Computer system, system configuration candidate output method, and system configuration candidate output program

The system addresses the challenge of selecting cloud system configurations by evaluating and ranking options based on performance and cost, enabling efficient cloud service migration.

JP7826163B2Active Publication Date: 2026-03-09HITACHI VANTARA LTD
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Patent Information

Application Number
JP2022154162
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Filing Date
2022-09-27
Publication Date
2026-03-09
Estimated Expiration
2042-09-27

AI Technical Summary

Technical Problem

Existing technologies fail to determine the appropriate system configuration for cloud services, considering performance, availability, and costs, requiring expert judgment and lacking automated selection methods.

Method used

A computer system and method that utilizes a processor and storage device to evaluate system configurations based on configuration requirements, narrowing down options and ranking them based on evaluation values, assisting in the selection of an optimal cloud system configuration.

Benefits of technology

Enables the automated selection of an appropriate cloud system configuration considering performance, availability, and costs, facilitating efficient migration to cloud services.

✦ Generated by Eureka AI based on patent content.

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Patent Text Reader

Abstract

To support appropriate selection of a cloud system configuration.SOLUTION: A computer system comprises a processor 111, a storage device 112, and an input-output device 141. The storage device 112 stores at least configuration condition information 132 indicative of an evaluation value about a system configuration configurable on a cloud. The input-output device 141 accepts a configuration request indicative of conditions for a system configuration configured on the cloud. The processor 111 calculates an evaluation value corresponding to the configuration request, compares the evaluation value corresponding to the configuration request with the evaluation value of the configuration condition information, and determines a system configuration candidate to be proposed on the basis of the comparison results. The input-output device 141 outputs the proposed system configuration candidate.SELECTED DRAWING: Figure 1
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Description

[Technical Field]

[0001] The present invention relates to a computer system, a system configuration candidate output method, and a system configuration candidate output program. [Background technology]

[0002] Traditionally, application systems were operated by purchasing dedicated servers, storage, networks, and other equipment, known as on-premise. However, in recent years, cloud-based systems have emerged that make it possible to use IT resources such as servers, storage, and networks on demand, making it possible to procure IT resources quickly and flexibly. As a result, there has been an increase in cases where application systems are being migrated from traditional on-premise environments to the cloud.

[0003] Once you have decided on the devices you want to use, such as servers and storage, and the cloud services, you need to estimate performance, availability, and other factors in accordance with your business requirements. One technique for making such estimates is described in Japanese Patent Application Laid-Open No. 2021-064078 (Patent Document 1). This publication states, "An apparatus creates an expanded configuration plan for a storage system that includes multiple nodes. The apparatus includes a processor and a storage device that stores programs executed by the processor. The processor obtains information on the performance requirements of each host that accesses the storage system, obtains information on the performance of each of multiple existing nodes in the storage system, and determines the number and performance of one or more additional nodes, as well as the connection topology between the host and the storage system, so as to satisfy the performance requirements of each host. The number and performance of the one or more additional nodes, as well as the connection topology, are included in the expanded configuration plan." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-064078 Summary of the Invention [Problem to be solved by the invention]

[0005] By using Patent Document 1, it is possible to estimate the configuration of equipment that meets the requirements. A similar method can also be used to estimate the specific functions of a specific cloud service. However, with conventional technology, it is not possible to determine in advance the system configuration, i.e., which functions from the many cloud services to combine, while taking into account requirements such as performance and availability, as well as costs. Furthermore, even if the industry type and scale are already determined, the prior determination requires the judgment of an expert to quantify the necessary requirements.

[0006] Therefore, an object of the present invention is to support the appropriate selection of the configuration of a cloud system. [Means for solving the problem]

[0007] In order to solve the above problem, one representative computer system of the present invention comprises a processor, a storage device, and an input / output device, wherein the storage device stores at least configuration condition information indicating an evaluation value for a system configuration that can be constructed on a cloud, the input / output device receives a configuration request indicating conditions for the system configuration to be constructed on the cloud, and the processor: determining evaluation values ​​for a plurality of items from the configuration requirements, narrowing down the possible system configurations to candidate system configurations using some of the evaluation values ​​for the plurality of items, and ranking the narrowed-down system configurations based on the evaluation values ​​for the plurality of items; A candidate system configuration to be proposed is determined, and the input / output device outputs the candidate system configuration to be proposed. In order to solve the above problem, one representative system configuration candidate output method of the present invention includes the steps of: a computer system that stores at least configuration condition information indicating evaluation values ​​for system configurations that can be constructed on a cloud receiving a configuration request indicating conditions for the system configuration to be constructed on the cloud; a step of obtaining evaluation values ​​for a plurality of items from the configuration requirements; a step of narrowing down the possible system configurations to candidate system configurations using some of the evaluation values ​​for the plurality of items; and a step of ranking the narrowed down system configurations based on the evaluation values ​​for the plurality of items to determine candidate system configurations. The present invention is characterized by comprising: In order to solve the above problem, one representative system configuration candidate output program of the present invention includes the steps of receiving a configuration request indicating conditions for a system configuration to be constructed on a cloud from a computer system that stores at least configuration condition information indicating evaluation values ​​for system configurations that can be constructed on the cloud; A step of obtaining evaluation values ​​for a plurality of items from the configuration requirements; a step of narrowing down the possible system configurations to candidate system configurations using some of the evaluation values ​​for the plurality of items; and a step of ranking the narrowed down system configurations based on the evaluation values ​​for the plurality of items to determine candidate system configurations. The present invention is characterized in that the above is executed. [Effects of the Invention]

