JP2015099500A - Storage unit updating apparatus, program, and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To further improve the accuracy of preliminary diagnosis.SOLUTION: A value in a table is changed when a VM can be constructed actually even though it is determined that the VM of a specified configuration cannot be constructed from values in a table which stores parameter values specifying a VM configuration which could be constructed in the past and parameter values entered this time to specify a VM configuration. For example, when a VM can be constructed actually even though a table 402 storing an actual record in which a VM could be constructed stores CPU performance values up to 2.5 GHz and a parameter this time specifies CPU performance values up to 4.0 GHz, the 2.5 GHz stored in the table is changed to 4.0 GHz.

Description

  The present invention relates to a storage unit update device, a program, and a method.

  Before building a system such as a virtual machine (VM) in a cloud environment was generalized, an administrator with abundant experience built the system. An experienced administrator had few errors in setting input parameters related to system construction. However, when it becomes possible for general users to construct a system in a cloud environment, the frequency with which the system is constructed increases significantly. Along with this, the situation where mistakes occur in the setting of input parameters related to system construction has increased dramatically.

  Therefore, conventionally, a correspondence relationship between the input parameter and the creation processing result indicating whether or not the VM according to the input parameter has been created is accumulated. When a parameter is input, based on the accumulated creation processing result, it is performed to diagnose in advance whether a VM can be created according to the input parameter.

  For example, in the past, when 2 GHz was specified as the maximum value of the performance value of the virtual CPU, if the VM could not be created, the maximum value of the performance value of the virtual CPU = 2 GHz and the VM could not be created Stored as a relationship. When the user newly designates 3 GHz as the maximum value of the performance value of the virtual CPU as a parameter, it is diagnosed in advance that a VM cannot be created from the past correspondence relationship, and the user is notified.

  As described above, it is considered that the more the above correspondence is accumulated, the more accurate the pre-diagnosis is.

JP 2006-181263 A

However, in a cloud environment, the amount allocated to the virtual CPU of the VM varies. For example, an actual CPU in the cloud environment is replaced with a CPU with high performance, or a VM that has already been created disappears. Therefore, in the above example, for example, the maximum value of the performance value of the virtual CPU may increase to 4 GHz, for example. However, in the above example, since the correspondence between the maximum value of the performance value of the virtual CPU = 2 GHz and the VM could not be created is stored, when the user specifies 3 GHz as the maximum value of the performance value of the virtual CPU The user is notified in advance that the VM cannot be created.
As described above, the accuracy of the pre-diagnosis may not be improved even if the accumulated amount of the correspondence relationship is increased.

  As one aspect, it is an object to further improve the accuracy of prior diagnosis whether or not a virtual machine can be configured.

  In one aspect, the receiving unit receives a specified value that specifies the configuration of the virtual machine. The storage unit stores at least one specified value specifying the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value is configured. The determination unit receives the designated value received based on the received specified value, the stored content stored in the storage unit, and the actual result of whether or not the virtual machine according to the received specified value can be configured. It is determined from the stored contents whether there is a contradiction that does not produce an actual result. When it is determined that a contradiction has occurred, the changing unit changes the stored content so that no contradiction occurs.

  As one aspect, there is an effect that it is possible to further improve the accuracy of pre-diagnosis as to whether or not a virtual machine can be configured.

It is a figure which shows the management system 10 provided with the diagnostic apparatus 12 and the cloud management system 14. FIG. 2 is a block diagram of a diagnostic device 12. FIG. (A) shows the functional unit of the diagnostic device 12, and (B) is a diagram showing each process of the diagnostic learning program of the diagnostic device 12. (A) shows the state management table 401, (B) shows the normal parameter management table 402, and (C) shows the abnormal parameter management table 403. (A) shows a correlation table (normal system) 404 and a parameter relationship table (normal system) 405, and (B) shows a parameter relationship table (abnormal system) 406 and a correlation table (abnormal system) 407. (C) is a diagram showing an interrelation check list 408. (A) shows a setting window 70 for setting a specified value for specifying the contents of the VM to be created when creating (deploying) the virtual server (VM), and (B) shows the virtual server (VM). It is a figure which shows the setting window 90 for setting the designated value which designates the content of VM to change in the case of a structure change. It is a flowchart which shows an example of the process which updates the state management table 401 according to the changed content started when the administrator of a system (physical server 26, 28 ... 30) instruct | indicates the change of a setting. It is a flowchart which shows an example of the diagnostic learning process which learns the prior diagnosis and the execution result which the diagnostic apparatus 12 performs. It is a flowchart which shows an example of the prior diagnosis process of step 112 of the diagnosis learning process of FIG. It is a flowchart which shows an example of the normal performance check process of step 126 of the prior diagnosis process of FIG. It is a flowchart which shows an example of the abnormality performance check process of step 128 of the prior diagnosis process of FIG. It is a flowchart which shows an example of the correlation check process of step 130 of the prior diagnosis process of FIG. It is a flowchart which shows an example of the execution result process of step 118 of the diagnostic learning process of FIG. It is a flowchart which shows an example of the update process of the normal time parameter management table of step 202 of the execution result process of FIG. It is a flowchart which shows an example of the update process of the parameter management table at the time of abnormality of step 204 of the execution result process of FIG. (A) shows a state of update processing of the normal parameter management table when the VM is created (normal), and (B) shows an abnormal parameter management table when the VM is created (normal). It is a figure which shows the mode of this update process. It is a flowchart which shows an example of the update process of the parameter relationship table (normal system) 405 of step 206 of the execution result process of FIG. (A) and (C) show how the parameter relationship table (normal system) 405 is updated, and (B) and (D) show how the correlation check list 408 is updated. . It is a flowchart which shows an example of the acquisition process which acquires the parameter of the cause of abnormality of step 214 of the execution result process of FIG. (A) and (C) show how the correlation table (abnormal system) 407 is updated when the VM is not created, and (B) and (D) show the parameter relationship table (normal system). The state of the update process 405 is shown, and (E) is a view showing the state in which the correlation check list 408 is updated.

Hereinafter, an example of an embodiment of the disclosed technology will be described in detail with reference to the drawings.
FIG. 1 shows a management system 10 including a diagnostic device 12 and a cloud management system 14. A plurality of user terminals 16, 18,... 20 are connected to the diagnostic device 12 via a network 22 such as the Internet. A plurality of physical servers 26, 28,... 30 are connected to the cloud management system 14 via a network 24 such as a local area network.
The diagnostic device 12 is an example of a storage unit update device according to the technique of the present disclosure.

  A virtual machine (VM (Virtual Machine)) such as a virtual server is created in the diagnostic device 12 of the management system 10 from the plurality of user terminals 16, 18,... To instruct. When making the instruction, the user terminal 16 transmits a specified value for instructing what kind of VM to create to the diagnostic device 12. For example, the user terminal 16 transmits a specified value such as 3 GHz to the management system 10 as the performance of the CPU (Central Processing Unit).

  Based on the received specified value, the diagnosis device 12 determines whether or not the cloud management system 14 can create a VM having the content specified in the specified value before creating the VM in advance. To do.

  The plurality of user terminals 16, 18,... 20, the diagnostic device 12, the cloud management system 14, and the plurality of physical servers 26, 28,. I will explain only.

FIG. 2 shows a block diagram of the diagnostic device 12. As shown in FIG. 2, in the diagnostic device 12, a CPU 32, a ROM (Read Only Memory) 34, and a memory (RAM (Random Access Memory)) 36 are connected to each other via a bus 38. Further, a secondary storage device 40 and a magnetic disk drive device 42 are connected to the bus 38. The magnetic disk drive device 42 has a built-in magnetic disk 44. The diagnostic device 12 includes a display control unit 46, a display device 48 connected to the display control unit 46, an input device 50, and a communication control unit 52. A plurality of user terminals 16, 18... 20 and the cloud management system 14 are connected to the communication control unit 52. The secondary storage device 40 is provided with various tables (401 to 408) described later.
The secondary storage device 40 is an example of a storage unit according to the technique of the present disclosure.

  As the display device 48, a liquid crystal display device (LCD), a cathode ray tube (CRT), an organic electroluminescence display device (OELD), a plasma display panel (PDP), a field emission display (FED), or the like can be applied. As the input device 50, a keyboard or a mouse can be applied.

