JP2019144785A - Monitoring program, monitoring apparatus and monitoring method - Google Patents

Abstract

To provide a monitoring program, a monitoring apparatus, and a monitoring method for identifying influence caused by an abnormality occurring in a monitoring target.SOLUTION: A monitoring program arranges a monitoring virtual machine used to monitor a plurality of monitoring targets including a virtualization software on the virtualization software; gets the results of a given test executed by the monitoring virtual machine at a given interval; determines whether there is an abnormality in the monitoring virtual machine from the acquired test results; obtains the predetermined status of the plurality of monitoring targets and outputs a determination result of whether there is the abnormality in the monitoring virtual machine and the predetermined state of the plurality of monitoring targets if the monitoring virtual machine is abnormal.SELECTED DRAWING: Figure 5

Description

  The present invention relates to a monitoring program, a monitoring apparatus, and a monitoring method.

  For example, a business provider (hereinafter also referred to as a service business) that provides a service to a user constructs a business system (hereinafter also referred to as an information processing system) in order to provide the service. Specifically, a service provider, for example, borrows a resource such as a virtual machine (hereinafter simply referred to as a virtual machine) from a provider that provides a cloud computing service (hereinafter also referred to as a cloud provider) and provides the service. Build a business system that realizes

  In this case, the cloud provider monitors a hypervisor or the like (hereinafter also simply referred to as a monitoring target) that operates a virtual machine lent to the service provider. Thereby, the cloud operator can prevent the virtual machine from being affected by, for example, an abnormality (failure) occurring in the monitoring target (see, for example, Patent Documents 1 and 2).

International Publication No. 2017/134758 International Publication No. 2013/190649

  Here, in general, a cloud operator as described above cannot freely access a virtual machine lent to a service operator, and information regarding the virtual machine (for example, the operating state of the virtual machine). Information) cannot be obtained.

  Therefore, for example, even when a cloud operator detects an abnormality that has occurred in the monitoring target, it cannot identify the effect of the abnormality on the virtual machine. In addition, for example, when a cloud operator cannot detect an abnormality that has occurred in a monitoring target, it cannot detect the abnormality even if the abnormality affects the virtual machine.

  In view of this, an object of one aspect of the present invention is to provide a monitoring program, a monitoring apparatus, and a monitoring method for identifying an influence caused by an abnormality that occurs in a monitoring target.

  In one aspect of the embodiment, a virtual machine for monitoring used for monitoring a plurality of monitoring targets including the virtualization software is arranged on the virtualization software, and the predetermined virtual machine executed by the virtual machine at a predetermined interval Obtain a test result, determine whether or not the virtual machine is abnormal from the acquired result, and if the virtual machine is abnormal, acquire a predetermined state of the plurality of monitoring targets, and determine whether or not the virtual machine is abnormal And a process for outputting the determination result and the predetermined states of the plurality of monitoring targets.

  According to one aspect, it is possible to identify an influence caused by an abnormality occurring in a monitoring target.

FIG. 1 is a diagram illustrating a configuration of the information processing system 10. FIG. 2 is a diagram illustrating a hardware configuration of the monitoring device 1. FIG. 3 is a block diagram of functions of the monitoring device 1. FIG. 4 is a flowchart for explaining an overview of the monitoring process according to the first embodiment. FIG. 5 is a flowchart for explaining an overview of the monitoring process according to the first embodiment. FIG. 6 is a diagram for explaining the outline of the monitoring process in the first embodiment. FIG. 7 is a diagram for explaining the outline of the monitoring process in the first embodiment. FIG. 8 is a diagram for explaining the outline of the monitoring process in the first embodiment. FIG. 9 is a flowchart for explaining the details of the monitoring process in the first embodiment. FIG. 10 is a flowchart for explaining the details of the monitoring process in the first embodiment. FIG. 11 is a flowchart for explaining the details of the monitoring process in the first embodiment. FIG. 12 is a flowchart for explaining the details of the monitoring process in the first embodiment. FIG. 13 is a diagram for describing a specific example of the correspondence information 132. FIG. 14 is a diagram for describing a specific example of the test result information 131 and the state information 133. FIG. 15 is a diagram for describing a specific example of the test result information 131 and the state information 133. FIG. 16 is a diagram for describing a specific example of the correspondence information 132. FIG. 17 is a diagram for describing a specific example of the test result information 131 and the state information 133. FIG. 18 is a diagram for describing a specific example of the test result information 131 and the state information 133. FIG. 19 is a diagram illustrating a specific example of the correspondence information 132. FIG. 20 is a diagram for describing a specific example of the test result information 131 and the state information 133. FIG. 21 is a diagram for describing a specific example of the notification information 134. FIG. 22 is a flowchart for explaining monitoring processing in the second embodiment. FIG. 23 is a flowchart for explaining monitoring processing according to the second embodiment. FIG. 24 is a flowchart for explaining monitoring processing according to the second embodiment. FIG. 25 is a flowchart for explaining monitoring processing according to the second embodiment. FIG. 26 is a diagram illustrating a specific example of the correspondence information 132 in the second embodiment. FIG. 27 is a diagram illustrating specific examples of the API result information 135 and the state information 133 in the second embodiment. FIG. 28 is a diagram illustrating a specific example of the API result information 135 and the state information 133 in the second embodiment. FIG. 29 is a diagram illustrating the notification information 134 according to the second embodiment.

[Configuration of information processing system]
FIG. 1 is a diagram illustrating a configuration of the information processing system 10. An information processing system 10 illustrated in FIG. 1 includes, for example, a monitoring device 1, a supervisor terminal 1a, a physical machine 2, a storage device 3, an API server 4, and a network device 5.

  The monitoring device 1 and the physical machine 2 are each composed of, for example, one or more physical machines. Each physical machine has physical resources such as a CPU (Central Computing Unit), a memory (DRAM: Dynamic Random Access Memory), and a hard disk (HDD: Hard Disk Drive).