[0008] According to the present invention, it is possible to assist in the selection of an appropriate configuration for a cloud system. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a computer system according to a first embodiment of the present invention. [Figure 2] Example of policy input screen [Figure 3] Example of a configuration proposal screen [Figure 4] 10 is a flowchart showing an example of a procedure for calculating a configuration plan for a management computer. [Figure 5] An example of information corresponding to the proposal priority policy [Figure 6] Examples of information corresponding to industry policies [Figure 7] An example of information corresponding to the scale policy [Figure 8] An example of information corresponding to the recovery policy when a cloud failure occurs [Figure 9] An example of information corresponding to data recovery policy in the event of an AP malfunction or operational error [Figure 10] FIG. 10 is an explanatory diagram illustrating an example of configuration condition information. [Figure 11] Flowchart showing system load calculation processing [Figure 12] An example of an instance sizing table DETAILED DESCRIPTION OF THE INVENTION

[0010] In the following description, "memory" refers to one or more memory devices, typically a primary storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.

[0011] In the following description, a "persistent storage device" refers to one or more persistent storage devices. A persistent storage device is typically a non-volatile storage device (e.g., an auxiliary storage device), specifically, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive).

[0012] In the following description, the term "storage device" may refer to either the above-mentioned "memory" or the above-mentioned "persistent storage device." In the following description, a "processor" refers to one or more processor devices. The at least one processor device is typically a microprocessor device such as a CPU (Central Processing Unit), but may also be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a hardware circuit (e.g., an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit)) that performs part or all of the processing.

[0013] In the following description, information that provides an output in response to an input may be described using expressions such as "xxx table," but this information may be data of any structure, or may be a learning model such as a neural network that generates an output in response to an input. Therefore, "xxx table" can be rephrased as "xxx information." In the following description, the configuration of each table is an example, and a table may be divided into two or more tables, or all or part of two or more tables may be a single table, or may include several data fields not shown.

[0014] In the following description, processing may be described using a "program" as the subject. However, since a program is executed by a processor to perform a predetermined process using a storage device and / or an interface device, etc., as appropriate, the subject of the process may also be the processor (or a device such as a controller having the processor). A program may be installed in a device such as a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable (e.g., non-transitory) recording medium. In the following description, two or more programs may be realized as one program, and one program may be realized as two or more programs.

[0015] In the following description, functions may be described using expressions such as "xxx unit," but the function may be realized by one or more computer programs executed by a processor, or by one or more hardware circuits (e.g., FPGA or ASIC). When a function is realized by a program executed by a processor, the specified processing is performed using a storage device and / or an interface device, etc., as appropriate, and therefore the function may be considered to be at least a part of the processor. Furthermore, processing described using a function as the subject may be processing performed by a processor or a device having the processor. Furthermore, a program may be installed from a program source. The program source may be, for example, a computer that distributes the program or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions. In the following description, a "computer system" is a system including one or more physical computers. The physical computers may be general-purpose computers or special-purpose computers.

[0016] In addition, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily represent all the control lines and information lines that are necessary for implementation. In reality, it can be assumed that almost all components are interconnected.

[0017] Hereinafter, a collection of one or more computers that manage an information processing system and display the display information of this embodiment may be referred to as a management system. When a management computer (hereinafter referred to as a management computer) displays the display information, the management computer is the management system. Furthermore, the combination of a management computer and a display computer is also a management system. Furthermore, in order to increase the speed and reliability of management processing, multiple computers may be used to achieve processing equivalent to that of a management computer, in which case the multiple computers (including the display computer if the display is performed by the display computer) are the management system.

[0018] The present invention is not limited to the above-described embodiments, but includes various modifications and equivalent configurations within the spirit and scope of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to configurations including all of the described configurations. Furthermore, part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Furthermore, the configuration of another embodiment may be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment may be added, deleted, or replaced with other configurations. Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. [Example]

[0019] <Example of problem-solving process> 1 is a block diagram showing an example of the configuration of a computer system according to a first embodiment of the present invention. The computer system is a system in which a management computer 101, an operation terminal 102, a cloud service 104 that is the object of management of the management computer, and a repository server 105 that holds program data used when constructing a target system can be interconnected via a network 103.

[0020] If the target system is not actually constructed on the cloud service in accordance with the configuration plan calculated by the management computer, the cloud service 104 and the repository server 105 do not need to be connected via the network 103. Furthermore, if the management computer 101 is equipped with an input / output device (not shown), the processing described below may be executed using the input / output device held by the management computer 101 without using the operation terminal 102.

[0021] The management computer 101 includes a processor 111 and a storage device 112. The management computer 101 may also include an input / output device (not shown). Here, the input / output device refers to, for example, a touch panel, a display, a keyboard, or a mouse. The processor 111 implements a configuration plan calculation process 121 and a construction execution process 122 by loading and executing a program in the storage device 112. The storage device 112 also stores policy conversion information 131, configuration condition information 132, calculation information 133, and fee information 134 in addition to data corresponding to the configuration plan calculation process 121 and the construction execution process 122. The processes and information stored in the storage device 112 may be stored in different storage devices, or may be stored in a storage device (not shown) connected via the network 103.

