk; predicting a target pre-configured performance value meeting a preset cost optimization condition according to the historical use data; and sending recommendation information related to cost optimization to the user according to the target pre-configured performance value. According to the technical scheme provided by the embodiment of the invention, the cost of using the cloud disk by the user can be optimized.

Description

Technical Field

[0001] The present application relates to the field of cloud computing technology, and in particular, to an information recommendation method, a data processing method, a device, and a storage medium. Background Art

[0002] Elastic Compute Service (ECS) is a simple, efficient, secure, and reliable cloud computing service provided by cloud service providers, with elastic scalability of processing capabilities. Block storage (e.g., cloud disk) is a block device product provided by cloud service providers for ECS, which has the characteristics of high performance and low latency, supports random read and write, and meets the data storage requirements in most general business scenarios. Users can format and establish a file system to use the block storage just like using a physical hard disk. After the cloud disk is mounted to an ECS instance, all the pressure borne by the cloud disk comes from the instance it is mounted to; the performance of the cloud disk used by all application programs in the instance will be included in the performance statistics.

[0003] In practical applications, there are such scenarios:

[0004] 1. The cloud disk capacity required by the instance is fixed, but higher cloud disk performance is needed to support the operation of the instance.

[0005] 2. The operation of the instance fluctuates greatly, and peaks appear frequently, requiring the cloud disk to have the ability to handle emergencies.

[0006] To meet the above scenarios, some cloud service providers provide cloud disks that support customizing the pre-configured performance and burst performance of the cloud disk according to business requirements. Such cloud disks can decouple the cloud disk capacity from the cloud disk performance to meet the user's usage requirements. During the operation of the cloud disk, when the pre-configured performance of the cloud disk cannot meet the operation requirements of the instance, the use of burst performance will be triggered. Once the pre-configured performance is enabled, it will be charged according to the billing duration (which can also be understood as the enabled duration), regardless of whether the user uses it or not; the burst performance is charged according to the user's burst read and write times.

[0007] It can be seen that in the prior art, if the user configures the pre-configured performance unreasonably, it will result in a large cost for using the cloud disk. Summary of the Invention

[0008] In view of the above problems, the present application is proposed to provide an information recommendation method, a data processing method, a device, and a storage medium that solve the above problems or at least partially solve the above problems.

[0009] In the first aspect of the present application, an information recommendation method is provided, including:

[0010] Obtain historical usage data of the cloud disk; the cloud disk is configured with pre-configured read / write performance and burst read / write performance; the pre-configured read / write performance is charged according to the pre-configured performance value and the billing duration; the burst read / write performance is charged according to the burst read / write times of the cloud disk; the burst read / write times refer to the read / write times involved in the part where the actually used performance value exceeds the pre-configured performance value;

[0011] Predict a target pre-configured performance value that meets the preset cost optimization condition according to the historical usage data;

[0012] Send recommendation information about cost optimization to the user according to the target pre-configured performance value.

[0013] Optionally, predicting a target pre-configured performance value that meets the preset cost optimization condition according to the historical usage data includes:

[0014] Determine the peak performance actually used by the cloud disk during the historical time period according to the historical usage data;

[0015] When the pre-configured performance value currently configured for the cloud disk is less than the peak performance, determine multiple alternative pre-configured performance values between the pre-configured performance value currently configured for the cloud disk and the peak performance;

[0016] For each alternative pre-configured performance value, determine the adjusted usage cost of the cloud disk during the historical time period when the pre-configured performance value is adjusted to this alternative pre-configured performance value according to the historical usage data;

[0017] When the smallest adjusted usage cost is less than the actual usage cost of the cloud disk during the historical time period, determine the alternative pre-configured performance value corresponding to the smallest adjusted usage cost as the target pre-configured performance value.

[0018] Optionally, determining multiple alternative pre-configured performance values between the pre-configured performance value currently configured for the cloud disk and the peak performance includes:

[0019] Select multiple alternative pre-configured performance values at preset intervals in sequence between the pre-configured performance value currently configured for the cloud disk and the peak performance;

[0020] The preset interval is determined according to the difference between the peak performance and the pre-configured performance value currently configured for the cloud disk.

[0021] Optionally, the multiple alternative pre-configured performance values include a first alternative pre-configured performance value;

[0022] Determining the adjusted usage cost of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the historical usage data includes:

[0023] Determining the adjusted pre-configured read / write performance cost of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the first alternative pre-configured performance value and the duration of the historical time period;

[0024] Determining the adjusted burst read / write times of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the historical usage data;

[0025] Determining the adjusted burst read / write performance cost of the cloud disk during the historical time period according to the adjusted burst read / write times;

[0026] Determining the adjusted usage cost of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the adjusted pre-configured read / write performance cost and the adjusted burst read / write performance cost.

[0027] Optionally, determining the adjusted burst read / write times of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the historical usage data includes:

[0028] Determining the actual burst read / write times and the proportion of the actual burst duration in each time interval among multiple time intervals of the cloud disk according to the historical usage data; the multiple time intervals are obtained by dividing the historical time period;

[0029] Estimating the burst reduction amount of the cloud disk in each time interval when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the difference between the currently configured pre-configured performance value of the cloud disk and the first alternative pre-configured performance value, the duration of each time interval, and the proportion of the burst duration of the cloud disk in each time interval;

[0030] Determining the adjusted burst read / write times of the cloud disk during the historical time period when adjusting the pre-configured performance value to the first alternative pre-configured performance value according to the actual burst read / write times and the burst reduction amount of the cloud disk in each time interval among multiple time intervals.