FIG. 3A shows a functional unit of the diagnostic device 12. The diagnostic device 12 includes, for example, an input parameter extraction processing unit 62 that extracts the specified value (parameter) from a signal input from the user terminal 16. The function unit includes a pre-diagnosis processing unit 64 that performs the pre-diagnosis based on the table in the secondary storage device 40 and the extracted parameters. Further, the functional unit includes an execution result learning processing unit 66.
The execution result learning processing unit 66 is an example of a determination unit and a change unit of the technology of the present disclosure.

  The ROM 34 stores a diagnostic learning program. The CPU 32 reads out the diagnostic learning program from the ROM 34, develops it in the memory 36, and executes the process of the diagnostic learning program.

  FIG. 3B shows the process of the diagnostic learning program. The diagnostic learning program process includes an input parameter extraction process 63, a pre-diagnosis process 65, and an execution result learning process 67.

The CPU 32 operates as the units 62 to 66 in FIG. 3A by executing each of the processes 63 to 67 shown in FIG.
The ROM 34 is an example of a storage medium according to the technology of the present disclosure.

  Although the case where the diagnostic learning program is read from the ROM 34 is illustrated here, it is not necessarily stored in the ROM 34 from the beginning. For example, a diagnostic learning program is first stored in an arbitrary “portable storage medium” such as an SSD (Solid State Drive), a DVD disk, an IC card, a magneto-optical disk, or a CD-ROM connected to the diagnostic apparatus 12. It may be left. Then, the diagnostic device 12 may acquire and execute a diagnostic learning program from these portable storage media. Further, the diagnostic learning program may be stored in a storage unit such as another computer or server device connected to the diagnostic device 12 via a communication line. In this case, the diagnostic device 12 acquires and executes a diagnostic learning program from another computer or server device.

4 and 5 show various tables provided in the secondary storage device 40. FIG.
FIG. 4A shows a state management table 401. In the state management table 401, information indicating the contents of the states of the physical servers 26, 28... 30 is stored. The state of the physical servers 26, 28... 30 is determined by information indicating whether overcommit is set for each pool, information indicating whether the application process is performed, information indicating whether or not to charge, and the like. . As shown in FIG. 4A, the state management table 401 indicates information indicating whether overcommit is set for each pool, information indicating whether an application process is performed, and whether or not to charge. Each area for storing information and the like is provided. For example, the state of the physical servers 26, 28,... That is, there is no overcommit setting for each physical server in pool A and pool B (OFF), the application process is performed (ON), and no charge is made (OFF). .

  In this embodiment, the physical servers 26 and 28 are grouped as a pool A as physical servers having relatively high performance (spec). Further, physical servers 30 and the like are grouped as a pool B as physical servers having relatively low performance (spec). In the state A, the overcommit setting for the pool A is OFF. Therefore, the OFF information in the pool A indicates that the maximum value assigned to the virtual CPU of the VM provided in the pool A is less than or equal to the maximum value assigned to the CPUs of the physical servers 26 and 28.

  Since it is set (ON) that the application process is performed, it is indicated that it has been determined whether or not the user apparatus side has given permission for the VM setting application. Since no charging is set (OFF), it is indicated that charging was not performed.

  The state of the physical servers 26, 28... 30 may be changed by the administrator depending on the situation. The contents of the different states are stored in the state management table 401. Note that the current state is state C, and there is no state having the same contents in the past.

  FIG. 4B shows a normal parameter management table 402. “Normal” means that a VM according to the specified value has been created, as will be described later. The normal parameter management table 402 stores, for each state recognized by the state management table 401 (FIG. 4A), for example, a normal range of designated values designated by the user of the user terminal 16. This range increases over time. For example, in state A, it is stored that a value that can be designated as the maximum value in the normal range of CPU performance is up to 3 GHz.

  FIG. 4C shows an abnormal parameter management table 403. Abnormal means that a VM according to the specified value could not be created. The abnormal parameter management table 403 stores a specified value that causes the abnormality for each state recognized by the state management table 401 (FIG. 4A). The number of specified values stored increases over time. For example, in the state A, since the specified value of the CPU performance is 4 GHz or 3.5 GHz, it is indicated that an abnormality has occurred.

  FIG. 5A shows an interrelation table (normal system) 404 and a parameter relationship table (normal system) 405.

  An interrelation table (normal system) 404, which is the upper table in FIG. 5A, shows the interrelationship between the requested amount of computing resources (resource) and the amount of computing resources that can be supplied in the normal state. Information to be stored is stored. That is, for example, a table CPU-memory is stored corresponding to the CPU and the memory. A table CPU-CPU pool is stored in correspondence with the CPU and CPU pool remaining capacity. “Table” means that an area in which the table CPU-CPU pool is stored is linked to an area described later in the parameter relationship table (normal system) 405.

  Here, the CPU pool remaining capacity (simply referred to as CPU pool) will be described. In the deployment destination pool as one of the designated values designated by the user, a value that designates in which pool the VM is created is designated. For example, assume that pool A is designated. The CPU pool remaining capacity refers to the remaining capacity of the computing resource allocated to the virtual CPU of the VM created in the pool A.

  The inter-parameter relationship table (normal system) is linked to each area in the inter-relation table (normal system) 404 of FIG. For example, the parameter relationship table (normal system) 405 shown in FIG. 5A is linked to the table CPU-CPU pool in FIG. The inter-parameter relationship table (normal system) 405 includes the following information in each of the three patterns between the allocation amount allocated to the VM virtual CPU and the remaining capacity allocated to the VM virtual CPU created in the pool: Is remembered. That is, information (“Yes”, “No”) indicating whether the VM has been successfully created or not is stored. For example, the following contents are stored in the upper row of the parameter relationship table (normal system) 405 of FIG. That is, “None” is stored in correspondence with CPU (allocation amount allocated to VM virtual CPU)> CPU pool (remaining capacity allocated to VM virtual CPU created in the pool). Therefore, in a certain state, it is indicated that the VM has never been created due to the relationship of (allocation amount allocated to the VM CPU)> (remaining capacity allocated to the VM CPU created in the pool). .

  FIG. 5B shows an interrelation table (abnormal system) 406 and an inter-parameter relationship table (abnormal system) 407. The interrelation table (abnormal system) 406 and the inter-parameter relationship table (abnormal system) 407 are tables when the VM cannot be created with the specified contents (abnormal), and is a table shown in FIG. Therefore, detailed description thereof is omitted. In the upper row in the parameter relationship table (abnormal system) 407 in FIG. 5B, (allocation amount allocated to the VM CPU)> (remaining capacity allocated to the VM CPU created in the pool A). Correspondingly, “Yes” is stored. Therefore, in a certain state, it is indicated that the VM has not been created due to the relationship of (allocation amount allocated to the VM CPU)> (remaining capacity allocated to the VM CPU created in the pool A). Yes.

  FIG. 5C shows an interrelation check list 408. The correlation check list 408 is a table obtained by extracting those recognized as having an abnormality in the correlation between the correlation table (abnormal system) 406 and the parameter relationship table (abnormal system) 407. Each time the parameter relationship table (abnormal system) 407 is updated, the diagnostic device 12 extracts the one recognized as having an abnormality in the correlation and stores it in the correlation check list 408.

Next, the operation of this embodiment will be described.
For example, the user terminal 16 stores an instruction program for instructing the management system 10 to create (deploy) a VM and change the configuration. When this instruction program is executed, on the screen of the display device 48 of the user terminal 16, in the case of creation (deployment) of a VM, a designated value for designating the contents of the VM to be deployed shown in FIG. A setting window 70 for designating is displayed.

  As shown in FIG. 6A, the setting window 70 is provided with areas 72 to 82 for designating the following designated values. In the area 72, a virtual machine name is designated. In the area 74, CPU performance (GHz) is specified. In the area 76, the number of CPUs is designated. In the area 78, a memory capacity (GB) is designated. In the area 80, a disk size (secondary storage device capacity) (GB) is designated. In the area 82, a deployment destination pool is specified.

  When this instruction program is executed, the designated value for designating the contents of the VM to be changed as shown in FIG. 6B is displayed on the screen of the display device 48 of the user terminal 16 in the case of changing the configuration of the VM. A setting window 90 for designating is displayed.

  As shown in FIG. 6B, the setting window 90 is provided with areas 92 to 100 for designating the following designated values. In the area 92, a target virtual machine whose configuration is to be changed is designated. In the area 94, the CPU performance (GHz) is designated. In the area 96, the number of CPUs is designated. In the area 98, a memory capacity (GB) is designated. In the area 100, an additional disk size (capacity of the secondary storage device) (GB) is designated.