[0022] The configuration plan calculation process 121 is a process for calculating a system configuration plan in accordance with a policy selected via the input / output device 141 and displaying the calculation results via the input / output device 141 . The construction execution process 122 is a process for constructing a target system on the cloud service 104 in accordance with the configuration plan output by the configuration plan calculation process 121. At this time, a process for copying program data held by the repository server 105 to the cloud service 104 may be executed.

[0023] The policy conversion information 131 is information that associates the policy displayed on the input / output device 141 with the value used in the configuration plan calculation process 121 . The configuration condition information 132 is information that holds information on the approximate performance and availability that can be realized by combining the many functions provided by the cloud service 104, as well as the approximate cost. The calculation information 133 is information that holds rules for sizing calculation of functions used in the configuration indicated by the configuration condition information 132 . The fee information 134 is basic information for calculating the fee to be charged when the configuration indicated by the configuration condition information 132 is used with the sizing calculated by the calculation information 133 .

[0024] The operation terminal 102 is, for example, a laptop computer or a tablet terminal, and has an input / output device 141. The input / output device 141 is, for example, a touch panel, a display, a keyboard, a mouse, or the like.

[0025] The network 103 is a communication path connected by wire or wirelessly, such as a wired LAN cable or a wireless WiFi, but is not limited to these. The cloud service 104 includes network devices, servers, storage, etc., and provides a wide variety of IT services that meet specified requirements, such as virtual servers and database services, in response to a request from the construction execution process 122. For example, the cloud service 104 may be provided by a company that provides cloud services as a business, or it may be a computer system independently maintained by an individual or company.

[0026] The repository server 105 is a server that has program information to be stored on the cloud service 104 in response to a request from the construction execution process 122. For example, it is Github.

[0027] FIG. 2 shows an example of a policy input screen for setting a policy to be input to the configuration proposal calculation process 121 in the first embodiment of the present invention. The policy input screen 200 includes a policy, a detailed settings button 211 that calls a detailed settings screen (not shown), and an estimate execution button 212 that instructs the start of calculation of a configuration proposal. Here, the detailed settings screen (not shown) is an input screen for setting arbitrary values ​​without using information from the policy conversion information 131 held by the management computer 101. If a detailed settings screen (not shown) is displayed in advance within the policy input screen 200, or if arbitrary setting values ​​are not used, the policy input screen 200 does not need to have the detailed settings button 211. The policies set on the policy input screen 200 include a proposal priority policy 201, an industry policy 202, a scale policy 203, a recovery policy 204 for when a cloud failure occurs, and a data recovery policy 205 for when an AP malfunction or operation error occurs, and may further include several policies (not shown). Furthermore, if some of these policies are not to be set arbitrarily, the policies may not be displayed on the screen.

[0028] The policies to be selected on the policy input screen 200 are selectable using, for example, a pull-down menu. The policies selectable on the policy input screen 200 may be displayed according to the values ​​defined in the policy conversion information 131 held by the management computer 101. All or some of the policies selectable on the policy input screen 200 may be selected in advance by the management computer 101 at random or with fixed values.

[0029] 3 is an example of a configuration proposal presentation screen that displays configuration proposals output by the configuration proposal calculation process 121 in the first embodiment of the present invention. The configuration proposal presentation screen 300 has a plurality of configuration proposals 301. Although the configuration proposal presentation screen 300 illustrated in FIG. 3 displays only two configuration proposals, it is sufficient that the configuration proposal presentation screen 300 allows for comparison of a plurality of configuration proposals, and it may display only one arbitrarily selected configuration proposal, or it may display three or more configuration proposals.

[0030] The configuration plan 301 has a configuration overview diagram 311, a configuration evaluation 312, a details confirmation button 313, and a construction execution button 314. The details confirmation button 313 is a button for calling a details confirmation screen (not shown) on which the details of the advantages and disadvantages of the configuration calculated in the configuration plan calculation process 121 can be confirmed. If detailed information (not shown) is displayed in advance in the configuration plan 301, the details confirmation button 313 may not be present. The construction execution button 314 is a button for calling the construction execution process 122 and constructing a target system in accordance with the corresponding configuration plan 301. If it is sufficient for the management computer 101 to execute only the configuration plan calculation process 121 and there is no intention to execute the construction execution process 122, the construction execution button 314 may not be present.

[0031] The configuration overview diagram 311 is a screen area that displays a diagram showing an overview of the system configuration of the target system indicated by the configuration plan 301. For example, the image of the configuration diagram corresponding to the combination of cloud service functions held in the configuration condition information 132 held by the management computer 101 may be stored in advance, and the image corresponding to the combination of cloud service functions corresponding to the configuration plan may be displayed.

[0032] The configuration evaluation 312 is a screen area that displays an overview of the advantages and disadvantages of the configuration calculated in the configuration proposal calculation process 121. The information displayed in the configuration evaluation 312 may be all or some of the values ​​calculated in the configuration proposal calculation process flow 400, or may be displayed in an abstracted form as shown in Fig. 3. When the values ​​are displayed in an abstracted form as shown in Fig. 3, for example, the values ​​may be calculated by a process in which the management computer 101 stores and displays a display language correspondence table corresponding to the values ​​of the logical fault tolerance field 1002, AZ fault tolerance 1003, and Region fault tolerance field 1004 held in the configuration condition information 1000.