  The hypervisor 2c (hereinafter also referred to as virtualization software 2c) operating on the physical machine 2 generates one or more virtual machines by allocating physical resources of the physical machine 2 and the storage device 3. Specifically, in this case, the hypervisor 2c generates a virtual machine (hereinafter also referred to as a user VM 2a) that is lent to the service provider.

  For example, when the service provider inputs to the user terminal (not shown) that a new user VM 2a is generated or a generated user VM 2a is deleted, the API server 4 The controller (not shown) that manages physical resources such as 2 is instructed to generate a new user VM 2a, delete a generated user VM 2a, or the like. In this case, the controller instructs the hypervisor 2c to generate a new user VM 2a, delete the generated user VM 2a, or the like.

  The network device 5 is, for example, a physical switch that connects devices such as the monitoring device 1 and the physical machine 2.

  The monitoring device 1 monitors, for example, the hypervisor 2c, the storage device 3, the API server 4, and the network device 5 that operate in the physical machine 2. Then, the cloud operator browses the monitoring result by the monitoring device 1 via the monitor terminal 1a.

  This prevents the cloud operator from affecting the operating state of the user VM 2a, which is a resource lent to the service provider, due to, for example, an abnormality occurring in the monitoring target such as the hypervisor 2c or the storage device 3. It becomes possible to do.

  Here, the monitoring device 1 as described above generally cannot freely access the user VM 2a lent to the service provider, and information on the user VM 2a (for example, the user VM 2a's) Information indicating the operating state) cannot be acquired.

  Therefore, for example, even when the cloud operator detects an abnormality that has occurred in the hypervisor 2c, the cloud operator cannot identify the effect of the abnormality on the user VM 2a. In addition, for example, when the cloud operator cannot detect an abnormality that has occurred in the hypervisor 2c, it cannot detect this abnormality even if the abnormality affects the user VM 2a.

  Therefore, the monitoring device 1 according to the present embodiment arranges a monitoring virtual machine (hereinafter also referred to as a monitoring VM) used for monitoring a plurality of monitoring targets including the hypervisor 2c on the hypervisor 2c.

  Then, the monitoring device 1 acquires a result of a predetermined test executed by the monitoring VM 2c at a predetermined interval, and determines whether there is an abnormality in the monitoring VM 2c from the acquired result. As a result, when it is determined that the monitoring VM 2c is abnormal, the monitoring apparatus 1 acquires a predetermined state of the plurality of monitoring targets, the determination result of whether or not the monitoring VM 2c is abnormal, and a plurality of monitoring target predetermined states. Status.

  That is, the monitoring device 1 according to the present embodiment is a virtual machine on which the monitoring device 1 can acquire information on the hypervisor 2c on which the user VM 2a on which the monitoring device 1 cannot acquire information operates, for example. The monitoring VM is arranged. Then, the monitoring device 1 estimates the operation state acquired from the monitoring VM as the current operation state of the user VM 2a.

  Thus, for example, when the monitoring apparatus 1 detects an abnormality that has occurred in the hypervisor 2c, the monitoring apparatus 1 refers to the operating state acquired from the monitoring VM, thereby determining the degree of influence that the generated abnormality has on the user VM 2a. It becomes possible to estimate. The monitoring device 1 can also detect an abnormality (abnormality caused by the hypervisor 2c) that cannot be detected by the hypervisor 2c, for example, by referring to the operation state acquired from the monitoring VM. .

[Hardware configuration of information processing system]
Next, the hardware configuration of the information processing system 10 will be described. FIG. 2 is a diagram illustrating a hardware configuration of the monitoring device 1.

  As illustrated in FIG. 2, the monitoring device 1 includes a CPU 101 that is a processor, a memory 102, an external interface (hereinafter also referred to as an I / O unit) 103, and a storage medium 104. Each unit is connected to each other via a bus 105.

  The storage medium 104 stores, for example, a program 110 for performing processing for monitoring a monitoring target (hereinafter also referred to as monitoring processing) in a program storage area (not shown) in the storage medium 104. The storage medium 104 may be an HDD, for example.

  In addition, the storage medium 104 includes, for example, a storage unit 130 (hereinafter also referred to as an information storage area 130) that stores information used when performing monitoring processing.

  The CPU 101 performs a monitoring process by executing the program 110 loaded from the storage medium 104 to the memory 102.

  The external interface 103 communicates with the physical machine 2, the storage device 3, the API server 4, and the network device 5 via a network (not shown), for example.

[Monitoring device functions]
Next, functions of the monitoring device 1 will be described. FIG. 3 is a block diagram of functions of the monitoring device 1.

  As shown in FIG. 3, the monitoring apparatus 1 has a virtual machine placement unit 111, a test result acquisition unit 112, and presence / absence of abnormality by organically cooperating hardware such as the CPU 101 and the memory 102 and the program 110. Various functions including the determination unit 113, the state acquisition unit 114, the execution instruction unit 115, and the result output unit 116 are realized.

  Further, as illustrated in FIG. 3, the monitoring device 1 stores test result information 131, correspondence information 132, status information 133, notification information 134, and API result information 135 in the information storage area 130.

  The virtual machine placement unit 111 places a monitoring VM used for monitoring a plurality of monitoring targets including the hypervisor 2c on the hypervisor 2c. Specifically, for example, the virtual machine placement unit 111 instructs the hypervisor 2c to place a monitoring VM that can perform the same processing as the user VM 2a.

  The test result acquisition unit 112 acquires test result information 131 indicating a predetermined test result executed by the monitoring VM at a predetermined interval. The predetermined test is a variety of tests determined in advance by the cloud operator, for example, a test for determining whether the access speed that the CPU of the monitoring VM performs on the memory or the disk is equal to or higher than a predetermined threshold. is there.

  The abnormality presence / absence determination unit 113 determines whether an abnormality has occurred in the monitoring VM from the test result acquired by the test result acquisition unit 112.