[0031] Optionally, it further includes:

[0032] When the minimum adjusted usage cost is greater than or equal to the actual usage cost of the cloud disk during the historical time period, no recommendation information regarding cost optimization is sent to the user.

[0033] Optionally, according to the historical usage data, predicting a target preconfigured performance value that meets the preset cost optimization condition in a future time period further includes:

[0034] If the preconfigured performance value currently configured for the cloud disk is greater than the performance peak value, determine the performance peak value as the target preconfigured performance value that meets the preset cost optimization condition.

[0035] Optionally, the preconfigured read / write performance includes: preconfigured IOPS performance; the burst read / write performance includes: burst IOPS performance.

[0036] In a second aspect of the present application, a data processing method is provided, including:

[0037] Obtain the historical usage data of the cloud disk; the cloud disk is configured with preconfigured read / write performance and burst read / write performance; the preconfigured read / write performance is charged according to the preconfigured performance value and the charging duration; the burst read / write performance is charged according to the burst read / write times of the cloud disk; the burst read / write times refer to the read / write times involved in the part where the actually used performance value exceeds the preconfigured performance value;

[0038] Predict a target preconfigured performance value that meets the preset cost optimization condition according to the historical usage data.

[0039] Optionally, predicting a target preconfigured performance value that meets the preset cost optimization condition according to the historical usage data includes:

[0040] Determine the performance peak value actually used by the cloud disk in the historical time period according to the historical usage data;

[0041] When the preconfigured performance value currently configured for the cloud disk is less than the performance peak value, determine multiple alternative preconfigured performance values between the preconfigured performance value currently configured for the cloud disk and the performance peak value;

[0042] For each alternative preconfigured performance value, determine the adjusted usage cost of the cloud disk in the historical time period when the preconfigured performance value is adjusted to this alternative preconfigured performance value according to the historical usage data;

[0043] When the minimum adjusted usage cost is less than the actual usage cost of the cloud disk in the historical time period, determine the alternative preconfigured performance value corresponding to the minimum adjusted usage cost as the target preconfigured performance value.

[0044] In a third aspect of the present application, an electronic device is provided. The electronic device includes: a memory and a processor, wherein,

[0045] The memory is used to store programs;

[0046] The processor, coupled to the memory, is configured to execute the program stored in the memory to implement the method described in any one of the above.

[0047] In a fourth aspect of the present application, there is provided a computer-readable storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the numerical method described in any one of the above.

[0048] In the technical solution provided by the embodiments of the present application, historical usage data of the cloud disk is obtained; according to the historical usage data of the cloud disk, a reasonable pre-configured performance value within a future time period can be predicted relatively accurately, and this pre-configured performance value is recommended to the user. In this way, when the user configures the pre-configured read / write performance of the cloud disk according to the recommended pre-configured performance value, not only can the cost of the user using the cloud disk be optimized.

[0049] In the technical solution provided by the embodiments of the present application, historical usage data of the cloud disk is obtained; according to the historical usage data of the cloud disk, a reasonable pre-configured performance value within a future time period can be predicted relatively accurately. In this way, by configuring the pre-configured read / write performance of the cloud disk according to the recommended pre-configured performance value, the cost of the user using the cloud disk can be optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0051] Figure 1 It is a schematic flowchart of an information recommendation method provided by an embodiment of the present application;

[0052] Figure 2 It is an example diagram of a performance value curve required for the operation of a cloud disk provided by an embodiment of the present application;

[0053] Figure 3 It is an interaction schematic diagram of an information recommendation method provided by an embodiment of the present application;

[0054] Figure 4 It is a schematic flowchart of a data processing method provided by an embodiment of the present application;

[0055] Figure 5 It is a block diagram of the structure of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] To enable those skilled in the art to better understand the solution of this application, the technical solution in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of this application.

[0057] In addition, in some processes described in the specification, claims and the above-mentioned accompanying drawings of this application, a plurality of operations that appear in a specific order are included. These operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., do not represent a sequence, and do not limit that "first" and "second" are of different types.

[0058] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties. And the collection, use and processing of relevant data need to comply with the relevant laws, regulations and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0059] First, the vocabulary involved in the embodiments of this application will be described. It can be understood that this description is for a clearer understanding of the embodiments of this application and does not necessarily constitute a limitation on the embodiments of this application.

[0060] Input / Output Operations Per Second (IOPS), that is, the number of read / write (IO) requests that can be processed per second, which is one of the main values for measuring storage performance.

[0061] Pre-configured performance (that is, pre-configured read / write performance): refers to the performance pre-configured for the cloud disk. In the embodiments of this application, the pre-configured performance is the sum of the benchmark performance provided by the cloud disk and the additional performance customized by the user on top of the benchmark performance; among them, the benchmark performance provided by the cloud disk can be understood as the performance built into the cloud disk, and the size of this performance is fixed and unchangeable, and the user cannot customize it.

[0062] Burst performance (that is, burst read / write performance): This performance automatically increases with the increase in demand.