[0033] 4 is a flowchart showing an example of the procedure of the configuration plan calculation process 121 of the management computer 101. The configuration plan calculation process 121 shown in this flowchart is executed in response to an instruction from the execute estimate button 212 on the policy input screen 200 displayed on the input / output device 141. Alternatively, it may be executed in response to an instruction from some kind of program.

[0034] 4, the management computer 101 executes a policy acquisition process (S401), a configuration pruning process (S402), a sizing process (S403), a fee calculation process (S404), and a configuration proposal sorting process (S405). The configuration proposal calculation process flow 400 may include other processing steps not shown, and the execution order of some processes may be changed or they may be executed in parallel as long as no discrepancies occur in input / output.

[0035] In the policy acquisition process (S401) of the configuration plan calculation process flow 400, the management computer 101 acquires information corresponding to the policy selected on the policy input screen 200 from the policy conversion information 131. Details of the information held by the policy conversion information 131 are illustrated in Figs. 5, 6, 7, 8, and 9.

[0036] FIG. 5 is an explanatory diagram showing an example of information corresponding to the proposed priority policy 201 input on the policy input screen 200, among the policy conversion information 131. The proposed priority table 500 has a proposed priority field 501, a sort key field 502, and an order field 503. Information corresponding to the proposed priority field 501 is displayed as an option for the proposed priority policy 201 on the policy input screen 200. In the policy acquisition process (S401), the values ​​of the sort key field (502) and the order field (503) of the row corresponding to the option selected in the proposed priority policy 201 are acquired. The acquired values ​​are used in the configuration proposal sort process (S405). The information in the proposed priority table 500 is information that is prepared in advance either manually or by some application program.

[0037] FIG. 6 is an explanatory diagram showing an example of information corresponding to the industry policy 202 input on the policy input screen 200, among the policy conversion information 131. The industry table 600 has an industry field 601, an IO coefficient field 602, a data volume coefficient 603, an RTO coefficient 604, and an RPO coefficient 605. Information corresponding to the industry field 601 is displayed as an option for the industry policy 202 on the policy input screen 200. In the policy acquisition process (S401), values ​​of the IO coefficient field 602, the data volume coefficient field 603, the RTO coefficient field 604, and the RPO coefficient field 605 of a row corresponding to an option selected in the industry policy 202 are acquired. The acquired values ​​are used in the sizing process (S403). The information in the industry table 600 is information that is prepared in advance either manually or by some application program.

[0038] FIG. 7 is an explanatory diagram showing an example of information corresponding to the scale policy 203 input on the policy input screen 200, among the policy conversion information 131. The scale table 700 has an industry field 601, an IO coefficient field 602, a data volume coefficient 703, an RTO coefficient 704, and an RPO coefficient 705. Information corresponding to the scale field 701 is displayed as an option for the scale policy 203 on the policy input screen 200. In the policy acquisition process (S401), the values ​​of the IO coefficient field 702, the data volume coefficient 703, the RTO coefficient 704, and the RPO coefficient 705 of the row corresponding to the option selected in the scale policy 203 are acquired. The acquired values ​​are used in the sizing process (S403). The information in the scale table 700 is information that is prepared in advance either manually or by some application program.

[0039] FIG. 8 is an explanatory diagram showing an example of information corresponding to the recovery policy 204 for when a cloud failure occurs, which is input on the policy input screen 200, among the policy conversion information 131. The recovery policy table 800 for when a cloud failure occurs has a recovery policy field 801 and a judgment value field 802. Information corresponding to the recovery policy field 801 is displayed as an option for the recovery policy 204 for when a failure occurs on the policy input screen 200. In the policy acquisition process (S401), the value of the judgment value field 802 of the row corresponding to the option selected in the recovery policy for when a failure occurs 204 is acquired. The value acquired here is used in the configuration pruning process (S402). The information in the recovery policy table 800 for when a cloud failure occurs is information that is prepared in advance either manually or by some application program.

[0040] 9 is an explanatory diagram showing an example of information from the policy conversion information 131 that corresponds to the data recovery policy 205 for AP malfunctions or operation errors that is input on the policy input screen 200. The data recovery policy table 900 for AP malfunctions or operation errors has a recovery policy field 901 and a judgment value field 902. Information corresponding to the recovery policy field 901 is displayed as an option for the data recovery policy 205 for AP malfunctions or operation errors on the policy input screen 200. In the policy acquisition process (S401), the value of the judgment value field 902 of the row corresponding to the option selected in the data recovery policy 205 for AP malfunctions or operation errors is acquired. The value acquired here is used in the configuration pruning process (S402). The information in the data recovery policy table 900 for AP malfunctions or operation errors is information that is prepared in advance either manually or by some application program.

[0041] In the configuration pruning process (S402) of the configuration plan calculation process flow 400, the management computer 101 prunes the configuration plan of the target system using the values ​​acquired in the policy acquisition process (S401) and the configuration condition information 132. An example of information held by the configuration condition information 132 is shown in Fig. 10.