  When the abnormality presence / absence determination unit 113 determines that an abnormality has occurred in the monitoring VM, the state acquisition unit 114 determines a predetermined number of monitoring targets (for example, the storage device 3 and the API server 4 described in FIG. 1). Status information 133 indicating the status is acquired. The predetermined state includes, for example, information indicating whether normal processing performed by each monitoring target is normally executed.

  The execution instruction unit 115 instructs the API server 4 to perform predetermined processing. The predetermined process is, for example, generation of a new user VM 2a in the physical machine 2 or deletion of the generated user VM 2a. In this case, for example, the state acquisition unit 114 acquires the API result information 135 indicating the execution result of the predetermined process instructed by the execution instruction unit 115 as information indicating the state of the API server 4.

  The result output unit 116 outputs notification information 134 including, for example, the determination result of the abnormality of the monitoring VM in the abnormality presence / absence determination unit 113 and the state information 133 and API result information 135 acquired by the state acquisition unit 114. Specifically, the result output unit 116 outputs the notification information 134 to, for example, an output device (not shown) of the supervisor terminal 1a. The correspondence information 132 will be described later.

[Outline of First Embodiment]
Next, an outline of the first embodiment will be described. 4 and 5 are flowcharts for explaining an overview of the monitoring process in the first embodiment. 6 to 8 are diagrams for explaining the outline of the monitoring process in the first embodiment. Details of the monitoring process of FIGS. 4 and 5 will be described with reference to FIGS. 6 to 8, the description and description of the network device 5 described in FIG. 1 are omitted.

  As shown in FIG. 4, the monitoring device 1 waits until the virtual machine placement timing (NO in S1). The virtual machine placement timing may be, for example, a timing at which the cloud operator inputs to the supervisor terminal 1a to start monitoring the user VM 2a.

  When the virtual machine placement timing comes (YES in S1), the monitoring device 1 places a monitoring virtual machine used for monitoring a plurality of monitoring targets including the hypervisor 2c on the hypervisor 2c ( S2).

  Specifically, for example, as illustrated in FIG. 6, the monitoring device 1 arranges a monitoring VM 2 b for monitoring the user VM 2 a and the like on the hypervisor 2 c where the user VM 2 a is arranged.

  Thereafter, as shown in FIG. 5, the monitoring device 1 stands by until the abnormality determination timing is reached (NO in S11). The abnormality determination timing may be, for example, a timing at predetermined intervals determined in advance by the cloud operator.

  When the abnormality determination timing is reached (YES in S11), the monitoring device 1 acquires the result of a predetermined test executed by the monitoring virtual machine (S12). Furthermore, the monitoring device 1 determines whether there is an abnormality in the monitoring virtual machine from the result acquired in the process of S12 (S13).

  Specifically, for example, as illustrated in FIG. 7, the monitoring device 1 acquires a result of a predetermined test (for example, test result information 131) from the monitoring VM 2b, and determines whether the monitoring VM 2b is abnormal from the acquired result. judge.

  As a result, when it is determined that there is an abnormality in the monitoring virtual machine (YES in S14), the monitoring device 1 acquires a predetermined state of a plurality of monitoring targets (S15). Thereafter, the monitoring device 1 outputs the determination result regarding the presence or absence of abnormality of the monitoring virtual machine in the processing of S13 and the predetermined states of the plurality of monitoring targets acquired in the processing of S15 (S16).

  Specifically, for example, as illustrated in FIG. 8, the monitoring device 1 acquires a state (for example, state information 133) from the storage device 3 or the API server 4 included in the monitoring target. Then, the monitoring device 1 outputs, for example, information indicating whether or not the monitoring VM 2b is abnormal and information indicating the status of the storage device 3, the API server 4 and the like to the supervisor terminal 1a.

  On the other hand, when it is determined that there is no abnormality in the monitoring virtual machine (NO in S14), the monitoring device 1 does not perform the processes in S15 and S16.

  That is, the monitoring device 1 according to the present embodiment is, for example, a monitoring device that allows the monitoring device 1 to acquire information on the hypervisor 2c on which the user VM 2a that the monitoring device 1 cannot acquire information operates. Arrange VM2b. Then, the monitoring device 1 estimates the operation state acquired from the monitoring VM 2b as the current operation state of the user VM 2a.

  Thus, for example, when the monitoring device 1 detects an abnormality that has occurred in the hypervisor 2c, the monitoring device 1 refers to the operation state acquired from the monitoring VM 2b, thereby determining the degree of influence that the generated abnormality has on the user VM 2a. It becomes possible to estimate. The monitoring device 1 can also detect an abnormality (abnormality caused by the hypervisor 2c) that cannot be detected by the hypervisor 2c, for example, by referring to the operation state acquired from the monitoring 2bVM. .

  Therefore, even if the monitoring device 1 cannot directly access the user VM 2a and cannot acquire information indicating the operation state of the user VM 2a, the monitoring device 1 is in an abnormal state in the monitoring target of the cloud operator. It becomes possible to specify the degree of influence on the resource of the service provider due to the problem. Therefore, for example, when an abnormality occurs in the monitoring target of the cloud operator, the cloud operator can take measures according to the actual degree of influence on the resource of the service operator.

[Details of First Embodiment]
Next, details of the first embodiment will be described. 9 to 12 are flowcharts for explaining details of the monitoring processing in the first embodiment. FIGS. 13 to 21 are diagrams for explaining the details of the monitoring process in the first embodiment. Details of the monitoring process of FIGS. 9 to 12 will be described with reference to FIGS. 13 to 21. FIG. In the following description, it is assumed that the monitoring virtual machine that monitors the user VM 2a is the monitoring VM 2b.

[Process of allocating monitoring VM]
First, of the monitoring processing, processing for arranging the monitoring VM 2b will be described.

  As shown in FIG. 9, the virtual machine placement unit 111 of the monitoring device 1 waits until the virtual machine placement timing (NO in S21). When the virtual machine placement timing comes (YES in S21), the virtual machine placement unit 111 monitors one or more hypervisors 2c on the monitoring VM 2b used for monitoring a plurality of monitoring targets including each hypervisor 2c. Are arranged respectively (S22).