[0063] The following will combine Figure 1 to introduce the information recommendation method provided by the embodiments of this application. The execution subject of this method can be a server. Among them, the server can be a common server, a cloud server, a virtual server, etc., and the embodiments of this application do not make specific limitations on this. As Figure 1 shown, this method includes:

[0064] 101. Obtain the historical usage data of the cloud disk.

[0065] Among them, the cloud disk is configured with pre-configured performance and burst performance; the pre-configured performance is billed according to the pre-configured performance value and the billing duration; the burst performance is billed according to the burst read / write times of the cloud disk; the burst read / write times refer to the read / write times involved in the part where the actually used performance value exceeds the pre-configured performance value.

[0066] It should be noted that the performance value in this article refers to the read / write performance value.

[0067] 102. According to the historical usage data, predict the target pre-configured performance value that meets the preset cost optimization condition in the future time period.

[0068] 103. According to the target pre-configured performance value, send recommendation information about cost optimization to the user.

[0069] In the above 101, in one example, the pre-configured performance can be the pre-configured IOPS performance; the burst performance can be the burst IOPS performance. In another example, the pre-configured performance can be the pre-configured throughput performance; the burst performance can be the burst throughput performance. Generally speaking, the IOPS performance and the throughput performance are related to each other. Therefore, in practical applications, only one of them needs to be selected for billing.

[0070] The historical usage data of the cloud disk can include: the historical usage data of the cloud disk in the historical time period. Among them, the start point and the end point of the historical time period can be set according to actual needs, and the embodiments of this application do not make specific limitations on this. Generally speaking, the closer the historical time period is to the current, the more the usage data of the cloud disk in this historical time period can reflect the next usage situation of the cloud disk. Therefore, the above historical time period can be a recent period of time in history, such as: the most recent month, the most recent week, the most recent three days, etc.

[0071] In one example, the historical usage data can include: historical usage record data, such as: the actually used performance value of the cloud disk in each sub-time interval (such as: per second), such as: the actually used IOPS of the cloud disk per second. Specifically, during the operation of the cloud disk, the performance value currently used by the cloud disk can be recorded every sub-time interval.

[0072] In another example, the historical usage data may include: data obtained by processing the historical usage record data.

[0073] Based on the historical usage record data of the cloud disk and the preconfigured performance value of the current configuration of the cloud disk, the number of burst read / write operations per time interval (e.g., per hour) of the cloud disk within a historical time period can be determined. The time interval is greater than the sub-time interval. Specifically, the time interval is an integer multiple of the sub-time interval.

[0074] The number of burst read / write operations of the cloud disk per time interval is: the sum of the number of burst read / write operations of the cloud disk in each sub-time interval within that time interval. The number of burst read / write operations of the cloud disk in a sub-time interval is the product of the burst performance value of the cloud disk in that sub-time interval and the duration of the sub-time interval. The burst performance value of the cloud disk in that sub-time interval is the part by which the performance value actually used by the cloud disk in that sub-time interval exceeds the preconfigured performance value of the current configuration of the cloud disk. It should be noted that if the performance value actually used by the cloud disk in a certain sub-time interval does not exceed the preconfigured performance value of the current configuration of the cloud disk, the burst performance value of the cloud disk in that sub-time interval is zero.

[0075] For ease of understanding, the following is introduced in conjunction with Figure 2 : Figure 2 shows the performance value curve used by the cloud disk. The horizontal axis represents time, with the unit of s; the vertical axis represents the performance value. The number of burst read / write operations of the cloud disk per hour (i.e., the time interval) is also Figure 2 the sum of the areas of regions H1 and H2 in Figure 2 . Exemplarily,

[0076] In addition, based on the historical usage record data of the cloud disk, the peak performance value actually used by the cloud disk within a historical time period can be determined. The peak performance value is also the maximum performance value actually used by the cloud disk within a historical time period. Exemplarily, the historical usage record data of the cloud disk includes: the performance value x1 actually used by the cloud disk at the 1st second, the performance value x2 actually used by the cloud disk at the 2nd second,..., the performance value x n of the cloud disk at the nth second; among them, x1, x2,..., x n in x j is the largest. Therefore, the peak performance value actually used by the cloud disk within a historical time period is x j , where j is one of 1, 2,..., n.

[0077] Optionally, based on the historical usage record data of the cloud disk, the proportion of the burst duration per time interval of the cloud disk within a historical time period can be determined. Exemplarily, the proportion of the burst duration per hour of the cloud disk refers to the ratio h / H of the burst duration h of the cloud disk within that hour to the duration H (i.e., 1 hour) of that hour.

[0078] Exemplarily, the historical usage data may include: the number of burst read / write operations of the cloud disk at each time interval within a historical time period, the peak performance actually used by the cloud disk within the historical time period, and the proportion of the burst duration at each time interval of the cloud disk within the historical time period.