[0042] FIG. 10 is an explanatory diagram showing an example of configuration condition information 132. The configuration condition information table 1000 has a configuration field 1001, a logical fault tolerance field 1002, an AZ fault tolerance field 1003, a region fault tolerance field 1004, a cost increase data field 1005, and a cost increase server field 1006. The configuration field 1001 is information indicating a combination of cloud service functions. The logical fault tolerance field 1002 describes an evaluation value of recovery performance when a logical fault occurs in a given configuration. The AZ fault tolerance field 1003 describes an evaluation value of recovery performance when an AZ fault occurs in the given configuration. The region fault tolerance field 1004 describes an evaluation value of recovery performance when a region fault occurs in the given configuration. The cost increase data field 1005 describes an evaluation value of the impact of the doubling rate of cost due to data increase when the given configuration is adopted. The cost increase server field 1006 describes an evaluation value of the impact of the doubling rate of cost due to server increase when the given configuration is adopted.

[0043] For example, the configuration in the first row of Figure 10 shows a configuration in which a certain system is run on Company A's service, with one backup server in the same availability zone in the same region. A region is a location where physical machines such as servers that provide cloud services are run, such as a data center. It is written as R or Region in the diagram and may also be written as R or Region in the specification. An availability zone is an independent group of resources within a region, such as a range of resources separated by a room or rack. It is written as AZ in the diagram and may also be written as AZ in the specification.

[0044] As shown in the first row of Figure 10, if a backup system is located in the same AZ in the same Region, data can be quickly restored using the backup data if it is lost due to an accident, such as when an application user accidentally deletes the data. For this reason, the evaluation value of the logical fault tolerance field 1002 is set to a high value of 3.

[0045] In the configuration shown in the first row of Figure 10, for example, if a failure occurs in the region where the target system is running, which is called a region failure, and which makes it impossible to access the cloud service on a region-by-region basis or causes a malfunction, or if a failure occurs in the AZ where the target system is running, which is called an AZ failure, and which makes it impossible to access the cloud service on an AZ-by-AZ basis or causes a malfunction, it is difficult to recover from the inaccessibility or malfunction that occurs in the target system, so the evaluation values ​​of the AZ failure tolerance field 1003 and the Region failure tolerance field 1004 are stored with a low evaluation value of 0.

[0046] In the configuration shown in the first row of Figure 10, a backup system is configured separately from the target system, so virtual machines for executing backup and restore processes must be started and backup data must be stored separately from the target system. Therefore, when configuring this system, more cloud services are used than when the target system is operated alone. Since this configuration stores twice the amount of data, an evaluation value of 2 is stored in the Cost Increase Data field 1005. Since this configuration requires a virtual machine to execute backup and restore processes, an evaluation value of 1 is stored in the Cost Increase Server field 1006.

[0047] As shown in Figure 10, even for a single function, the evaluation value of recovery capability for logical failures, AZ failures, and region failures varies depending on the implementation method, and the combination of recovery capability evaluation value and cost varies when multiple functions are used in combination. Even for similar functions, the effectiveness and cost may differ depending on the cloud service provider. The configuration condition information table 1000 may be prepared manually in advance based on this knowledge, or it may contain information calculated by some application program.

[0048] The values ​​stored in the configuration field 1001 shown in Figure 10 are primarily examples of Company A's functions, but it is also possible to use the functions of another company's cloud service, or to use a unique service that utilizes IT resources owned by a company or individual.

[0049] In the configuration pruning process (S402), the management computer 101 compares the judgment value 902 in the data recovery policy table 900 for an AP malfunction or an operation error, acquired in the policy acquisition process (S401), with the value of the logical fault tolerance field 1002, and if the value of the logical fault tolerance field 1002 is smaller than the judgment value 902, the management computer 101 excludes the configuration from proposal targets. Furthermore, in the configuration pruning process (S402), the management computer 101 compares the judgment value 802 in the recovery policy table 800 for the occurrence of a cloud failure, acquired in the policy acquisition process (S401), with both the values ​​of the AZ fault tolerance field 1003 and the Region fault tolerance field 1004, and if both the values ​​of the AZ fault tolerance field 1003 and the Region fault tolerance field 1004 are smaller than the judgment value 802, the management computer 101 excludes the configuration from proposal targets.

[0050] In the configuration pruning process (S402), normally, if the value of either the AZ fault tolerance field 1003 or the Region fault tolerance field 1004 is equal to or greater than the value of the judgment value 802, the configuration is judged as a candidate for proposal and is not excluded from the candidate configurations for proposal. However, it is also possible to perform exceptional processing, such as making the judgment based solely on the value of the AZ fault tolerance field regardless of the value of the Region fault tolerance field when tolerance to AZ faults is required on a detailed setting screen not shown, or making the judgment based solely on the value of the Region fault tolerance field regardless of the value of the AZ fault tolerance field when a condition exists in the detailed setting screen not shown that tolerance to Region faults is required.

[0051] In the sizing process (S403) of the configuration proposal calculation process flow 400, the management computer 101 calculates the target system load to be constructed and the amount of data held by the system using the values ​​acquired in the policy acquisition process (S401), and performs sizing of the components in the proposed candidate configurations that were not excluded in the configuration pruning process (S402) based on the calculated values.