  Specifically, for example, the virtual machine placement unit 111 refers to information (not illustrated) indicating the hypervisor 2c in which each user VM 2a is placed among the information stored in the information storage area 130, and uses each use. One or more hypervisors 2c in which the person VM2a is arranged are specified. Then, the virtual machine placement unit 111 instructs the identified hypervisor 2c to place the monitoring VM 2b.

  Thereafter, the virtual machine placement unit 111 generates correspondence information 132 in which the monitoring VM 2b placed in the process of S22 is associated with the hypervisor 2c on which each monitoring VM 2b is placed (S23). Then, the virtual machine placement unit 111 stores the generated correspondence information 132 in the information storage area 130. Hereinafter, a specific example of the correspondence information 132 generated in the process of S23 will be described.

[Specific example of correspondence information (1)]
FIG. 13 is a diagram for describing a specific example of the correspondence information 132.

  The correspondence information 132 (hereinafter also referred to as correspondence information 132a) illustrated in FIG. 13 includes “item number” for identifying each information, “HVID” for identifying each hypervisor 2c, and “monitoring” for identifying each monitoring VM 2b. "VMID for use" as an item.

  Specifically, in the correspondence information 132a shown in FIG. 13, “001” is set as “HVID” and “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”. Is set. Further, in the correspondence information 132a shown in FIG. 13, “002” is set as “HVID” and “yyy” is set as “monitoring VMID” in the information whose “item number” is “2”. ing. Description of other information included in FIG. 13 is omitted.

[Processing when abnormality is detected in monitoring VM]
Next, of the monitoring process, a process when an abnormality is detected in the monitoring VM 2b will be described.

  As shown in FIG. 10, the test result acquisition unit 112 of the monitoring device 1 waits until an abnormality determination timing is reached (NO in S31). When the abnormality determination timing comes (YES in S31), the test result acquisition unit 112 displays test result information 131 indicating the result of a predetermined test instructed to be executed in advance for each monitoring VM 2b. (S32). Thereafter, the test result acquisition unit 112 stores the test result information 131 acquired from each monitoring VM 2b in the information storage area 130. Hereinafter, a specific example of the test result information 131 acquired in the process of S32 will be described.

[Specific example of test result information (1)]
FIG. 14 is a diagram for describing a specific example of the test result information 131 and the state information 133. Specifically, FIG. 14A is a diagram for describing a specific example of the test result information 131.

  The test result information 131 (hereinafter also referred to as test result information 131a1) shown in FIG. 14A includes “item number” for identifying each information, “monitoring VMID” for identifying each monitoring VM 2b, and each monitoring. “Test result (first test)” and “test result (second test)” in which the result of a predetermined test instructed to be executed by the VM 2b is set as items. “Test result (first test)” and “test result (second test)” include “OK” indicating that the test result is normal, “NG” indicating that the test result is abnormal, Alternatively, “not acquired” indicating that the test result could not be acquired is set.

  Specifically, in the test result information 131a1 shown in FIG. 14A, “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”, and “test result (first “OK” is set as “Test” ”, and“ OK ”is set as“ Test result (second test) ”. That is, the test result information 131a1 illustrated in FIG. 14A includes information indicating that the monitoring VM 2b whose “monitoring VMID” is “xxx” is normal.

  On the other hand, in the test result information 131a1 shown in FIG. 14A, “yyy” is set as “monitoring VMID” in the information whose “item number” is “2”, and “test result (first test)” "OK" is set as "", and "NG" is set as "Test result (second test)". That is, the test result information 131a1 illustrated in FIG. 14A includes information indicating that the monitoring VM 2b whose “monitoring VMID” is “xxx” is abnormal. Description of other information included in the test result information 131a1 illustrated in FIG. 14 is omitted.

  Returning to FIG. 10, the abnormality presence / absence determining unit 113 of the monitoring device 1 refers to the test result information 131 stored in the information storage area 130 and determines whether or not there is a monitoring VM 2b having an abnormality (S33). .

  Specifically, the abnormality presence / absence determination unit 113 refers to, for example, the test result information 131 stored in the information storage area 130 (the test result information 131 acquired in the process of S32), and “test result (first test)”. And “test result (second test)”, it is determined whether or not there is information in which “NG” or “not acquired” is set. Then, the abnormality presence / absence determining unit 113 determines that there is no information in which “NG” or “not acquired” is set in any of “test result (first test)” and “test result (second test)”. If determined, it is determined that all the monitoring VMs 2b are normal. Further, the abnormality presence / absence determining unit 113 determines that there is information in which “NG” or “not acquired” is set in either of the “test result (first test)” and “test result (second test)”. In this case, it is determined that the monitoring VM 2b corresponding to the information determined to exist is abnormal.

  As a result, when it is determined that there is no monitoring VM 2b that has been determined to be abnormal (NO in S34), the test result acquisition unit 112 performs the processes subsequent to S31 again.

  On the other hand, when it is determined that there is a monitoring VM 2b that is determined to be abnormal (YES in S34), the status acquisition unit 114 of the monitoring device 1 refers to the correspondence information 132 stored in the information storage area 130, and S34 The monitoring target corresponding to the monitoring VM 2b that is determined to be abnormal in the process is specified (S35). Then, the status acquisition unit 114 acquires status information 133 indicating the specified status of the monitoring target (S35). Thereafter, the state acquisition unit 114 stores the acquired state information 133 in the information storage area 130. Hereinafter, a specific example of the state information 133 acquired in the process of S35 will be described.

[Specific example of status information (1)]
FIG. 14B is a diagram for describing a specific example of the state information 133.

  The status information 133 (hereinafter also referred to as status information 133a1) shown in FIG. 14B includes “item number” for identifying each information, “HVID” for identifying each hypervisor 2c, and the status of each hypervisor 2c. As an item. In “Status”, “OK” indicating that the state of the hypervisor 2c is normal, “NG” indicating that the state of the hypervisor 2c is abnormal, or information can be acquired from the hypervisor 2c. One of “unacquired” indicating that there was no information is set.