  FIG. 7 shows a state management table update process that starts when the administrator of the system (physical servers 26, 28... 30) instructs to change the setting and updates the state management table 401 according to the changed contents. An example is shown as a flowchart.

  When the state management table update process starts, the diagnostic device 12 acquires the changed setting content from the cloud management system 14 in step 102. In step 104, the diagnostic device 12 determines whether the same state as the acquired content is stored in the state management table 401. If it is determined that the same state as the acquired content is stored in the state management table 401, the state management table update process ends. On the other hand, when it is determined that the same state as the acquired content is not stored in the state management table 401, the diagnostic device 12 registers the content acquired in step 102 in the state management table 401 in step 106. (Remember. For example, before the current state management table update process is executed, only the contents of state A and state B are stored in the state management table 401 as shown in FIG. . Then, it is assumed that the setting contents changed this time are that the overcommit is ON for each of the pools A and B, the application process is ON, and the billing is ON. This state is different from states A and B. That is, it is a new state. Therefore, the determination result in step 104 is negative. Therefore, the contents acquired in step 102 (overcommit is ON for each pool A, B, application process is ON, billing is ON) are stored as state C.

  As described above, the setting contents of the system (physical servers 26, 28... 30) are stored in the state management table 401 for each state.

  By the way, a plurality of user terminals 16, 18,... 20 (see FIG. 1), for example, a user terminal 16 creates a VM or changes a configuration of a VM that has already been created in the diagnostic device 12 of the management system 10. Instructed.

  For example, in the user terminal 16, when the instruction program starts and VM creation is specified, a setting window 70 shown in FIG. 6A is displayed on the display device 48 of the user terminal 16. The user designates the virtual machine name in the area 72, the CPU performance in the area 74, the number of CPUs in the area 76, and the memory capacity (GB) in the area 78 via the input device 50. Enter. Thereafter, when a transmission button (not shown) is turned on, these designated values (hereinafter referred to as parameters) are transmitted together with a command indicating a VM creation instruction.

  Further, when the instruction program is started and the VM configuration change is designated on the user terminal 16, a setting window 90 shown in FIG. 6B is displayed on the display device 48 of the user terminal 16. Through the input device 50, the user selects the target virtual machine whose configuration is to be changed in the area 92, the CPU performance (GHz) in the area 94, the number of CPUs in the area 96, and the memory capacity (GB) in the area 98. Each designation value for designating the additional disk size (GB) is input to the area 100. Thereafter, when a transmission button (not shown) is turned on, these parameters are transmitted to the diagnostic device 12 together with a command indicating a VM configuration change instruction.

  When the diagnostic device 12 receives VM creation and configuration change commands together with the above parameters, the diagnostic learning process of FIG. 8 starts. Since the diagnosis learning process when the VM creation and configuration change commands are received by the diagnostic device 12 is the same, the case where a VM creation command is received will be described below as an example.

  In step 110 of FIG. 8, the input parameter extraction processing unit 62 extracts the input parameters. As a result, the contents of the parameters are extracted. In step 114, the pre-diagnosis processing unit 64 determines in advance whether a VM is created (normal) or not created (abnormal) according to the parameter extracted in step 112.

  In the next step 114, the pre-diagnosis processing unit 64 transmits the parameter extracted in step 110 to the cloud management system 14, and requests a VM creation process according to the parameter.

  The cloud management system 14 executes a VM creation process with the requested content. When a VM can be created with the requested content, a normal signal indicating that the VM has been created is transmitted to the diagnostic device 12. If the VM cannot be created with the requested content, an abnormal signal indicating that the VM has not been created is transmitted to the diagnostic device 12.

  In step 116, the execution result learning processing unit 66 acquires the result by receiving the normal signal or the abnormal signal. In step 118, the execution result learning processing unit 66 executes execution result processing based on the acquired result.

  Next, with reference to FIG. 9, the specific content of the pre-diagnosis process of step 112 of FIG. 8 is demonstrated. In step 122 of FIG. 9, the pre-diagnosis processing unit 64 acquires the setting state of the cloud management system 14. That is, the prior diagnosis processing unit 64 instructs the cloud management system 14 to notify the setting state of the system (physical servers 26, 28,... 30). The instructed cloud management system 14 checks the current system setting state and transmits the current setting state to the diagnostic device 12. Thereby, the advance diagnosis processing unit 64 acquires the setting state of the cloud management system 14.

  In step 124, the pre-diagnosis processing unit 64 compares the setting state acquired in step 122 with the contents of the state management table 401, and manages the state identification information (state i) corresponding to the acquired setting state. Obtained from the table 401. When the setting state acquired in step 122 is not in the state management table 401, the pre-diagnosis processing unit 64 adds the setting state acquired in step 122 to the state management table 401.

  The advance diagnosis processing unit 64 executes normal result check processing in step 126, abnormal result check processing in step 128, and correlation check processing in step 130. In step 132, the advance diagnosis processing unit 64 feeds back to the user terminal 16.

Next, each process of steps 126, 128, and 130 will be described.
FIG. 10 is a flowchart showing an example of the normal performance check process in step 126 of FIG. In step 142, the pre-diagnosis processing unit 64 initializes a flag Fp described later and a variable p for identifying each input parameter to 0. In step 144, the advance diagnosis processing unit 64 increments the variable p by 1. For example, the CPU maximum value is identified when p = 1, and the CPU minimum value is identified when p = 2.

  In step 146, a value vi corresponding to the parameter p in the column of state i in the normal parameter management table 402 (FIG. 4B) is acquired. For example, assume that p = 1. In this case, in state i = state A, CPU maximum value = 3 GHz is acquired as value vi. In step 148, the pre-diagnosis processing unit 64 acquires the value vp identified by the variable p among the input parameters. That is, in the above example, the maximum value (vp) of the CPU is obtained from the input parameter.

  In step 150, the pre-diagnosis processing unit 64 determines whether or not vp is a normal value based on the acquired vi and vp. The normal parameter management table 402 stores the maximum CPU value = 3 GHz. This indicates that it was normal in the past up to the maximum value of the CPU = 3 GHz. That is, if the CPU's maximum indication value (vp) in the current input parameter is 3 GHz or less, it can be determined that the VM is created (normal). On the contrary, if the instruction value (vp) of the maximum value of the CPU in the current input parameter exceeds 3 GHz, it can be determined that the VM is not created (abnormal).

  If the determination result in step 150 is affirmative, the normal performance check process proceeds to step 152. If the determination result of step 150 is negative, the flag Fp corresponding to the variable p is set to 1 in step 154. By determining whether or not 1 is set in the flag Fp, it is possible to recognize which of the input parameters is an abnormal value.

  In step 152, it is determined whether or not the variable p is equal to the total number P of input parameters. If the determination result of step 152 is negative, there is a parameter for which it is not determined whether or not it is a normal value, and the process returns to step 144. On the other hand, if it is determined whether all parameters are normal values, the determination result in step 152 is affirmative. Therefore, the normal performance check process ends, and the process proceeds to step 128 in FIG.

  FIG. 11 is a flowchart showing an example of the abnormality record check process in step 128 of FIG. In step 162, the pre-diagnosis processing unit 64 initializes a flag Gp and a variable p, which will be described later, to zero. In step 164, the advance diagnosis processing unit 64 increments the variable p by 1.

  In step 166, the pre-diagnosis processing unit 64 obtains the actual abnormality value wi corresponding to the parameter p in the column of the state i in the abnormal parameter management table 403 (FIG. 4C). For example, as described above, the maximum value of the CPU is identified by p = 1. Therefore, in Step 166, 4 GHz is acquired as a value determined to be abnormal in the past in the CPU in the state i (for example, state A) in the abnormal parameter management table 403. As shown in the abnormal parameter management table 403, when a plurality of values are stored corresponding to the state i = state A and the CPU, the following processing is executed for each. In step 170, the advance diagnosis processing unit 64 determines whether or not the value wi = value vp. That is, it is determined whether the value vp identified by the variable p in the input parameter has been an abnormal value in the past.

  If the determination result in step 170 is affirmative, in step 172, the preliminary diagnosis processing unit 64 sets the flag Gp identified by the variable p to 1. Therefore, by determining whether or not 1 is set in the flag Gp, it is possible to recognize which of the input parameters is an abnormal value.

  In step 174, it is determined whether or not the variable p is equal to the total number P of input parameters. If the determination result in step 174 is negative, there is a parameter for which it is not determined whether or not the value is an abnormal value, and the process returns to step 164. On the other hand, if it is determined whether or not all parameters are abnormal values, the determination result in step 174 is affirmative. Therefore, the abnormality record check process ends, and the process proceeds to step 130 in FIG.