[0052] First, the system load calculation process will be described. 11 is a flowchart showing the system load calculation process executed by the management computer 101. The system load calculation process 1100 illustrated in this flowchart may be executed in response to an instruction from the sizing process step (S403) of the configuration plan calculation process flow 400.

[0053] 11, the management computer 101 executes a business IO volume estimation process (S1101), a DB transaction volume calculation process (S1102), and a storage IO volume calculation process (S1103). The system load calculation process flow 1100 may include other processing steps not shown.

[0054] Furthermore, when a business IO volume per day is input on a detailed setting screen (not shown) on the policy input screen 200, part of the business IO volume estimation process (S1101) may not be executed, and when both a business IO volume per day and a business IO density are specified, the business IO volume estimation process (S1101) may not be executed. Furthermore, when a value of DB transaction density is specified on a detailed setting screen (not shown) on the policy input screen 200, the DB transaction volume calculation process (S1102) may not be executed. Furthermore, when a storage IO density is specified on a detailed setting screen (not shown) on the policy input screen 200, the storage IO volume calculation process (S1103) may not be executed.

[0055] In the business IO volume estimation process (S1101), the management computer 101 calculates the business IO volume per day and the business IO density when a peak load is applied as requirements that the construction target system should fulfill. The business IO volume per day and the calculated business IO density are used in the sizing process (S403) for sizing the virtual server, storage, and network. First, the management computer 101 calculates the business IO volume per day to be processed by the target system by multiplying the value of the IO coefficient 602 in the industry table 600 acquired in the policy acquisition process (S401), the IO coefficient 702 in the scale table 700, and the business IO specific value. Expressed as a formula, it is as follows. Daily business IO volume = IO coefficient 602 x IO coefficient 702 x business IO characteristic value

[0056] Next, divide the business IO volume per day by the value of business hours per day x 60 x 60, and then multiply it by the peak load coefficient to calculate the peak business load per second as business IO density. Expressed as the formula below. Business IO density = business IO volume per day ÷ (business hours per day x 60 x 60) x peak load coefficient

[0057] The values ​​of the business IO specific value, the business hours of one day, and the load coefficient at peak times may be fixed values ​​held by the management computer 101, or may be values ​​inputted via a detailed setting screen (not shown) on the policy input screen 200.

[0058] In the DB transaction amount calculation process (S1102), the management computer 101 calculates the DB transaction density. The calculated DB coefficient transaction density value is used in the sizing process (S403) for sizing the DB service. In the DB transaction amount calculation process (S1102), the management computer 101 calculates the DB transaction density by multiplying the business IO density value calculated in the business IO amount estimation process (S1101) by the DB access coefficient per business IO. Expressed as a formula, it is as follows. DB transaction density = Business IO density x DB access coefficient per business IO

[0059] The value of the DB access coefficient per business IO may be a fixed value held by the management computer 101, or a value inputted on a detailed setting screen (not shown) of the policy input screen 200.

[0060] In the storage IO amount calculation process (S1103), the management computer 101 calculates the storage IO density. The calculated storage IO density value is used in the sizing process (S403) for sizing the storage service. In the storage IO amount calculation process (S1103), the management computer 101 calculates the storage IO density by multiplying the DB transaction density value calculated in the DB transaction amount calculation process (S1102) by the storage IO coefficient per DB access. Expressed as a formula, it is as follows: Storage IO density = DB transaction density x storage IO factor per DB access

[0061] The value of the storage IO coefficient per DB access may be a fixed value held by the management computer 101, or a value input on a detailed setting screen (not shown) of the policy input screen 200.

[0062] The calculation formulas given in the explanation of each processing step of the system load calculation process 1100 may be stored as the calculation information 133 of the management computer 101 .

[0063] The following describes the calculation process of the data capacity held by the target system executed by the management computer 101 in the sizing process (S403). In calculating the data capacity, the management computer 101 calculates the data capacity of the target system by multiplying the value of the data volume coefficient 603 in the industry table 600 acquired in the policy acquisition process (S401), the data volume coefficient 703 in the scale table 700, and the data volume characteristic value. Expressed as a formula, it is as follows: Data capacity = data volume coefficient 603 x data volume coefficient 703 x data volume characteristic value

[0064] The data volume characteristic value may be a fixed value held by the management computer 101, or may be a value inputted on a detailed setting screen (not shown) of the policy input screen 200.

[0065] In the sizing process (S403), the management computer 101 performs performance design processing for the computer resources used in the target system, such as performance calculations for virtual machines, storage functions, network functions, backup functions, and cluster functions. The performance design processing executed here may be performed using values ​​calculated by the above-mentioned sizing process (S403) and some kind of application program. Alternatively, the management computer 101 may hold multiple correspondence tables such as those shown in Fig. 12 as calculation information 133 and execute performance design processing for each function.

[0066] 12 is an explanatory diagram showing an example of a DB instance sizing table as a correspondence table used when sizing DB instances, as an example of data used in the performance design process for various functions as one of the calculation information 133. The DB instance sizing table 1200 has a DB transaction density field 1201 and a machine spec field 1202. The information in the DB instance sizing table 1200 is information that is prepared in advance either manually or by some application program. The machine specs illustrated in FIG. 12 are merely an example, and each company may store information for each service it provides.