  Specifically, in the status information 133a1 shown in FIG. 14B, “002” is set as “HVID” and “OK” is set as “status” in the information whose “item number” is “1”. Has been.

  That is, in the test result information 131a1 described with reference to FIG. 14A, the “test result (second test)” of the information whose “item number” is “2” (information whose “monitoring VMID” is “yyy”). "" Is set to "NG". In the correspondence information 132 a described with reference to FIG. 13, “002” is set in “HVID” of information in which “yyy” is set in “monitoring VMID”. Therefore, in the process of S35, the state acquisition unit 114 accesses the hypervisor 2c whose “HVID” is “002” and acquires information included in the state information 133a1 illustrated in FIG.

  After that, the result output unit 115 of the monitoring device 1 outputs the determination result of whether or not the monitoring VM 2b is abnormal to the process of S34 and the status information 133 of the monitoring target acquired in the process of S35 (S36).

  Specifically, for example, the result output unit 115 generates the notification information 134 from the determination result of the presence or absence of abnormality of the monitoring VM 2b in the process of S34 and the monitoring target state information 133 acquired in the process of S35. The notification information 134 is output to the supervisor terminal 1a. A specific example of the notification information 134 will be described later.

  Thereby, the monitoring apparatus 1 is related to the abnormality when the abnormality is detected in the monitoring VM 2b regardless of whether the abnormality is detected in the monitoring target (for example, the hypervisor 2c) of the cloud operator. It is possible to output information to be performed. Therefore, the monitoring device 1 can prevent omission of detection of an influence (an influence on the resource of the service provider) due to the abnormality in the monitoring target of the cloud provider.

  In addition, the monitoring apparatus 1 outputs not only the content of the abnormality detected in the monitoring VM 2b but also the information on the monitoring target related to the monitoring VM 2b in which the abnormality is detected, thereby investigating the cause of the detected abnormality. It is possible to quickly output information necessary for performing the operation.

[Processing when an abnormality is detected in the monitoring target of the cloud service provider]
Next, of the monitoring processing, processing when an abnormality is detected in the monitoring target of the cloud operator will be described.

  As shown in FIG. 11, the state acquisition unit 114 waits until the abnormality determination timing (NO in S41). The abnormality determination timing illustrated in FIG. 11 may be, for example, the same timing as the abnormality determination timing described in FIG.

  When the abnormality determination timing is reached (YES in S41), the state acquisition unit 114 acquires state information 133 indicating each state of one or more monitoring targets (S42). Thereafter, the state acquisition unit 114 stores the state information 133 acquired from each monitoring target in the information storage area 130. Hereinafter, a specific example of the state information 133 acquired in the process of S42 will be described.

[Specific example of status information (2)]
FIG. 15 is a diagram for describing a specific example of the test result information 131 and the state information 133. Specifically, FIG. 15B is a diagram for describing a specific example of the state information 133.

  In the status information 133 (hereinafter also referred to as status information 133a2) shown in FIG. 15B, “001” is set as “HVID” in the information whose “item number” is “1”, and “status” “OK” is set. In the status information 133a2 shown in FIG. 15B, “003” is set as “HVID” and “NG” is set as “status” in the information whose “item number” is “3”. Yes. Description of other information included in FIG.

  Returning to FIG. 11, the abnormality presence / absence determination unit 113 refers to the state information 133 stored in the information storage area 130 and determines whether there is a monitoring target having an abnormality (S <b> 43).

  Specifically, the abnormality presence / absence determination unit 113 refers to, for example, the state information 133 (the state information 133 acquired in the processing of S42) stored in the information storage area 130, and sets “Status” to “NG” or “Not acquired”. It is determined whether or not there is information set with “”. Then, the abnormality presence / absence determination unit 113 determines that all the monitoring targets are normal when determining that there is no information in which “NG” or “not acquired” is set in the “state”. Further, when the abnormality presence / absence determining unit 113 determines that there is information in which “NG” or “not acquired” is set in any of the “states”, the monitoring target corresponding to the information determined to exist is abnormal. Judge that there is.

  As a result, when it is determined that there is no monitoring target determined to be abnormal (NO in S44), the state acquisition unit 114 performs the processing from S41 onward again.

  On the other hand, when it is determined that there is a monitoring target that is determined to be abnormal (YES in S44), the test result acquisition unit 112 refers to the correspondence information 132 stored in the information storage area 130 and performs an abnormality in the process of S44. The monitoring VM 2b corresponding to the monitoring target determined to be present is specified (S45). Then, the test result acquisition unit 112 acquires the test result information 131 of the specified monitoring VM 2b (S45). Hereinafter, a specific example of the test result information 131 acquired in the process of S45 will be described.

[Specific example of test result information (2)]
FIG. 15A is a diagram for describing a specific example of the test result information 131.

  In the test result information 131 (hereinafter also referred to as test result information 131a2) shown in FIG. 15A, “zzz” is set as “monitoring VMID” in the information whose “item number” is “1”. “OK” is set as “test result (first test)”, and “OK” is set as “test result (second test)”.

  That is, in the status information 133a2 described in FIG. 15B, “NG” is set in the “status” of the information whose “item number” is “3” (information whose “HVID” is “003”). Has been. In the correspondence information 132a described with reference to FIG. 13, “zzzz” is set in “monitoring VMID” of information in which “003” is set in “HVID”. Therefore, in the process of S45, the test result acquisition unit 112 accesses the monitoring VM 2b whose “monitoring VMID” is “zzz” and acquires information included in the test result information 131a2 illustrated in FIG. .

  Returning to FIG. 12, the abnormality presence / absence determining unit 113 refers to the test result information 131 stored in the information storage area 130, and the monitoring VM 2b that acquired the test result information 131 in the process of S45 has an abnormality in the monitoring VM 2b. Is determined (S51).