[0079] In one example, the preconfigured performance cost (i.e., the preconfigured read / write performance cost) is determined based on the preconfigured performance value and the billing duration. In practical applications, the preconfigured performance value is the sum of the basic performance value and the additional performance value customized by the user for the cloud disk. Then, the usage cost corresponding to the preconfigured performance is the sum of the basic performance cost and the additional performance cost. Among them, the basic performance cost is related to the billing duration and has nothing to do with the size of the preconfigured performance value; the additional performance cost is related to both the size of the preconfigured performance value and the billing duration, and is specifically positively correlated with the additional performance value customized by the user for the cloud disk, the billing duration, etc. That is, the additional performance cost is determined based on the additional performance value customized by the user for the cloud disk and the billing duration. Specifically, the product of the additional performance unit price, the additional performance value, and the billing duration can be determined as the additional performance cost. Exemplarily, the preconfigured performance cost of the cloud disk within a historical time period is: the sum of the basic performance cost of the cloud disk within the historical time period and the additional performance cost of the cloud disk within the historical time period; among them, the basic performance cost of the cloud disk within the historical time period is the product of the basic performance unit price and the duration of the historical time period (i.e., the billing duration); the additional performance cost of the cloud disk within the historical time period is the product of the additional performance unit price, the additional performance value, and the duration of the historical time period.

[0080] The burst performance cost (i.e., the burst read / write performance cost) is determined based on the burst performance unit price and the number of burst read / write operations of the cloud disk. Specifically, the product of the burst performance unit price and the number of burst read / write operations of the cloud disk can be used as the burst performance cost. Exemplarily, the burst performance cost of the cloud disk within a historical time period is the product of the burst performance unit price and the number of burst read / write operations of the cloud disk within the historical time period; the number of burst read / write operations of the cloud disk within the historical time period refers to the sum of the number of burst read / write operations of the cloud disk at each sub-time interval (e.g., per second) within the historical time period, or the sum of the number of burst read / write operations of the cloud disk at each time interval (e.g., per hour) within the historical time period.

[0081] The actual usage cost of the cloud disk within a historical time period is the sum of the actual preconfigured performance cost of the cloud disk within the historical time period and the actual burst performance cost of the cloud disk within the historical time period.

[0082] In the above step 102, the target usage cost of the cloud disk within the historical time period is calculated based on the historical usage data and the target preconfigured performance value; the target usage cost of the cloud disk within the historical time period is less than the actual usage cost of the cloud disk within the historical time period. The actual usage cost of the cloud disk within the historical time period is calculated based on the historical usage data and the preconfigured performance value currently configured for the cloud disk.

[0083] That is to say, step 102 is to find the target preconfigured performance value that can reduce the usage cost of the cloud disk. Among them, the specific search method will be introduced in detail in the following embodiments.

[0084] In the above step 103, in one example, the target preconfigured performance value can be recommended to the user of the cloud disk.

[0085] In another example, the recommended information regarding cost optimization can be generated based on the difference between the target preconfigured performance value and the basic performance value (i.e., the target additional performance value), and sent to the user of the cloud disk. Exemplarily, the recommended message can be displayed on the user's cloud disk usage interface: "For cloud disk ***, cost optimization can be achieved by configuring an additional 5066 IOPS value. According to your usage in the past 7 days, it is estimated that the cost can be reduced by 50%". Among them, "***" can be the name or number of the cloud disk.

[0086] In practical applications, in addition to sending the recommended information regarding cost optimization to the user through the cloud disk usage interface, other methods such as emails and text messages can also be used to send the recommended information regarding cost optimization to the user. The embodiments of the present application do not make specific limitations on this.

[0087] In the technical solution provided by the embodiments of the present application, the historical usage data of the cloud disk is obtained; based on the historical usage data of the cloud disk, the reasonable preconfigured performance value within the future time period can be predicted more accurately, and this preconfigured performance value is recommended to the user. In this way, when the user configures the preconfigured performance of the cloud disk according to the recommended preconfigured performance value, the cost of the user using the cloud disk can be optimized.

[0088] In a feasible solution, for "predicting the target preconfigured performance value that meets the preset cost optimization condition" in the above step 102, the following steps can be adopted to implement it:

[0089] 1021. Determine the peak performance actually used by the cloud disk within the historical time period according to the historical usage data.

[0090] 1022. Determine a plurality of alternative preconfigured performance values between the preconfigured performance value currently configured for the cloud disk and the peak performance.

[0091] 1023. For each alternative preconfigured performance value, based on the historical usage data, determine the adjusted usage cost of the cloud disk during the historical time period when the preconfigured performance value is adjusted to this alternative preconfigured performance value.

[0092] 1024. When the minimum adjusted usage cost is less than the actual usage cost of the cloud disk during the historical time period, determine the alternative preconfigured performance value corresponding to the minimum adjusted usage cost as the target preconfigured performance value.

[0093] In the above 1021, the specific determination method of the actual usage performance peak of the cloud disk during the historical time period can refer to the corresponding content in the above embodiments, which will not be elaborated here.

[0094] In the above 1022, in a specific example, between the preconfigured performance value currently configured for the cloud disk and the performance peak, multiple alternative preconfigured performance values can be sequentially selected according to a preset interval. Among them, the preset interval can be preconfigured in advance or determined according to the difference between the performance peak and the preconfigured performance value currently configured for the cloud disk. If the preset interval is preconfigured in advance, then its size can be set according to actual experience, and the embodiments of the present application do not make specific limitations on this. If the preset interval is determined according to the difference between the performance peak and the preconfigured performance value currently configured for the cloud disk, then the preset number of alternative preconfigured performance values can be preconfigured in advance, and the preset interval is the ratio of the difference to the preset number.