  FIG. 12 is a flowchart showing an example of the interrelation check process in step 130 of FIG.

  In step 182 of FIG. 12, the pre-diagnosis processing unit 64 initializes a flag Hq, which will be described later, and a variable q for identifying a check target in the correlation check list 408 (FIG. 5C) to 0. In step 184, the advance diagnosis processing unit 64 increments the variable q by 1. Each time q increases by 1 from 0, items to be checked are identified in order from the top of the correlation check list 408.

  In step 186, an item to be checked identified by the variable q, that is, an abnormal relationship is acquired. For example, when q = 1, the relationship of CUP> CPU pool is acquired.

  In step 190, the pre-diagnosis processing unit 64 acquires a value vq1 corresponding to the check item q in the input parameter. In the above example, as the value vq1, the maximum value of CPU performance, that is, a value that is requested to be allocated to the virtual CPU in the VM is acquired. Further, the pre-diagnosis processing unit 64 identifies the placement destination pool in this step 196, acquires the value of the remaining capacity allocated to the virtual CPU of the VM in the identified pool from the cloud management system 14, and uses this. The value is vq2.

  In step 192, it is determined whether or not the values vq1 and vq2 satisfy the abnormal relationship acquired in step 186. That is, in the above example, it is determined whether value vq1> value vq2 is satisfied. For example, it is assumed that the value vq1 = 3.5 GHz and the value vq2 = 1.0 GHz. In this case, the determination result of step 192 is affirmative, and the process proceeds to step 194. For example, it is assumed that the value vq1 = 3.5 GHz and the value vq2 = 100.0 GHz. In this case, the determination result of step 192 is negative, and the process proceeds to step 196.

  In step 194, the pre-diagnosis processing unit 64 sets 1 to the flag Hq. By determining whether or not 1 is set in the flag Hp, it is possible to recognize which check item is established among the respective check targets in the correlation check list 408.

  In step 196, the preliminary diagnosis processing unit 64 determines whether or not the variable q is the total number Q of check items. If the determination result in step 196 is negative, there is a check item that has not yet been determined as to whether or not it has been established, and the process returns to step 184. On the other hand, if all the check items are checked, the determination result in step 196 is affirmative. In this case, the correlation check process ends, and the process proceeds to step 132 in FIG.

  In step 132, the pre-diagnosis processing unit 64 executes a feedback process. Specifically, it is determined whether each flag Fp (F1 to FP), each Gp (G1 to GP), and Hq (H1 to HQ) is set, and which abnormality is established. And informs the user terminal 16 of the contents.

  When the process of step 132 is finished, the pre-diagnosis process is finished, and the process proceeds to step 114 of FIG. In step 114, the pre-diagnosis processing unit 64 transmits the parameter extracted in step 110 to the cloud management system 14, and requests VM creation processing according to the parameter.

  The cloud management system 14 executes a VM creation process with the requested content. When a VM can be created with the requested content, a normal signal indicating that the VM has been created is transmitted to the diagnostic device 12. If the VM cannot be created with the requested content, an abnormal signal indicating that the VM has not been created is transmitted to the diagnostic device 12.

  In step 116, the execution result learning processing unit 66 acquires the result by receiving the normal signal or the abnormal signal. In step 118, the execution result learning processing unit 66 executes execution result processing based on the acquired result.

FIG. 13 is a flowchart showing an example of the execution result process of step 118 of the diagnostic learning process of FIG.
In step 200 of FIG. 13, the execution result learning processing unit 66 determines whether the execution result is normal, that is, whether a VM has been created according to the parameter contents.

  If the VM can be created according to the parameter contents, the execution result process proceeds to step 202. In step 202, the execution result learning processing unit 66 updates the range of normal values in the normal parameter management table 402 (FIG. 4B). In other words, the normal range stored in the normal parameter management table 402 until the previous time may be expanded by the creation (normal) of the current VM. That is, in this preliminary diagnosis, the parameter value is out of the normal value range in the normal parameter management table 402, and thus is determined to be abnormal. However, this time the VM was created (normal). Therefore, the execution result learning processing unit 66 in the normal-time parameter management table 402 so that the parameter value is determined to be a normal value if the value of the parameter is within the current range in the subsequent pre-diagnosis. Update the normal value range.

FIG. 14 is a flowchart showing an example of update processing of the normal parameter management table 402 in step 202 of FIG.
In step 232, the execution result learning processing unit 66 initializes the variable p to 0, and in step 234 increments the variable p by 1. In step 236, the execution result learning processing unit 66 is identified by the value vp identified by the variable p from the input parameters and the variable p in the state i of the normal parameter management table 402 (FIG. 4B). Get the value vi.

  In step 238, the execution result learning processing unit 66 determines whether or not the value vp is an abnormal value on the normal parameter management table 402. If the determination result in step 238 is affirmative, in step 240, the execution result learning processing unit 66 sets the value vp to the value vi.

  This process will be further described with reference to FIG. FIG. 16A shows how the normal parameter management table 402 is updated when the VM is created (normal). The value vp (maximum CPU value) identified by the variable p from the input parameters is 4.0 GHz, and the value vi identified by the variable p in the state i (for example, state C) of the normal parameter management table 402. Is 2.5 GHz. In the pre-diagnosis process, vp is not determined to be a normal value (No in step 150 in FIG. 10). However, this time the VM was created (normal). That is, the VM is not created from the relationship between the value vp and the value vi, but there is a contradiction in which the VM is created. Therefore, if the value vi is the value vp = 4.0 GHz, in step 240, the parameter value is determined to be normal if the parameter value is within the current range in the subsequent pre-diagnosis. The value vp is set to the value vi. This ensures no contradiction.

If the determination result of step 238 is negative, the update process proceeds to step 242. Even after the process of step 240 is executed, the update process proceeds to step 242.
In step 242, the execution result learning processing unit 66 determines whether or not the variable p is equal to the total number P of input parameters. If the determination result in step 242 is negative, the update process returns to step 234 because there are parameters for which the update process has not been determined.

On the other hand, if the determination result of step 242 is affirmative, the update process ends, and the execution result process proceeds to step 204 in FIG.
In step 204 of FIG. 13, when the value of the parameter input this time is stored in the abnormal parameter management table 403, the execution result learning processing unit 66 stores the value in the abnormal parameter management table 403 (FIG. 4 (C)). That is, when the parameter value input this time is stored in the abnormal parameter management table 403, it is determined as an abnormal value in the preliminary diagnosis (step 170 in FIG. 11). However, a VM was created with the parameters entered this time (normal). Therefore, the value of the parameter input this time is deleted from the parameter management table 403 at the time of abnormality so that it is not determined to be abnormal in the prior diagnosis after the next time.

The process of step 204 will be described in detail. FIG. 15 is a flowchart showing an example of the abnormality parameter management table update process in step 204 of FIG.
In step 252, the execution result learning processing unit 66 initializes the variable p to 0, and in step 254 increments the variable p by 1. In step 256, the execution result learning processing unit 66 acquires the value vp identified by the variable p from the input parameters.

  In step 258, the execution result learning processing unit 66 determines whether or not the value vp is stored in an area corresponding to the parameter p of the abnormal parameter management table 403. If the determination result in step 258 is affirmative, the execution result learning processing unit 66 deletes the value vp from the abnormal parameter management table 403 in step 260.

  This process will be further described with reference to FIG. FIG. 16B shows how the parameter management table 403 is updated when the VM is created (normal). The value vp (value indicating the performance of the CPU) identified by the variable p from the input parameters is 4.0 GHz, and is identified by the variable p in the state i (for example, the state C) of the abnormal parameter management table 403. Assume that the value vi is 4.0 GHz.

  In the pre-diagnosis process, vp is determined to be an abnormal value (No in step 170 in FIG. 11). However, this time the VM was created (normal). That is, the VM is not created from the relationship between the value vp and the value vi, but there is a contradiction in which the VM is created. Therefore, if the value vp = 4.0 GHz is deleted from the abnormal parameter management table 403, it will not be determined as an abnormal value even if the parameter value is the current value vp = 4.0 GHz in the subsequent pre-diagnosis. That is, no contradiction occurs. In step 260, the execution result learning processing unit 66 deletes the value vp from the abnormal parameter management table 403.

If the determination result of step 258 is negative, the update process proceeds to step 262. After step 260, the update process proceeds to step 262.
In step 262, the execution result learning processing unit 66 determines whether or not the variable p is equal to the total number P of input parameters. If the determination result in step 262 is negative, the update process returns to step 254 because there are parameters for which the update process has not been determined.