  As a result, when it is determined that there is a monitoring VM 2b that is determined to be abnormal (YES in S51), the result output unit 115 determines whether there is an abnormality in each monitoring target in the process of S44, and in the process of S51. The determination result of the presence or absence of abnormality of each monitoring VM 2b and information indicating that the degree of abnormality detected in the process of S51 is a first abnormality (for example, an abnormality having an emergency level of “high”) are output (S52). ).

  Specifically, for example, the result output unit 115 determines the presence / absence of abnormality of each monitoring target in the process of S44, the determination result of abnormality of each monitoring VM 2b in the process of S51, and the abnormality detected in the process of S51. The notification information 134 is generated from the information indicating that the degree of the first abnormality is the first abnormality, and the generated notification information 134 is output to the supervisor terminal 1a.

  On the other hand, if it is determined that there is no monitoring VM 2b that is determined to be abnormal (NO in S51), the result output unit 115 determines whether there is an abnormality in each monitoring target in the process of S44, and in the process of S51. A determination result of whether each monitoring VM 2b is abnormal or not and information indicating that the degree of abnormality detected in the process of S51 is the second abnormality (for example, an abnormality having an urgent level of “low”) are output (S53). ).

  Specifically, for example, the result output unit 115 determines the presence / absence of abnormality of each monitoring target in the process of S44, the determination result of abnormality of each monitoring VM 2b in the process of S51, and the abnormality detected in the process of S51. The notification information 134 is generated from the information indicating that the degree of the second abnormality is the second abnormality, and the generated notification information 134 is output to the supervisor terminal 1a.

  As a result, when an abnormality is detected in the monitoring target (for example, the hypervisor 2c) of the cloud operator, the monitoring device 1 takes into consideration the occurrence state of the abnormality in the monitoring VM 2b, and information related to the detected abnormality Can be output. Therefore, the monitoring device 1 can output information according to the degree of the influence (impact on the resource of the service provider) caused by the abnormality in the monitoring target of the cloud provider. Therefore, the cloud provider can take measures according to the degree of influence on the resource of the service provider by referring to the information output by the monitoring device 1.

[Other Specific Example (1) in First Embodiment]
Next, another specific example in the first embodiment will be described. FIGS. 16 to 18 are diagrams for explaining other specific examples in the first embodiment.

  As shown in FIG. 9, the virtual machine placement unit 111 monitors a plurality of monitoring targets including each hypervisor 2c on one or more hypervisors 2c when the virtual machine placement timing comes (YES in S21). The monitoring VMs 2b to be used are respectively arranged (S22).

  Specifically, the virtual machine placement unit 111 specifies the hypervisor 2c in which each user VM 2a is placed. Then, the virtual machine placement unit 111 places the monitoring VM 2b in each of the identified hypervisors 2c. In this case, for example, the virtual machine placement unit 111 reserves a monitoring volume corresponding to each of the monitoring VMs 2b in the storage apparatus 3 described with reference to FIG.

  Then, the virtual machine placement unit 111 generates correspondence information 132 in which the monitoring VM 2b placed in the process of S22 is associated with the hypervisor 2c on which each monitoring VM 2b is placed (S23). Thereafter, the virtual machine placement unit 111 stores the generated correspondence information 132 in the information storage area 130. Hereinafter, a specific example of the correspondence information 132 generated in the process of S23 will be described.

[Specific example of correspondence information (2)]
FIG. 16 is a diagram for describing a specific example of the correspondence information 132. Specifically, FIG. 16A is a diagram for describing correspondence information 132 (hereinafter also referred to as correspondence information 132b1) indicating the correspondence between the storage apparatus 3 and the monitoring volume. FIG. 16B is a diagram for explaining correspondence information 132 (hereinafter also referred to as correspondence information 132b2) indicating the correspondence between the monitoring VM 2b and the monitoring volume.

  The correspondence information 132b1 shown in FIG. 16A includes an “item number” for identifying each information, a “storage ID” for identifying each storage device 3, and a “monitoring volume ID” for identifying each monitoring volume. As an item.

  Specifically, in the correspondence information 132b1 shown in FIG. 16A, “011” is set as the “storage ID” in the information whose “item number” is “1”, and “monitoring volume ID” “Vol_xxx” is set. In the correspondence information 132b1 shown in FIG. 16A, “012” is set as the “storage ID” and “012” is set as the “monitoring volume ID” in the information whose “item number” is “2”. vol_yyy "is set. Description of other information included in FIG.

  On the other hand, the correspondence information 132b2 shown in FIG. 16B includes an “item number” for identifying each information, a “monitoring VMID” for identifying each monitoring VM 2b, and a “monitoring volume” for identifying each monitoring volume. "ID" as an item.

  Specifically, in the correspondence information 132b2 shown in FIG. 16B, “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”, and “monitoring volume ID” "Vol_xxx" is set. In the correspondence information 132b2 shown in FIG. 16B, “yyy” is set as the “monitoring VMID” in the information whose “item number” is “2”, and the “monitoring volume ID” is set as the “monitoring volume ID”. “Vol_yyy” is set. Description of other information included in FIG.

  Subsequently, as shown in FIG. 10, the test result acquisition unit 112, when the abnormality determination timing is reached (YES in S31), indicates a result of a predetermined test instructed to be executed in advance for each monitoring VM 2b. The result information 131 is acquired from each monitoring VM 2b and each monitoring volume (S32). Specifically, in this case, for example, the test result acquisition unit 112 determines whether or not the access speed when each monitoring VM 2b accesses each monitoring volume is equal to or higher than a predetermined threshold. Get the result. Then, the test result acquisition unit 112 stores the test result information 131 acquired from each monitoring VM 2b and the monitoring volume in the information storage area 130. Hereinafter, a specific example of the test result information 131 acquired in the process of S32 will be described.

[Specific example of test result information (3)]
FIG. 17 is a diagram for describing a specific example of the test result information 131 and the state information 133. Specifically, FIG. 17A is a diagram for describing a specific example of the test result information 131.