[0095] That is: the number of alternative preconfigured performance values is negatively correlated with the size of the preset interval, that is: the smaller the preset interval, the more the number of alternative preconfigured performance values. In practical applications, the more the number of alternative preconfigured performance values, the greater the amount of calculation involved in this solution, that is, the more computing resources occupied, and the closer the usage cost corresponding to the finally determined target preconfigured performance value is to the minimum value, that is, the more accurate. Therefore, in practical applications, the size of the preset interval can be flexibly configured according to actual needs.

[0096] In the above 1023, the multiple alternative preconfigured performance values include a first alternative preconfigured performance value; the first alternative preconfigured performance value refers to any one of the multiple alternative preconfigured performance values. In the above 1023, "Based on the historical usage data, determine the adjusted usage cost of the cloud disk during the historical time period when the preconfigured performance value is adjusted to the first alternative preconfigured performance value" can be implemented by the following steps:

[0097] S11. Based on the first alternative preconfigured performance value and the duration of the historical time period, determine the adjusted preconfigured performance cost (that is, the adjusted preconfigured read / write performance cost) of the cloud disk during the historical time period when the preconfigured performance value is adjusted to the first alternative preconfigured performance value.

[0098] S12. Determine the adjusted burst read / write count of the cloud disk during the historical time period when the preconfigured performance value is adjusted to the first alternative preconfigured performance value according to the historical usage data.

[0099] S13. Determine the adjusted burst performance cost (i.e., adjusted burst read / write performance cost) of the cloud disk during the historical time period according to the adjusted burst read / write count.

[0100] S14. Determine the adjusted usage cost of the cloud disk during the historical time period when the preconfigured performance value is adjusted to the first alternative preconfigured performance value according to the adjusted preconfigured performance cost and the adjusted burst performance cost.

[0101] In the above S11, according to the first alternative preconfigured performance value and the duration of the historical time period, determine the adjusted preconfigured performance cost of the cloud disk during the historical time period.

[0102] The difference between the first alternative preconfigured performance value and the basic performance value is the adjusted additional performance value. The adjusted preconfigured performance cost of the cloud disk during the historical time period is the sum of the basic performance cost of the cloud disk during the historical time period and the adjusted additional performance cost of the cloud disk during the historical time period. The adjusted additional performance cost of the cloud disk during the historical time period is the product of the adjusted additional performance value, the additional performance unit price, and the duration of the historical time period.

[0103] In the above S12, according to the historical usage data, determine the adjusted burst read / write count of the cloud disk during the historical time period when the preconfigured performance value is adjusted to the first alternative preconfigured performance value. In one example, the calculation method of the adjusted burst read / write count can refer to the corresponding content in the above embodiments.

[0104] In another example, in order to reduce the calculation amount, the following method can be used to calculate the above adjusted burst read / write count:

[0105] S121. According to the historical usage data, determine the actual burst read / write count and the proportion of the actual burst duration in each time interval among multiple time intervals of the cloud disk.

[0106] Among them, the multiple time intervals are obtained by dividing the historical time period.

[0107] S122. Estimate the burst reduction amount of the cloud disk at each time interval when the pre-configured performance value is adjusted to the first alternative pre-configured performance value (that is, the reduced burst read / write times of the cloud disk at each time interval when the pre-configured performance value is adjusted to the first alternative pre-configured performance value) according to the difference between the pre-configured performance value currently configured for the cloud disk and the first alternative pre-configured performance value, the duration of each time interval, and the proportion of the burst duration of the cloud disk at each time interval.

[0108] S123. Determine the adjusted burst read / write times of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value according to the actual burst read / write times and burst reduction amounts of the cloud disk at each time interval among multiple time intervals.

[0109] In the above S121, the calculation methods of the actual burst read / write times and the proportion of the actual burst duration of the cloud disk at each time interval among multiple time intervals can refer to the corresponding content in the above embodiments.

[0110] Among them, the actual burst read / write times and the proportion of the actual burst duration of the cloud disk at each time interval among multiple time intervals are determined based on the pre-configured performance value currently configured for the cloud disk.

[0111] In the above S122, the first time interval is included in the above multiple time intervals, and the first time interval refers to any one of the multiple time intervals. The product of the difference between the pre-configured performance value currently configured for the cloud disk and the first alternative pre-configured performance value, the duration of the first time interval, and the proportion of the burst duration of the cloud disk in the first time interval is determined as the burst reduction amount of the cloud disk in the first time interval when the pre-configured performance value is adjusted to the first alternative pre-configured performance value.

[0112] Here, the burst reduction amount is corrected using the proportion of the burst duration to ensure that the finally estimated burst reduction amount is close to the actual burst reduction amount, thereby improving the estimation accuracy of the adjusted burst read / write times of the cloud disk during the historical time period.

[0113] In the above S123, the difference between the burst read / write times of the cloud disk in the first time interval and the burst reduction amount of the cloud disk in the first time interval is determined as the adjusted burst read / write times of the cloud disk in the first time interval when the pre-configured performance value is adjusted to the first alternative pre-configured performance value; the sum of the adjusted burst read / write times of the cloud disk at each time interval among the multiple time intervals is determined as the adjusted burst read / write times of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value.

[0114] In the above S13, the product of the adjusted burst read / write times and the burst performance unit price is determined as the adjusted burst performance cost of the cloud disk within the historical time period.

[0115] In the above S14, the sum of the adjusted pre-configured performance cost of the cloud disk within the historical time period and the adjusted burst performance cost of the cloud disk within the historical time period is determined as the adjusted usage cost of the cloud disk within the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value.