On the other hand, if the determination result in step 262 is affirmative, the update process ends, and the execution result process proceeds to step 206 in FIG.
In step 206, the execution result learning processing unit 66 updates the parameter relationship table (normal system) 405 (the lower side of FIG. 5A). That is, the execution result learning processing unit 66 determines that the relationship between parameters input this time is not in the parameter relationship table (normal system) 405 (lower side of FIG. 5A), the parameter relationship table (normal system). ) In 405, the relationship between the parameters input this time is added.

FIG. 17 is a flowchart showing an example of the update process of the parameter relationship table (normal system) 405 in step 206 of FIG.
In step 272 of FIG. 17, the execution result learning processing unit 66 initializes a variable r for identifying the mutual relationship in the correlation table (normal system) 404 to 0. In step 274, the execution result learning processing unit 66 Increment r by 1.

  In step 276, the execution result learning processing unit 66 acquires values vi and vr corresponding to the mutual relationship r identified by the variable r in the input parameters. For example, when the correlation r identified by the variable r is CPU <CPU pool, the execution result learning processing unit 66 acquires the CPU performance value vi from the input parameters. Further, the execution result learning processing unit 66 inquires the cloud management system 14 and acquires the remaining capacity vr allocated to the virtual CPU in the pool obtained from the value indicating the deployment destination pool.

  In step 278, the execution result learning processing unit 66 sets m as the relationship between the CPU performance value vi and the remaining capacity vr allocated to the CPU in the pool. For example, CPU performance value vi <remaining capacity vr, that is, CPU <CPU pool is m.

  In step 280, the execution result learning processing unit 66 determines whether or not the relationship corresponding to the mutual relationship m is stored as “none” in the parameter relationship table (normal system) 405. If the determination result in step 280 is affirmative, in step 290, the execution result learning processing unit 66 changes “none” to “present”.

FIGS. 18A and 18C show how the parameter relationship table (normal system) 405 is updated. As described above, the correlation between parameters obtained from the input parameters is CPU <CPU pool. When a VM is created according to this parameter, the parameter relationship table (normal system) 405 is changed to “Yes” corresponding to the relationship.
In step 292, the execution result learning processing unit 66 determines whether or not the variable r has reached the total number R of correlations in the correlation table (normal system) 404. If the determination result of step 292 is negative, the process returns to step 274. If the determination result in step 292 is affirmative, the update process ends, and the execution result process proceeds to step 208 in FIG.

  In step 208, the execution result learning processing unit 66 determines whether new information has been added in step 206. If the determination result of step 208 is negative, the execution result process ends and the diagnostic learning process also ends.

  When the determination result in step 208 is affirmative, in step 210, the execution result learning processing unit 66 also passes the link from the correlation table (abnormal system) 406 to the parameter relationship table (abnormal system) 407. It is determined whether or not the correlation m exists. If the determination result of step 210 is negative, the execution result process ends and the diagnostic learning process ends.

  When the determination result in step 210 is affirmative, in step 212, the execution result learning processing unit 66 deletes the corresponding correlation from the correlation check list 408 that is updated according to the update of the tables 406 and 407. The interrelation check list 408 is a table that stores items of abnormal correlations extracted based on the contents of the parameter relationship table (abnormal system) 406 and the correlation table (abnormal system) 407. The mutual relationship in which the VM has been created this time is not an abnormal correlation item, and is a relationship that is not stored in the correlation check list 408. That is, if the determination result in step 210 is affirmative, a contradiction has occurred. Therefore, as illustrated in FIGS. 18B and 18D, the execution result learning processing unit 66 deletes the corresponding correlation from the correlation check list 408. This is to prevent the pre-diagnosis process from the next time from being determined to be an abnormal relationship. When the process of step 212 is completed, the diagnostic learning process is ended.

If the determination result in step 200 of FIG. 13 is negative, that is, if a VM according to the input parameters cannot be created (abnormal), the execution result process proceeds to step 214. In step 214, the execution result learning processing unit 66 compares the contents of the normal parameter management table 402 with the input parameter executed this time, and identifies the parameter that is the cause of the abnormality.
FIG. 19 is a flowchart showing an example of the cause parameter acquisition process in step 214 of FIG.
In step 302 of FIG. 19, the execution result learning processing unit 66 initializes the variable p to 0, and in step 304, increments the variable p by 1.

  In step 306, the execution result learning processing unit 66 acquires the value vp of the parameter identified by the variable p and the value vi identified by the variable p of the state i from the normal parameter management table 402. In step 308, the execution result learning processing unit 66 determines whether or not the parameter value vp is an abnormal value on the normal parameter management table 402. For example, it is assumed that the parameter value vp = CPU performance value = 4 GHz and the value vi = 2.5 GHz. Parameter value vp = CPU performance value = 4 GHz> value vi = 2.5 GHz, and the value vp is considered to be the cause of the abnormality. Therefore, in step 310, the execution result learning processing unit 66 stores the parameter value vp = CPU performance value (= 4 GHz) in the memory 36 as a parameter causing the abnormality.

  In step 216, the execution result learning processing unit 66 stores only the different part in the abnormal parameter management table 403 (FIG. 4C). That is, only when the parameter causing the abnormality stored in the memory 36 is not stored in the parameter management table 403 during abnormality, the parameter causing the abnormality is stored (added) in the parameter management table 403 during abnormality. Thereafter, when the parameter transmitted together with the VM creation command includes a parameter for the cause of the abnormality, the parameter for the cause of the abnormality is stored in the parameter management table 403 for the abnormality. Diagnosis is abnormal. Therefore, the accuracy of subsequent prior diagnosis can be improved.

In step 218, the weighting for the same abnormal pattern is updated.
Here, the weighting is a value in parentheses attached to each value in the abnormal parameter management table 403. Specifically, this is the number of times the parameter value has become abnormal in the past. Corresponding to the CPU in the state A, it is 4 GHz (1), which indicates that the CPU performance value has become abnormal once at 4 GHz.

In step 220, the execution result learning processing unit 66 confirms the weighted state, and deletes the abnormal pattern having the abnormality occurrence rate less than the threshold from the abnormal parameter management table 403. Thereby, the memory capacity of the secondary storage device 40 can be effectively utilized.

  Here, the abnormality occurrence rate can be a percentage of the total value of abnormality in the current parameter with respect to the number of occurrences of abnormality for each parameter for each element that defines the configuration of the VM in each state. For example, if the current abnormality is the CPU performance value in state A = 4 GHz, the number of abnormality caused by the CPU value in state A is 1 + 2 = 3, and the current CPU value is The number of causes of abnormality is 1. Therefore, the abnormality occurrence rate is 33%. If the threshold is 1 percent, it is not determined that the threshold is less than the threshold in the above example. Therefore, the CPU performance value = 4 GHz in the state A of the current abnormality is not deleted.

  In step 222, the execution result learning processing unit 66 updates the contents of the interrelation table (abnormal system) 407 based on the parameter relationship table (abnormal system) 406.

  The specific contents of the process of step 222 are almost the same as the update process shown in FIG. 17, and are different in the following points. That is, the step 272 in the update process in FIG. 17 uses the correlation table (normal system) 404, whereas the step 222 uses the correlation table (abnormal system) 406. Further, in step 280 in the update process in FIG. 17, the parameter relationship table (normal system) 405 is used, whereas in step 222, the parameter relationship table (abnormal system) 407 is used.

  20A and 20C show how the parameter relationship table (abnormal system) 407 is updated in step 222. FIG. For example, when the mutual relationship identified by the variable r is CPU <CPU pool, it is determined in the parameter relationship table (abnormal system) 407 whether “None” is associated with CPU <CPU pool. In the example illustrated in FIG. 20A, “None” is stored in the parameter relationship table (abnormal system) 407 corresponding to CPU <CPU pool. Therefore, as shown in FIG. 20C, CPU <CPU pool is changed to “Yes” corresponding to the CPU pool.

  In step 224, the execution result learning processing unit 66 determines whether or not communication information has been added to the parameter relationship table (abnormal system) 407. If the determination result of step 224 is negative, the execution result process and the diagnostic learning process are finished.