  The test result information 131 (hereinafter also referred to as test result information 131b1) shown in FIG. 17A includes “item number” for identifying each information, “monitoring VMID” for identifying each monitoring VM 2b, and each monitoring. “Monitoring volume ID” for identifying the monitoring volume, and “Test result (third test)” and “Test result (fourth test)” in which the result of the test instructed to be executed by the monitoring VM 2b is set. Have as.

  Specifically, in the test result information 131b1 shown in FIG. 17A, “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”, and “monitoring volume ID” “Vol_xxx” is set, “OK” is set as “test result (third test)”, and “OK” is set as “test result (fourth test)”. That is, in the test result information 131b1 shown in FIG. 17A, the monitoring VM 2b whose “monitoring VMID” is “xxx” and the monitoring volume whose “monitoring volume ID” is “vol_xxx” are normal. It contains information indicating that.

  On the other hand, in the test result information 131b1 shown in FIG. 17A, “yyy” is set as “monitoring VMID” and “monitoring volume ID” is set to “2” in the information whose “item number” is “2”. “vol_yyy” is set, “OK” is set as the “test result (third test)”, and “NG” is set as the “test result (fourth test)”. That is, the test result information 131b1 shown in FIG. 17A includes at least one of the monitoring VM 2b whose “monitoring VMID” is “yyy” and the monitoring volume whose “monitoring volume ID” is “vol_yyy”. It contains information indicating that was abnormal. A description of other information included in the test result information 131b1 illustrated in FIG.

  Returning to FIG. 10, the abnormality presence / absence determination unit 113 refers to the test result information 131 stored in the information storage area 130 (the test result information 131 acquired in the process of S32), and has a monitoring VM 2b or a monitoring volume having an abnormality. Is determined (S33).

  As a result, when there is a monitoring VM 2b or a monitoring volume determined to be abnormal (YES in S34), the status acquisition unit 114 refers to the correspondence information 132 stored in the information storage area 130, and in S34 The monitoring target corresponding to the monitoring VM 2b or the monitoring volume determined to be abnormal in the process is specified (S35). Then, the status acquisition unit 114 acquires status information 133 indicating the specified status of the monitoring target (S35). Thereafter, the state acquisition unit 114 stores the acquired state information 133 in the information storage area 130. Hereinafter, a specific example of the state information 133 acquired in the process of S35 will be described.

[Specific example of status information (3)]
FIG. 17B is a diagram for describing a specific example of the state information 133.

  The status information 133 (hereinafter also referred to as status information 133b1) shown in FIG. 17B includes “item number” for identifying each information, “storage ID” for identifying each storage device 3, and each storage device 3 “State” indicating the state is included as an item.

  Specifically, in the status information 133b1 shown in FIG. 17B, “012” is set as the “storage ID” and “OK” is set as the “status” in the information whose “item number” is “1”. Is set.

  That is, in the test result information 131b1 described with reference to FIG. 17A, the "test result (fourth test)" of the information whose "item number" is "2" (information whose "monitoring VMID" is "yyy") "" Is set to "NG". In the correspondence information 132b1 described with reference to FIG. 16A, “012” is set in the “storage ID” of the information in which “yyy” is set in the “monitoring VMID”. Therefore, in the process of S35, the status acquisition unit 114 accesses the storage device 3 whose “storage ID” is “012”, and acquires information included in the status information 133b1 illustrated in FIG.

  Thereafter, the result output unit 115 outputs the determination result of whether the monitoring VM 2b or the monitoring volume is abnormal to the process of S34 and the status information 133 of the monitoring target acquired in the process of S35 (S36).

  Moreover, as shown in FIG. 11, when the abnormality determination timing is reached (YES in S41), the state acquisition unit 114 acquires state information 133 indicating each state of one or more monitoring targets (S42). Thereafter, the state acquisition unit 114 stores the state information 133 acquired from each monitoring target in the information storage area 130. Hereinafter, a specific example of the state information 133 acquired in the process of S42 will be described.

[Specific example of status information (4)]
FIG. 18 is a diagram for describing a specific example of the test result information 131 and the state information 133. Specifically, FIG. 18B is a diagram illustrating a specific example of the state information 133.

  In the status information 133 (hereinafter also referred to as status information 133b2) shown in FIG. 18B, “011” is set as the “storage ID” for the information whose “item number” is “1”, and “status” "NG" is set. In the status information 133b2 shown in FIG. 18B, “012” is set as the “storage ID” and “OK” is set as the “status” in the information whose “item number” is “2”. ing. Description of other information included in FIG. 18B is omitted.

  Returning to FIG. 11, the abnormality presence / absence determination unit 113 refers to the state information 133 stored in the information storage area 130 and determines whether there is a monitoring target having an abnormality (S <b> 43).

  As a result, when there is a monitoring target determined to be abnormal (YES in S44), the test result acquisition unit 112 refers to the correspondence information 132 stored in the information storage area 130, and the abnormality is detected in the process of S44. The monitoring VM 2b and the monitoring volume corresponding to the monitoring target determined to be present are specified (S45). Thereafter, the test result acquisition unit 112 acquires the test result information 131 of the specified monitoring VM 2b or monitoring volume (S45). Hereinafter, a specific example of the state information 133 acquired in the process of S45 will be described.

[Specific example of test result information (4)]
FIG. 18A is a diagram for describing a specific example of the test result information 131.

  In the test result information 131 shown in FIG. 18A (hereinafter also referred to as test result information 131b2), “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”. “Vol_xxx” is set as the “monitoring volume ID”, “OK” is set as the “test result (third test)”, and “OK” is set as the “test result (fourth test)”.

  That is, in the status information 133b2 described with reference to FIG. 18B, “NG” is set in the “status” of the information whose “item number” is “1” (information whose “storage ID” is “011”). Is set. In the correspondence information 132b1 described with reference to FIG. 16A, “vol_xxx” is set in the “monitoring volume ID” of the information in which “011” is set in the “storage ID”. Therefore, the test result acquisition unit 112 accesses the monitoring volume whose “monitoring volume ID” is “vol_xxx” in the process of S45, and acquires the information included in the test result information 131b2 illustrated in FIG. To do.