[0116] The adjusted usage cost of the cloud disk within the historical time period when the pre-configured performance value is adjusted to other alternative pre-configured performance values can be determined in the same manner as above.

[0117] Taking IOPS as an example, the following formulas (1) and (3) can be used to calculate the actual usage cost of the cloud disk within the historical time period, and the following formulas (2), (4), (5) and (6) can be used to calculate the adjusted usage cost of the cloud disk within the historical time period:

[0118] E0 = e + E′0 (1)

[0119] E i = e + E′ i , i ∈ [1, 10] (2)

[0120] Where,

[0121] E′0 = x * p * T + a * bur (3)

[0122] E′ i = (x + n i ) * p * T + b i * bur (4)

[0123] Where,

[0124]

[0125] b i = ∑ 1<j<m (h j - n i * t * ratio j ) (6)

[0126] Where, E0 is the usage cost of the cloud disk within the historical week; E i is the adjusted usage cost of the cloud disk within the historical week when the pre-configured IOPS value is adjusted to the i-th alternative pre-configured IOPS value. e is the basic IOPS cost, and the basic IOPS cost remains unchanged before and after the adjustment. Since only E0 and E iThe size relationship. Therefore, to reduce the computational complexity, only the above formulas (3) to (6) need to be calculated, and the size relationship between E′0 and E′ i is also the size relationship between E0 and E i .

[0127] x is the additional IOPS value currently configured for the cloud disk, p is the unit price of the additional IOPS, T is the duration of the past week, a is the burst I / O volume (i.e., the number of burst read / write operations) of the cloud disk within the past week (i.e., the historical time period); bur is the unit price of burst IOPS (i.e., the unit price of burst performance); IOPS max is the peak IOPS actually used by the cloud disk within the past week (i.e., the performance peak); base is the basic IOPS value of the cloud disk; IOPS max -base - x is the difference between the peak IOPS and the preconfigured performance value of the current configuration of the cloud disk; is the above - preset spacing; n i is the difference between the i - th alternative preconfigured IOPS value (i.e., the alternative preconfigured performance value) and the preconfigured IOPS value (i.e., the preconfigured performance value) of the current configuration of the cloud disk; b i is the adjusted burst I / O volume (adjusted number of burst read / write operations) of the cloud disk within the past week when the preconfigured IOPS value is adjusted to the i - th alternative preconfigured IOPS value; m is the total number of hours included in the past week (i.e., the total number of multiple time intervals); h j is the burst I / O volume of the cloud disk at the j - th hour; ratio j is the ratio of the burst duration of the cloud disk at the j - th hour; t is the duration of one hour; n i *t*ratio j can be understood as the burst I / O reduction amount (i.e., the burst reduction amount) of the cloud disk at the j - th hour when the preconfigured IOPS value is adjusted to the i - th alternative preconfigured IOPS value; h j -n i *t*ratio j can be understood as the adjusted burst I / O volume of the cloud disk at the j - th hour when the preconfigured IOPS value is adjusted to the i - th alternative preconfigured IOPS value.

[0128] It should be added that in the above example, the difference between the peak IOPS and the preconfigured performance value of the current configuration of the cloud disk is divided into ten equal parts to obtain the preset spacing.

[0129] Among the above 1024, when the smallest adjusted usage cost is less than the actual usage cost of the cloud disk within the historical time period, the alternative preconfigured performance value corresponding to the smallest adjusted usage cost is determined as the target preconfigured performance value.

[0130] Optionally, the above method may further include:

[0131] 104. When the minimum adjusted usage cost is greater than or equal to the actual usage cost of the cloud disk during the historical time period, no recommendation information regarding cost optimization is sent to the user.

[0132] That is to say, when cost optimization is not achieved, there is no need to send optimization suggestions to the user.

[0133] In practical applications, there may be three situations:

[0134] The first situation is that the preconfigured performance value currently configured for the cloud disk is less than the performance peak value;

[0135] The second situation is that the preconfigured performance value currently configured for the cloud disk is equal to the performance peak value;

[0136] The third situation is that the preconfigured performance value currently configured for the cloud disk is greater than the performance peak value.

[0137] If it is the first situation, then the step of "determining multiple alternative preconfigured performance values between the preconfigured performance value currently configured for the cloud disk and the performance peak value" in step 1022 above can be executed. That is to say, if it is the first situation, then steps 1022-1024 above are executed.

[0138] If it is the second situation, then no steps are executed.

[0139] If it is the third situation, then the performance peak value is determined as the target preconfigured performance value that meets the preset cost optimization condition. That is to say, the preconfigured performance value of the cloud disk is reduced to the performance peak value.

[0140] Next, the information recommendation method provided in the embodiments of the present application will be introduced in conjunction with Figure 3 The system architecture involved in the information recommendation method includes: a task scheduling platform 31, a cloud disk management and control service 32, a cloud disk meta-database 33, a cloud disk hourly data statistics service 34, a cloud disk second-level data statistics service 35, a centralized service 36, and a cloud disk management and control service message module 321.

[0141] Among them, the cloud disk management and control service message module 321 can be a functional module in the cloud disk management and control service 32.

[0142] As

[0143] shown, the information recommendation method includes the following steps: Figure 3

[0144] 1. Trigger cost optimization offline analysis at a fixed time every week.