  As shown in FIG. 20C, when the CPU <CPU pool is changed to “Yes” corresponding to the CPU pool, the determination result in step 224 is affirmative. In this case, in step 226, the execution result learning processing unit 66 determines “Yes” for the added correlation in the parameter relationship table (normal system) 405 via the link from the correlation table (normal system) 404. It is determined whether or not. In the inter-parameter relationship table (normal system) 405, when it is determined that the added correlation is “Yes”, in step 228, the execution result learning processing unit 66 determines that the added correlation is “ None ”.

  Further, in step 228, the execution result learning processing unit 66 adds a mutual relationship corresponding to the mutual relationship check list 408 as shown in FIG. The mutual relationship that could not be created this time is an item of abnormal correlation. Therefore, the execution result learning processing unit 66 adds the correlation to the correlation check list 408 so that it is determined as abnormal when the correlation occurs in the subsequent pre-diagnosis processing. It is. When the process of step 228 is completed, the diagnosis learning process is also ended.

Next, the effect of this embodiment will be described.
(First effect)
In the present embodiment, the input parameter is stored in the abnormal parameter management table 403, and even if it is diagnosed by the prior diagnosis that the parameter has an abnormal value, if the VM can be created, the parameter is abnormal. It is deleted from the parameter management table 403. Therefore, when a parameter including the deleted parameter is input after the next time, the parameter has already been deleted from the abnormal parameter management table 403. It is not diagnosed to exist. Therefore, this embodiment has an effect that the accuracy of the pre-diagnosis can be further improved.

  In the present embodiment, the input parameter is not stored in the normal parameter management table 402, and a VM may be created even when the prior diagnosis diagnoses that the parameter is an abnormal value. . In this case, the normal parameter management table 402 is updated so that the normal range is expanded to the parameter. Therefore, when a parameter including the added parameter is input after the next time, the parameter has already been added to the normal parameter management table 402. It is not diagnosed to exist. Therefore, this embodiment has an effect that the accuracy of the pre-diagnosis can be further improved.

  Further, since the input parameter is not stored in the abnormal parameter management table 403, even if the parameter has not been previously diagnosed as an abnormal value, if a VM is not created, the abnormal parameter management table 403 Add the parameter. Therefore, when the input parameter includes a parameter added to the abnormal parameter management table 403 after the next time, the parameter is preliminarily diagnosed as an abnormal value. Therefore, this embodiment has an effect that the accuracy of the pre-diagnosis can be further improved.

  Further, in the embodiment, the mutual relationship between the amount that requests the calculation resource and the amount that can supply the calculation resource when the VM is not created is stored in the correlation check list 408. Even if it is diagnosed in the prior diagnosis that a mutual relationship that the VM cannot be created is established from the input parameters, if the VM can be created, the mutual relationship is deleted from the mutual check list 408. Therefore, even after the next time, even if the deleted correlation is established from the parameter, the correlation is already deleted in the correlation check list 408. Therefore, in the pre-diagnosis, the VM is created from the input parameter. It is not diagnosed that the mutual relationship that it is impossible is established. Therefore, this embodiment has an effect that the accuracy of the pre-diagnosis can be further improved.

  Furthermore, in the embodiment, even if it is diagnosed that the VM cannot be created based on the input parameters in the pre-diagnosis, if the VM cannot be created, the correlation is added to the correlation checklist 408. Added. Therefore, when the correlation deleted from the parameter is established after the next time, the correlation is already added to the correlation check list 408. Therefore, the VM cannot be created from the input parameter in the prior diagnosis. It is diagnosed that the mutual relationship is established. Therefore, this embodiment has an effect that the accuracy of the pre-diagnosis can be further improved.

(Second effect)
In the present embodiment, even if a parameter is stored in the abnormal parameter management table 403, if the number of occurrences (occurrence rate) of VMs in that parameter is less than the threshold, the parameter is stored in the abnormal parameter management table 403. It is deleted from 403. Therefore, this embodiment has an effect that the memory capacity can be effectively used.

(Third effect)
In this embodiment, since a pre-diagnosis is performed based on the input parameters and the contents of each table, the user knows the prediction result of whether a VM is created or not based on the parameters specified by the user. be able to. Therefore, the present embodiment has an effect that it is possible to provide information that allows a general user who is not an expert to recognize where the cause of the abnormality occurred in the parameters input by the user.

Next, a modification of this embodiment will be described.
(First modification)
In the present embodiment, since the input parameter is not stored in the abnormal parameter management table 403, even if the VM is not created even if the pre-diagnosis does not diagnose the parameter as an abnormal value, The following processing can be executed. When the maximum value of the CPU in the input parameters is 3 GHz and the normal parameter management table 402 stores 4 GHz as the maximum value of the CPU, if the VM is not created, the present embodiment is as follows. Can be executed. That is, in the present embodiment, the maximum value of the CPU in the normal parameter management table 402 can be limited to a value smaller than 3 GHz by a predetermined value (for example, 0.1 GHz). Therefore, after the next time, when the maximum value of the CPU in the input parameter is 3 GHz, it is diagnosed that the parameter is an abnormal value in the preliminary diagnosis. Therefore, the first modification has an effect that the accuracy of the prior diagnosis can be further improved.

(Second modification)
In the present embodiment, as the correlation check list 408, correlations recognized as having an abnormality are listed. The correlation check list 408 is referred to as a correlation check list (abnormal system) 408. Therefore, the technology of the present disclosure has an effect that the accuracy of the pre-diagnosis can be further improved.

  All documents, patent applications and technical standards mentioned in this specification are to the same extent as if each individual document, patent application and technical standard were specifically and individually stated to be incorporated by reference. Incorporated by reference in the book.

Regarding the above embodiment, the following additional notes are disclosed.
(Appendix 1)
A receiving unit for receiving a specified value for specifying the configuration of the virtual machine;
A storage unit that stores at least one specified value specifying the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value is configured;
Based on the received specified value, the stored content stored in the storage unit, and the actual result of whether or not a virtual machine according to the received specified value can be configured, the received specified value and A determination unit for determining whether or not there is a contradiction that does not cause the actual result from the stored content;
When it is determined that the contradiction has occurred, a change unit that changes the stored content so that the contradiction does not occur;
A storage unit update device.

(Appendix 2)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the virtual machine according to the received specified value cannot be configured by the determining unit because the received specified value is not included in the plurality of specified values, the received specified value is actually changed to the received specified value. If it is determined that there is a contradiction that the virtual machine that you followed has been configured,
The storage unit update device according to claim 1, wherein the change unit changes the storage content of the storage unit so that the received specified value is added to the plurality of specified values.

(Appendix 3)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the determination unit can configure the virtual machine according to the received specified value by including the received specified value in the plurality of second specified values, the received specified value is actually If it is determined that there is a conflict that the virtual machine according to the value cannot be configured,
The storage unit update device according to claim 1, wherein the changing unit changes the storage content of the storage unit such that a specified value having the same value as the received specified value is deleted from the plurality of specified values.

(Appendix 4)
The storage unit stores at least one specified value that specifies a configuration of a virtual machine that was not actually configured,
Since the received specified value matches the stored specified value by the determination unit, a virtual machine according to the received specified value cannot be configured, but in reality the received specified value is changed to the received specified value. If it is determined that there is a contradiction that the virtual machine that you followed has been configured,
The storage unit update device according to claim 1, wherein the changing unit changes the storage content of the storage unit such that the stored specified value that matches the received specified value is deleted.

(Appendix 5)
The storage unit stores a plurality of different designated values,
In correspondence with each of the plurality of designated values, a counting unit that counts the number of times a designated value that matches the designated value is received;
The change unit, when there is an occurrence rate that is less than or equal to a predetermined value among the occurrence rates of the plurality of times counted corresponding to each of the plurality of designated values, designation corresponding to the occurrence rate that is less than or equal to the predetermined value The storage unit update device according to attachment 4, wherein the storage content of the storage unit is changed so that a value is deleted.

(Appendix 6)
A receiving unit for receiving a specified value for specifying the configuration of the virtual machine;
A plurality of different first designated values that are actually configured by the virtual machine are stored so that it is recognized that a virtual machine according to the first designated value is configured, and the virtual machine is A storage unit that stores at least one second specified value that has not been configured in order to recognize that a virtual machine according to the second specified value has not been configured;
Based on the received specified value, the stored content stored in the storage unit, and the actual result of whether or not a virtual machine according to the received specified value can be configured, the received specified value and A determination unit for determining whether or not there is a contradiction that does not cause the actual result from the stored content;
When it is determined that the contradiction has occurred, a change unit that changes the stored content so that the contradiction does not occur;
A storage unit update device.