[0067] When sizing a DB instance in the sizing process (S403), for example, the DB transaction density calculated in the above-mentioned sizing process (S403) is compared with the DB transaction density field 1201, and the value of the machine spec field 1202 of the row that fits the DB transaction density value is output as the size of the DB instance to be constructed.

[0068] In the sizing process (S403), the management computer 101 may calculate target values ​​for RPO and RTO to be input into a tool for estimating backup performance in order to estimate backup performance. Here, RPO is an abbreviation for Recovery Point Objective and is a recovery point target value that indicates the timing of the state to which the system should be restored when a failure occurs, tracing back from the occurrence of the failure. RTO is an abbreviation for Recovery Time Objective and is a target value for the target recovery time that indicates how long it will take to recover the system when a failure occurs. The RPO and RTO can be calculated, for example, by multiplying the value of the RTO coefficient field 604 in the industry table 600, the value of the RTO coefficient field in the scale table 700, and an RTO coefficient internally held by the management computer 101, all of which were acquired in the policy acquisition process (S401). Similarly, the target RPO value can be calculated by multiplying the value of the RPO coefficient field 605 of the industry table 600 acquired in the policy acquisition process (S401), the value of the RPO coefficient field of the scale table 700, and the RPO coefficient held internally by the management computer 101.

[0069] Furthermore, the RTO coefficient and RPO coefficient held internally by the management computer 101 may use values ​​set from a detailed setting screen (not shown) on the policy input screen 200. Furthermore, target values ​​for the RPO and RTO may be input directly from a detailed setting screen (not shown) on the policy input screen 200.

[0070] In the fee calculation process (S404) of the configuration plan calculation process flow 400, the management computer 101 executes fee calculation for each configuration. This may be executed by an application program that executes some kind of estimation of the fees for the functions used in each configuration. Alternatively, a fee table for each function used in the configuration condition information 132 may be stored as fee information 134, and the fees may be calculated using the values ​​calculated in the above-mentioned process of the configuration plan calculation process flow 400.

[0071] The configuration proposal sorting process (S405) of the configuration proposal calculation process flow 400 is a process for calculating the display priority of the calculated configuration proposal candidates. The cost and performance values ​​for each configuration proposal obtained by the sizing process (S403) of the configuration proposal calculation process flow 400, the values ​​of the logical fault tolerance field 1002, the AZ fault tolerance field 1003, and the Region fault tolerance field 1004 of the configuration condition information table 1000 as availability evaluation values ​​for each configuration, and the values ​​of the sort key field 502 and the order field 503 of the proposal priority table obtained by the policy acquisition process (S401) are used. In the fee calculation process (S404), the management computer 101 uses the information specified in the sort key field 502 to sort the proposals in the order specified by the information in the order field 503. For example, if the value of the proposal priority field 501 in the first row illustrated in FIG. 5 is "balance-oriented," the value of the sort key field is availability / cost. In this case, the management computer 101 calculates the sorting evaluation value by adding up the values ​​of the logical fault tolerance field 1002, the AZ fault tolerance field 1003, and the Region fault tolerance field 1004 in the configuration condition information table 1000 for each configuration and dividing the sum by the cost value calculated in the fee calculation process (S404), and sorts the results in descending order as indicated by the value of the order field 503. Note that the configuration evaluation area 312 of the configuration proposal presentation screen 300 shown in the example of Fig. 3 displays star ratings as a degree of recommendation, but the number of star ratings can be calculated according to a rule such as giving five stars to the configuration with the highest rating among the sorting evaluation values ​​calculated in the configuration proposal sorting process (S405), four stars to the top 10% of configurations, and three stars to the remaining top 30%.

[0072] The management computer 101 executes a construction execution process 122 that constructs a configuration corresponding to an arbitrary configuration plan 301 on the cloud service 104 in accordance with an instruction from a construction execution button 314 on a configuration plan presentation screen 300 displayed via the input / output device 141 of the operation terminal 102. The construction execution process 122 may be executed by some application program that issues a construction instruction by means of a command operation using an API or an automatic execution operation of a GUI, and in this case, the construction process may be realized by using program data stored in the repository server 105.

[0073] As described above, according to the embodiment of the present invention, the management computer 101 calculates sizing requirements based on policies related to the industry, scale, and availability of the target system, selects a system configuration that combines cloud service functions that satisfies the policy, and derives optimal system configuration candidates in order of recommendation based on the calculated sizing requirements and cost information. This makes it possible to determine an appropriate system configuration from among the many cloud services that exist, taking into account requirements such as performance and availability, and costs, and to automatically construct the target system as needed.

[0074] As described above, the disclosed computer system comprises a processor 111, a storage device 112, and an input / output device 141, wherein the storage device 112 stores at least configuration condition information 132 indicating an evaluation value for a system configuration that can be constructed on the cloud, the input / output device 141 receives a configuration request indicating conditions for the system configuration to be constructed on the cloud, the processor 111 obtains an evaluation value corresponding to the configuration request, compares the evaluation value corresponding to the configuration request with the evaluation value of the configuration condition information, and determines a candidate system configuration to propose based on the result of the comparison, and the input / output device 141 outputs the candidate system configuration to propose. Therefore, the disclosed computer system can support the appropriate selection of the configuration of a cloud system.