[0145] ​Exemplarily, the task scheduling platform 31 may send a cost optimization analysis instruction to the cloud disk management service 32 at 2:00 am every Sunday.

[0146] 2. Pull cloud disk metadata.

[0147] The cloud disk metadata may include: the cloud disk name, the currently preconfigured performance value of the cloud disk, and the burst performance activation status.

[0148] The cloud disk management service 32 pulls the cloud disk metadata from the cloud disk metadata database 33.

[0149] 3. Pull cloud disk metering data.

[0150] The cloud disk management service 32 pulls the cloud disk metering data from the cloud disk hourly data statistics service 34. The cloud disk metering data (i.e., the historical usage data of the cloud disk) may include: the number of burst read / write operations per hour of the cloud disk within the historical week, that is, the burst I / O volume. That is to say, the number of burst read / write operations per hour of the cloud disk within the historical week is pre-statistically calculated by the cloud disk hourly data statistics service 34. When performing the cost optimization offline analysis, it can be directly obtained, which can shorten the time occupied by cost optimization.

[0151] 4. Pull the weekly performance peak of the cloud disk.

[0152] The cloud disk management service 32 pulls the weekly performance peak of the cloud disk from the cloud disk second-level data statistics service 35. For example: the IOPS peak within the historical week.

[0153] 5. Calculate the recommended configuration and generate an optimization event.

[0154] The process of calculating the recommended configuration, that is, the process of finding the target preconfigured performance value that meets the preset cost optimization conditions, can refer to the corresponding content in the above embodiments for specific implementation methods.

[0155] 6. Store the cost optimization event in the database.

[0156] The cloud disk management service 32 stores the optimization event (i.e., the recommended information regarding cost optimization) in the centralized service 36.

[0157] 7. Trigger the sending of the optimization event regularly every week.

[0158] The task scheduling platform may send a notification instruction to the cloud disk management service 32 at 8:00 am every Monday.

[0159] 8. Notify the user on a weekly basis.

[0160] The cloud disk management service 32 may trigger the cloud disk management service message module 321 to send the optimization event stored in the centralized service 36 to the corresponding user.

[0161] Figure 4 The flowchart of the data processing method provided by the embodiment of the present application is shown. The execution subject of this method can be a server. Among them, the server can be a common server, a cloud server or a virtual server, etc., and the embodiments of the present application do not make specific limitations on this.

[0162] 401. Obtain the historical usage data of the cloud disk.

[0163] The cloud disk is configured with pre-configured performance and burst performance; the pre-configured performance is charged according to the pre-configured performance value and the charging duration; the burst performance is charged according to the burst read / write times of the cloud disk.

[0164] 402. According to the historical usage data, predict the target pre-configured performance value that meets the preset cost optimization condition.

[0165] For the specific implementation manners of the above steps 401 and 402, reference can be made to the corresponding content in the above embodiments, which will not be elaborated here.

[0166] After obtaining the target pre-configured performance value in the embodiment of the present application, relevant cost optimization recommendation information can be sent to the user according to the target pre-configured performance value, or the pre-configured performance value of the cloud disk can be automatically changed according to the target pre-configured performance value. It should be noted that automatically changing the pre-configured performance value of the cloud disk according to the target pre-configured performance value is executed when the user has previously granted the cloud provider the permission to automatically optimize the pre-configured performance value.

[0167] In the technical solution provided by the embodiment of the present application, the historical usage data of the cloud disk is obtained; according to the historical usage data of the cloud disk, a reasonable pre-configured performance value in the future time period can be predicted more accurately. In this way, by configuring the pre-configured performance of the cloud disk according to the recommended pre-configured performance value, the cost of the user using the cloud disk can be optimized.

[0168] It should be noted here that: for the content not elaborated in each step of the method provided by the embodiment of the present application, reference can be made to the corresponding content in the above embodiments, which will not be elaborated here. In addition, in the method provided by the embodiment of the present application, in addition to the above steps, other parts or all of the steps in the above embodiments may also be included. For specific reference, see the corresponding content in the above embodiments, which will not be elaborated here.

[0169] Figure 5 The structural diagram of the electronic device provided by an embodiment of the present application is shown. As Figure 5As shown, the electronic device includes a memory 1101 and a processor 1102. The memory 1101 can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device. The memory 1101 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Electrically Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), magnetic memory, flash memory, magnetic disks, or optical disks.

[0170] The memory 1101 is used to store programs;

[0171] The processor 1102, coupled to the memory 1101, is configured to execute the programs stored in the memory 1101 to implement the methods provided in the above method embodiments.

[0172] Further, as Figure 5 shown, the electronic device further includes: a communication component 1103, a display 1104, a power supply component 1105, an audio component 1106, and other components. Figure 5 Only some components are schematically shown herein, and it does not mean that the electronic device only includes Figure 5 the components shown.

[0173] Correspondingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the steps or functions of the methods provided in the above method embodiments.

[0174] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative efforts.

[0175] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM (Read Only Memory), RAM (Random Access Memory), magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. An information recommendation method, characterized in that, Including: Obtain the historical usage data of the cloud disk; the cloud disk is configured with pre-configured read / write performance and burst read / write performance; the pre-configured read / write performance is charged according to the pre-configured performance value and the billing duration; the burst read / write performance is charged according to the burst read / write times of the cloud disk; the burst read / write times refer to the read / write times involved in the part where the actually used performance value exceeds the pre-configured performance value. Predict the target pre-configured performance value that meets the preset cost optimization condition according to the historical usage data. Send recommendation information about cost optimization to the user according to the target pre-configured performance value.