(Appendix 7)
Since the received specified value matches the second specified value by the determination unit, a virtual machine according to the first specified value cannot be configured, but the received specified value is actually set to the received specified value. If it is determined that there is a contradiction that the virtual machine that you followed has been configured,
The changing unit is configured to add the received specified value to the plurality of first specified values and delete the second value that matches the received specified value. The storage update device according to appendix 6, wherein the storage content is changed.

(Appendix 8)
Since the received specified value matches the first specified value by the determination unit, a virtual machine according to the first specified value can be configured, but in reality the received specified value is set to the received specified value. If it is determined that there is a discrepancy that the virtual machine you followed could not be configured,
The change unit stores the storage unit so that the received specified value is deleted from the plurality of first specified values and the received specified value is added as the second specified value. The storage unit update device according to appendix 7, wherein the content is changed.

(Appendix 9)
The storage unit stores a plurality of different second designated values,
A counting unit that counts the number of times a designated value that matches the second designated value is received in correspondence with each of the plurality of second designated values;
The changing unit may reduce the occurrence rate below the predetermined value when the occurrence rate is equal to or less than a predetermined value among the occurrence rates of the plurality of times counted corresponding to each of the plurality of second designated values. The storage unit update device according to appendix 8, wherein the storage content of the storage unit is changed so that the corresponding second designated value is deleted.

(Appendix 10)
A receiving unit for specifying a configuration of the virtual machine and receiving a specified value for specifying an amount of a computing resource to be supplied;
Whether the virtual machine according to the specified value is related to the relationship between at least one specified value that specifies the configuration of the virtual machine and specifies the amount of computing resources to be supplied and the amount that can be supplied A storage unit for storing so that
Based on the received specified value, the stored content stored in the storage unit, and the actual result of whether or not a virtual machine according to the received specified value can be configured, the received specified value and A determination unit for determining whether or not there is a contradiction that does not cause the actual result from the stored content;
When it is determined that the contradiction has occurred, a change unit that changes the stored content so that the contradiction does not occur;
A storage unit update device.

(Appendix 11)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
Since the relationship is established based on the received specified value, the determination unit determines that the virtual machine can actually be configured even though the virtual machine cannot be configured according to the stored specified value. If
The storage unit update device according to claim 10, wherein the change unit changes the content stored in the storage unit so that the relationship is deleted.

(Appendix 12)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
When the determination unit determines that the virtual machine could not be configured, although the virtual machine can be configured because the relationship is not established based on the received specified value,
The storage unit update device according to appendix 10, wherein the change unit changes the content stored in the storage unit so that a relationship between the received specified value and the supply amount of the calculation resource is added. .

(Appendix 13)
On the computer,
In order to be able to recognize whether or not the virtual machine according to the second designated value is configured with the designated value that designates the received virtual machine configuration and at least one designated value that designates the virtual machine configuration. Based on the stored content stored in the storage unit for storing and the actual result of whether or not the virtual machine according to the received specified value can be configured, from the received specified value and the stored content, Determine if there is a conflict that does not produce real results,
When it is determined that the contradiction has occurred, a storage unit update program that executes processing including changing the stored content so that the contradiction does not occur.

(Appendix 14)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received designated value is not included in the plurality of designated values, a virtual machine according to the received designated value cannot be configured. If it ’s determined that there was a conflict,
The storage unit update program according to appendix 13, wherein the computer changes the storage content of the storage unit such that the received specified value is added to the plurality of specified values.

(Appendix 15)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received specified value is included in the plurality of specified values, a virtual machine according to the received specified value can be configured, but in reality, the virtual machine according to the received specified value is If it is determined that there is a conflict that cannot be configured,
In the change, the computer changes the storage content of the storage unit so that a specified value having the same value as the received specified value is deleted from the plurality of specified values. program.

(Appendix 16)
The storage unit stores at least one specified value that specifies a configuration of a virtual machine that was not actually configured,
Since the received specified value matches the stored specified value, a virtual machine according to the received specified value cannot be configured, but in reality, a virtual machine according to the received specified value cannot be configured. If it ’s determined that there was a conflict,
The storage unit update program according to claim 13, wherein in the change, the computer changes the storage content of the storage unit such that the stored specified value that matches the received specified value is deleted.

(Appendix 17)
The storage unit stores a plurality of different designated values,
The processing is as follows:
In correspondence with each of the plurality of designated values, the number of times a designated value that matches the designated value is received,
If there is an occurrence rate that is less than or equal to a predetermined value among the counted occurrences corresponding to each of the plurality of specified values, the specified value that corresponds to the occurrence rate that is less than or equal to the predetermined value is deleted. The storage unit update program according to supplementary note 16, including changing the storage content of the storage unit as described above.

(Appendix 18)
On the computer,
Recognizing that the virtual machine according to the first designated value is configured based on the received designated value for specifying the configuration of the virtual machine and a plurality of different first designated values for which the virtual machine is actually configured. And storing at least one second specified value for which the virtual machine was not actually configured, so that it is recognized that a virtual machine according to the second specified value was not configured. From the received specified value and the stored content, based on the stored content stored in the storage unit for storing and the actual result of whether or not the virtual machine according to the received specified value could be configured Determines whether there is a contradiction that does not produce the actual result,
When it is determined that the contradiction has occurred, a storage unit update program that executes processing including changing the stored content so that the contradiction does not occur.

(Appendix 19)
Since the received specified value matches the second specified value, a virtual machine according to the received specified value cannot be configured, but in reality, the virtual machine according to the received specified value is If it ’s determined that there was a conflict,
In the modification, the computer adds the received specified value to the plurality of first specified values and deletes the second value that matches the received specified value. The storage unit update program according to appendix 18, which changes the storage content of the storage unit.

(Appendix 20)
Since the received specified value matches the first specified value by the determination unit, a virtual machine according to the received specified value can be configured, but in reality, the received specified value is changed to the received specified value. If it is determined that there is a discrepancy that the virtual machine you followed could not be configured,
In the change, the computer stores the memory so that the received specified value is deleted from the plurality of first specified values and the received specified value is added as the second specified value. The storage unit update program according to attachment 19, wherein the storage content of the unit is changed.

(Appendix 21)
The storage unit stores a plurality of different second designated values,
The processing is as follows:
Corresponding to each of the plurality of second designated values, count the number of times a designated value that matches the second designated value is received,
If there is an occurrence rate that is less than or equal to a predetermined value among the occurrence rates of the plurality of times counted corresponding to each of the plurality of second designated values, the second corresponding to the occurrence rate that is less than or equal to the predetermined value The storage unit update program according to supplementary note 20, including changing the storage content of the storage unit so that the specified value is deleted.

(Appendix 22)
On the computer,
A specified value that specifies the configuration of the received virtual machine and specifies the amount of computing resources that are requested to supply, and at least one specified value that specifies the configuration of the virtual machine and specifies the amount of computing resources that are requested to be supplied And the stored contents stored in the storage unit for storing the relationship between the supply amount of computing resources and the amount that can be supplied, so as to recognize whether or not the virtual machine according to the specified value is configured, and the received specification Based on the actual result of whether or not the virtual machine according to the value can be configured, it is determined whether or not there is a contradiction that does not cause the actual result from the received specified value and the stored content,
When it is determined that the contradiction has occurred, a storage unit update program that executes processing including changing the stored content so that the contradiction does not occur.

(Appendix 23)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
Since the relationship is established based on the received specified value, a virtual machine according to the stored specified value cannot be configured, but when it is determined that the virtual machine can actually be configured,
The storage unit update program according to attachment 22, wherein, in the change, the computer changes the content stored in the storage unit so that the relationship is deleted.

(Appendix 24)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
Since it is determined that the virtual machine could not be configured in reality, although the virtual machine can be configured because the relationship is not established based on the received specified value before,
In the change, the computer changes the content stored in the storage unit so as to add a relationship between the received specified value and the supplyable amount of the calculation resource. Department update program.

(Appendix 25)
On the computer,
A storage that stores a specified value that specifies the configuration of the received virtual machine and at least one specified value that specifies the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value has been configured. Based on the stored content stored in the storage unit and the actual result indicating whether or not the virtual machine according to the received specified value can be configured, the actual result is determined from the received specified value and the stored content. To determine if there is a conflict that does not occur
When it is determined that the contradiction has occurred, a storage unit updating method for executing processing including changing the stored content so that the contradiction does not occur.

(Appendix 26)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received designated value is not included in the plurality of second designated values, a virtual machine according to the received designated value cannot be configured, but in reality, the received designated value is followed. If it is determined that there is a conflict that the virtual machine has been configured,
26. The storage unit updating method according to claim 25, wherein in the change, the computer changes the storage content of the storage unit so that the received specified value is added to the plurality of specified values.