[0075] In addition, the processor 111 calculates evaluation values ​​for multiple items from the configuration request, uses some of the evaluation values ​​for the multiple items to narrow down the possible system configurations to potential system configurations, ranks the narrowed down system configurations based on the evaluation values ​​for the multiple items, and determines the system configuration to propose. At this time, the processor 111 ranks the proposed system configurations based on whether the size of the proposed system configuration is small and / or the cost of the proposed system configuration is low. By performing configuration pruning and sizing in stages in this way, an appropriate system configuration can be determined efficiently.

[0076] In addition, the configuration request indicates policies regarding the system's industry, scale, and availability, and the processor 111 converts the policies regarding the industry, scale, and availability into evaluation values ​​for multiple items and compares them with the evaluation values ​​of the configuration condition information. Then, the processor 111 narrows down the possible system configurations to candidate system configurations based on the evaluation value obtained from the availability, ranks the narrowed down system configurations based on the evaluation values ​​obtained from the industry and the scale, and determines the system configuration to propose. In this way, by pruning the configuration based on availability and sizing based on industry and scale, we can propose a system configuration that reliably meets recovery requirements while keeping costs down.

[0077] In addition, the input / output device 141 outputs the proposed system configuration candidates and evaluation values ​​corresponding to the configuration request, and accepts input of modifications to the configuration request, and the processor 111 re-determines the proposed system configuration candidates in accordance with the modifications. Then, the input / output device 141 receives a construction execution request for the output system configuration candidate, and the processor 111 executes the system construction process for the system configuration specified in the construction execution request. Therefore, it is possible to arbitrarily search for an appropriate system configuration and easily build the determined system configuration.

[0078] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, not only can the configurations be deleted, but also replacements and additions of configurations are possible. For example, in the above embodiment, configuration pruning is performed based on an availability policy, and sizing is performed based on an industry and size policy. However, other policies, such as a policy related to response time, can also be used. Furthermore, the same policy may be used for both configuration pruning and sizing. For example, configuration pruning may be performed based on the minimum response time, and then the response time score may be used for sizing. [Explanation of symbols]

[0079] 101: Management computer, 102: Operation terminal, 103: Network, 104: Cloud service, 105: Repository server, 111: Processor, 112: Storage device, 121: Configuration plan calculation process, 122: Construction execution process, 131: Policy conversion information, 132: Configuration condition information, 133: Calculation information, 134: Fee information

Claims

1. a processor; A storage device; an input / output device; the storage device stores at least configuration condition information indicating an evaluation value for a system configuration that can be constructed on the cloud; the input / output device receives a configuration request indicating conditions for a system configuration to be constructed on the cloud; the processor obtains evaluation values ​​for a plurality of items from the configuration request, narrows down the possible system configurations to candidate system configurations using some of the evaluation values ​​for the plurality of items, ranks the narrowed down system configurations based on the evaluation values ​​for the plurality of items, and determines candidate system configurations to propose; The input / output device outputs the proposed system configuration candidates. A computer system comprising:

2. 2. The computer system of claim 1, The computer system is characterized in that the processor ranks the proposed system configurations based on the size of the proposed system configurations being small and / or the cost of the proposed system configurations being low.

3. 2. The computer system of claim 1, The configuration request indicates policies regarding the type, size, and availability of the system; The processor evaluates the business type, the size, and the availability policy based on evaluation values ​​for a plurality of items. and comparing the calculated value with the evaluation value of the configuration condition information.

4. A computer system according to claim 3, The processor narrows down the possible system configurations to be candidates based on the evaluation value obtained from the availability, and ranks the narrowed down system configurations based on the evaluation values ​​obtained from the industry and the scale, thereby determining the system configuration to be proposed.

5. 2. The computer system of claim 1, the input / output device outputs the proposed system configuration candidates and evaluation values ​​corresponding to the configuration requests; Accepting input of modifications to the configuration request; The processor re-determines the proposed system configuration candidates in response to the modification. A computer system comprising:

6. 2. The computer system of claim 1, the input / output device receives a construction execution request for the output system configuration candidate; The computer system is characterized in that the processor executes a system construction process for a system configuration specified in a construction execution request.

7. a computer system that stores at least configuration condition information indicating an evaluation value for a system configuration that can be constructed on a cloud; receiving a configuration request indicating conditions for a system configuration to be built on the cloud; determining evaluation values ​​for a plurality of items from the configuration requirements; narrowing down possible candidate system configurations from the configurable system configurations using some of the evaluation values ​​of the plurality of items; a step of ranking the narrowed-down system configurations based on the evaluation values ​​of the plurality of items to determine candidates for the system configuration; A system configuration candidate output method comprising:

8. A computer system that stores at least configuration condition information indicating an evaluation value for a system configuration that can be constructed on a cloud, receiving a configuration request indicating conditions for a system configuration to be built on the cloud; determining evaluation values ​​for a plurality of items from the configuration requirements; narrowing down possible candidate system configurations from the configurable system configurations using some of the evaluation values ​​of the plurality of items; a step of ranking the narrowed-down system configurations based on the evaluation values ​​of the plurality of items to determine candidates for the system configuration; A system configuration candidate output program characterized by executing the above.

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