2. The method according to claim 1, wherein Predict the target pre-configured performance value that meets the preset cost optimization condition according to the historical usage data, including: Determine the peak performance actually used by the cloud disk during the historical time period according to the historical usage data. When the currently configured pre-configured performance value of the cloud disk is less than the peak performance, determine multiple alternative pre-configured performance values between the currently configured pre-configured performance value of the cloud disk and the peak performance. For each alternative pre-configured performance value, determine the adjusted usage cost of the cloud disk during the historical time period when the pre-configured performance value is adjusted to this alternative pre-configured performance value according to the historical usage data. When the minimum adjusted usage cost is less than the actual usage cost of the cloud disk during the historical time period, determine the alternative pre-configured performance value corresponding to the minimum adjusted usage cost as the target pre-configured performance value.

3. The method according to claim 2, wherein Determine multiple alternative pre-configured performance values between the currently configured pre-configured performance value of the cloud disk and the peak performance, including: Select multiple alternative pre-configured performance values in sequence at a preset interval between the currently configured pre-configured performance value of the cloud disk and the peak performance. The preset interval is determined according to the difference between the peak performance and the currently configured pre-configured performance value of the cloud disk.

4. The method according to claim 2 or 3, characterized in that The multiple alternative pre-configured performance values include the first alternative pre-configured performance value. Determine the adjusted usage cost of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value according to the historical usage data, including: Determine the adjusted pre-configured read / write performance cost of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value according to the first alternative pre-configured performance value and the duration of the historical time period. Determine the adjusted burst read / write times of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value according to the historical usage data. Determine the adjusted burst read / write performance cost of the cloud disk during the historical time period according to the adjusted burst read / write times. Determine the adjusted usage cost of the cloud disk during the historical time period when the pre-configured performance value is adjusted to the first alternative pre-configured performance value according to the adjusted pre-configured read / write performance cost and the adjusted burst read / write performance cost.

5. The method according to claim 4, wherein Determining the adjusted burst read / write times of the cloud disk during the historical time period when adjusting the preconfigured performance value to the first alternative preconfigured performance value according to the historical usage data includes: Determining, according to the historical usage data, the actual burst read / write times and the proportion of the actual burst duration in each time interval among multiple time intervals; the multiple time intervals are obtained by dividing the historical time period; Estimating the burst reduction amount of the cloud disk in each time interval when adjusting the preconfigured performance value to the first alternative preconfigured performance value according to the difference between the currently configured preconfigured performance value of the cloud disk and the first alternative preconfigured performance value, the duration of each time interval, and the proportion of the burst duration of the cloud disk in each time interval; Determining the adjusted burst read / write times of the cloud disk during the historical time period when adjusting the preconfigured performance value to the first alternative preconfigured performance value according to the actual burst read / write times and the burst reduction amount of the cloud disk in each time interval among multiple time intervals.

6. The method according to claim 2 or 3, characterized in that, It further includes: When the minimum adjusted usage cost is greater than or equal to the actual usage cost of the cloud disk during the historical time period, no recommendation information regarding cost optimization is sent to the user.

7. The method according to claim 2 or 3, characterized in that, Predicting a target preconfigured performance value that meets the preset cost optimization conditions according to the historical usage data further includes: If the currently configured preconfigured performance value of the cloud disk is greater than the performance peak value, determining the performance peak value as the target preconfigured performance value that meets the preset cost optimization conditions.

8. The method according to claim 2 or 3, characterized in that, The preconfigured read / write performance includes: preconfigured IOPS performance; the burst read / write performance includes: burst IOPS performance.

9. A data processing method, characterized in that It includes: Obtaining the historical usage data of the cloud disk; the cloud disk is configured with preconfigured read / write performance and burst read / write performance; the preconfigured read / write performance is billed according to the preconfigured performance value and the billing duration; the burst read / write performance is billed according to the burst read / write times of the cloud disk; the burst read / write times refer to the read / write times involved in the part where the actually used performance value exceeds the preconfigured performance value; Predicting a target preconfigured performance value that meets the preset cost optimization conditions according to the historical usage data.

10. The method according to claim 9, wherein Predicting a target preconfigured performance value that meets the preset cost optimization conditions according to the historical usage data includes: Determining the performance peak value actually used by the cloud disk during the historical time period according to the historical usage data; When the currently configured preconfigured performance value of the cloud disk is less than the performance peak value, determining multiple alternative preconfigured performance values between the currently configured preconfigured performance value of the cloud disk and the performance peak value; For each alternative preconfigured performance value, determining the adjusted usage cost of the cloud disk during the historical time period when adjusting the preconfigured performance value to this alternative preconfigured performance value according to the historical usage data; When the minimum adjusted usage cost is less than the actual usage cost of the cloud disk during the historical time period, determining the alternative preconfigured performance value corresponding to the minimum adjusted usage cost as the target preconfigured performance value.

11. An electronic device, characterized in that, It includes: A memory and a processor, wherein, The memory is used for storing a program; The processor is coupled to the memory and is used for executing the program stored in the memory so as to implement the method according to any one of claims 1 to 10.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a computer, it can implement the method according to any one of claims 1 to 10.

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