(Appendix 27)
The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received specified value is included in the plurality of specified values, a virtual machine according to the received specified value can be configured, but in reality, a virtual machine according to the received specified value is configured. If it is determined that there is a contradiction that is not possible,
In the change, the computer changes the storage content of the storage unit so that a specified value having the same value as the received specified value is deleted from the plurality of specified values. Method.

(Appendix 28)
The storage unit stores at least one specified value that specifies a configuration of a virtual machine that was not actually configured,
Since the received designated value matches the stored designated value, a virtual machine according to the received designated value cannot be configured, but in reality, the virtual machine according to the received designated value is used. If it is determined that there is a conflict that
26. The storage unit updating method according to claim 25, wherein, in the change, the computer changes the storage content of the storage unit so that the stored specified value that matches the received specified value is deleted.

(Appendix 29)
The storage unit stores a plurality of different designated values,
The processing is as follows:
In correspondence with each of the plurality of designated values, the number of times a designated value that matches the designated value is received,
If there is an occurrence rate that is less than or equal to a predetermined value among the counted occurrences corresponding to each of the plurality of specified values, the specified value that corresponds to the occurrence rate that is less than or equal to the predetermined value is deleted. The storage unit update method according to supplementary note 28, including changing the storage content of the storage unit as described above.

(Appendix 30)
On the computer,
Recognizing that the virtual machine according to the first designated value is configured based on the received designated value for specifying the configuration of the virtual machine and a plurality of different first designated values for which the virtual machine is actually configured. And storing at least one second specified value for which the virtual machine was not actually configured, so that it is recognized that a virtual machine according to the second specified value was not configured. From the received specified value and the stored content, based on the stored content stored in the storage unit for storing and the actual result of whether or not the virtual machine according to the received specified value could be configured Determines whether there is a contradiction that does not produce the actual result,
When it is determined that the contradiction has occurred, a storage unit updating method for executing processing including changing the stored content so that the contradiction does not occur.

(Appendix 31)
Since the received specified value matches the second specified value, a virtual machine according to the received specified value cannot be configured, but in reality, the virtual machine according to the received specified value is If it ’s determined that there was a conflict,
In the modification, the computer adds the received specified value to the plurality of first specified values and deletes the second value that matches the received specified value. The storage unit update method according to attachment 30, wherein the storage content of the storage unit is changed.

(Appendix 32)
Since the received specified value matches the first specified value by the determination unit, a virtual machine according to the received specified value can be configured, but in reality, the received specified value is changed to the received specified value. If it is determined that there is a discrepancy that the virtual machine you followed could not be configured,
In the change, the computer stores the memory so that the received specified value is deleted from the plurality of first specified values and the received specified value is added as the second specified value. The storage unit updating method according to attachment 31, wherein the storage content of the unit is changed.

(Appendix 33)
The storage unit stores a plurality of different second designated values,
The processing is as follows:
Corresponding to each of the plurality of second designated values, count the number of times a designated value that matches the second designated value is received,
If there is an occurrence rate that is less than or equal to a predetermined value among the occurrence rates of the plurality of times counted corresponding to each of the plurality of second designated values, the second corresponding to the occurrence rate that is less than or equal to the predetermined value The storage unit update method according to appendix 32, comprising changing the storage content of the storage unit so that the specified value is deleted.

(Appendix 34)
On the computer,
A specified value that specifies the configuration of the received virtual machine and specifies the amount of computing resources that are requested to supply, and at least one specified value that specifies the configuration of the virtual machine and specifies the amount of computing resources that are requested to be supplied And the stored contents stored in the storage unit for storing the relationship between the supply amount of computing resources and the amount that can be supplied, so as to recognize whether or not the virtual machine according to the specified value is configured, and the received specification Based on the actual result of whether or not the virtual machine according to the value can be configured, it is determined whether or not there is a contradiction that does not cause the actual result from the received specified value and the stored content,
When it is determined that the contradiction has occurred, a storage unit updating method for executing processing including changing the stored content so that the contradiction does not occur.

(Appendix 35)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
Since the relationship is established based on the received specified value, a virtual machine according to the stored specified value cannot be configured, but when it is determined that the virtual machine can actually be configured,
35. The storage unit updating method according to claim 34, wherein in the change, the computer changes the content stored in the storage unit so that the relationship is deleted.

(Appendix 36)
In the storage unit, the relationship is stored so that it is recognized that a virtual machine according to the stored specified value is not configured,
When it is determined that the virtual machine could not be configured, although the virtual machine could be configured because the relationship was not established based on the received specified value,
In the change, the computer changes the content stored in the storage unit so as to add a relationship between the received specified value and the supplyable amount of the calculation resource. Department update method.

(Appendix 37)
A storage medium for storing a storage unit update program for causing a computer to execute predetermined processing,
The predetermined reason is
A storage that stores a specified value that specifies the configuration of the received virtual machine and at least one specified value that specifies the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value has been configured. Based on the stored content stored in the storage unit and the actual result indicating whether or not the virtual machine according to the received specified value can be configured, the actual result is determined from the received specified value and the stored content. To determine if there is a conflict that does not occur
When it is determined that the contradiction has occurred, the storage medium includes changing the storage content so that the contradiction does not occur.

12 diagnostic device 32 CPU
52 Communication control unit
66 execution result learning processing unit

Claims (7)

A receiving unit for receiving a specified value for specifying the configuration of the virtual machine;
A storage unit that stores at least one specified value specifying the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value is configured;
Based on the received specified value, the stored content stored in the storage unit, and the actual result of whether or not a virtual machine according to the received specified value can be configured, the received specified value and A determination unit for determining whether or not there is a contradiction that does not cause the actual result from the stored content;
When it is determined that the contradiction has occurred, a change unit that changes the stored content so that the contradiction does not occur;
A storage unit update device. On the computer,
A storage that stores a specified value that specifies the configuration of the received virtual machine and at least one specified value that specifies the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value has been configured. Based on the stored content stored in the storage unit and the actual result indicating whether or not the virtual machine according to the received specified value can be configured, the actual result is determined from the received specified value and the stored content. To determine if there is a conflict that does not occur
When it is determined that the contradiction has occurred, a storage unit update program that executes processing including changing the stored content so that the contradiction does not occur. The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received designated value is not included in the plurality of designated values, a virtual machine according to the received designated value cannot be configured. If it ’s determined that there was a conflict,
The storage unit update program according to claim 2, wherein in the change, the computer changes the storage content of the storage unit so that the received specified value is added to the plurality of specified values. The storage unit stores a plurality of different specified values that specify the configuration of a virtual machine configured in reality,
Although the received specified value is included in the plurality of specified values, a virtual machine according to the received specified value can be configured, but in reality, a virtual machine according to the received specified value is configured. If it is determined that there is a contradiction that is not possible,
3. The storage unit according to claim 2, wherein in the change, the computer changes the storage content of the storage unit such that a specified value having the same value as the received specified value is deleted from the plurality of specified values. Update program. The storage unit stores at least one specified value that specifies a configuration of a virtual machine that was not actually configured,
Since the received specified value matches the stored specified value, a virtual machine according to the received specified value cannot be configured, but in reality, a virtual machine according to the received specified value cannot be configured. If it ’s determined that there was a conflict,
The storage unit update program according to claim 2, wherein in the change, the computer changes the storage content of the storage unit such that the stored specified value that matches the received specified value is deleted. The storage unit stores a plurality of different designated values,
The processing is as follows:
In correspondence with each of the plurality of designated values, the number of times a designated value that matches the designated value is received,
If there is an occurrence rate that is less than or equal to a predetermined value among the counted occurrences corresponding to each of the plurality of specified values, the specified value that corresponds to the occurrence rate that is less than or equal to the predetermined value is deleted. The storage unit update program according to claim 16, comprising changing the storage content of the storage unit as described above. On the computer,
A storage that stores a specified value that specifies the configuration of the received virtual machine and at least one specified value that specifies the configuration of the virtual machine so that it can be recognized whether or not the virtual machine according to the specified value has been configured. Based on the stored content stored in the storage unit and the actual result indicating whether or not the virtual machine according to the received specified value can be configured, the actual result is determined from the received specified value and the stored content. To determine if there is a conflict that does not occur
When it is determined that the contradiction has occurred, the storage unit updating method for executing processing including changing the stored content so that the contradiction does not occur

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