  Returning to FIG. 12, when there is a monitoring VM 2b that is determined to be abnormal (YES in S51), the result output unit 115 determines whether there is an abnormality in each monitoring target in the process of S44, and in the process of S51. The determination result of the presence or absence of abnormality of each monitoring VM 2b and information indicating that the degree of abnormality detected in the process of S51 is the first abnormality are output (S52).

  As a result, the monitoring device 1 does not depend on whether or not an abnormality is detected in the monitoring target of the cloud operator (for example, the storage device 3), and when an abnormality is detected in the monitoring VM 2b or the monitoring volume, It becomes possible to output information related to the abnormality. Therefore, the monitoring device 1 can prevent omission of detection of an influence (an influence on the resource of the service provider) due to the abnormality in the monitoring target of the cloud provider.

  In addition, when an abnormality is detected in the monitoring target of the cloud operator, the monitoring device 1 outputs information related to the detected abnormality in consideration of the abnormality occurrence state in the monitoring VM 2b and the monitoring volume. Is possible. Therefore, the monitoring device 1 can output information according to the degree of the influence (impact on the resource of the service provider) caused by the abnormality in the monitoring target of the cloud provider. Therefore, the cloud provider can take measures according to the degree of influence on the resource of the service provider by referring to the information output by the monitoring device 1.

[Other Specific Example (2) in First Embodiment]
Next, another specific example in the first embodiment will be described. 19 and 20 are diagrams for explaining another specific example in the first embodiment.

  As shown in FIG. 9, the virtual machine placement unit 111 monitors a plurality of monitoring targets including each hypervisor 2c on one or more hypervisors 2c when the virtual machine placement timing comes (YES in S21). The monitoring VMs 2b to be used are respectively arranged (S22).

  Then, the virtual machine placement unit 111 generates correspondence information 132 in which the monitoring VM 2b placed in the process of S22 is associated with the hypervisor 2c on which each monitoring VM 2b is placed (S23). Thereafter, the virtual machine placement unit 111 stores the generated correspondence information 132 in the information storage area 130. Hereinafter, the correspondence information 132 will be described in the process of S23.

[Specific example of correspondence information (3)]
FIG. 19 is a diagram illustrating a specific example of the correspondence information 132. Specifically, the correspondence information 132 (hereinafter also referred to as correspondence information 132c) illustrated in FIG. 19 is information indicating the relationship between the monitoring VM 2b and the network device 5 such as a switch with respect to the correspondence information 132a described in FIG. Is added information.

  The correspondence information 132c illustrated in FIG. 19 includes, as items, “item number” for identifying each information, “HVID” for identifying each hypervisor 2c, and “monitoring VMID” for identifying each monitoring VM 2b. The correspondence information 132c illustrated in FIG. 19 includes “NICID” that identifies a physical NIC (Network interface card) used by each hypervisor 2c, “NW device ID” that identifies each network device 5, and each network device. 5 has “port ID” for identifying each port included in 5 as an item.

  Specifically, in the correspondence information 132c shown in FIG. 19, “001” is set as “HVID” and “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”. , “NIC_01” is set as “NICID”, “1” is set as “NW device ID”, and “Port 1-1” is set. In addition, in the correspondence information 132c shown in FIG. 19, “002” is set as “HVID”, “yyy” is set as “monitoring VMID”, and “yyy” is set as “HVID”. “NIC_11” is set as “NICID”, “1” is set as “NW device ID”, and “port 1-2” is set as “port ID”. Description of other information included in FIG. 19 is omitted.

  Returning to FIG. 10, when the abnormality determination timing is reached (YES in S31), the test result acquisition unit 112 stores test result information 131 indicating the result of a predetermined test instructed to be executed in advance for each monitoring VM 2b. Obtained from the monitoring VM 2b (S32). Thereafter, the test result acquisition unit 112 stores the test result information 131 acquired from each monitoring VM 2b in the information storage area 130. Hereinafter, a specific example of the test result information 131 acquired in the process of S32 will be described.

[Specific example of test result information (5)]
FIG. 20 is a diagram for describing a specific example of the test result information 131 and the state information 133. Specifically, FIG. 20A is a diagram for describing a specific example of the test result information 131.

  The test result information 131 (hereinafter also referred to as test result information 131c) shown in FIG. 20A includes “item number” for identifying each information, “monitoring VMID” for identifying each monitoring VM 2b, and monitoring information. “Test result (fifth test)” and “test result (sixth test)” in which the result of the test instructed to be executed by the VM 2b is set as items.

  Specifically, in the test result information 131c shown in FIG. 20A, “xxx” is set as “monitoring VMID” in the information whose “item number” is “1”, and “test result (fifth) “Not acquired” is set as “Test” ”, and“ Not acquired ”is set as“ Test result (sixth test) ”. That is, the test result information 131c shown in FIG. 20A cannot be acquired from the monitoring VM 2b whose “monitoring VMID” is “xxx” (the “monitoring VMID” is “xxx”). Is included in the monitoring VM 2b). Description of other information included in the test result information 131b1 illustrated in FIG.

  Returning to FIG. 10, when there is a monitoring VM 2b that is determined to be abnormal (YES in S34), the state acquisition unit 114 refers to the correspondence information 132 stored in the information storage area 130, and performs the process of S34. A monitoring target corresponding to the monitoring VM 2b determined to be abnormal is specified (S35). Then, the status acquisition unit 114 acquires status information 133 indicating the specified status of the monitoring target (S35). Thereafter, the state acquisition unit 114 stores the acquired state information 133 in the information storage area 130. Hereinafter, a specific example of the state information 133 acquired in the process of S35 will be described.

[Specific example of status information (5)]
FIG. 20B is a diagram for explaining a specific example of the state information 133c1 of the physical NIC used by the hypervisor 2c. FIG. 20C is a diagram for describing a specific example of port status information 133c2 included in the network device 5 connected to the hypervisor 2c.

  The status information 133c1 illustrated in FIG. 20B includes, as items, “item number” that identifies each information, “NICID” that identifies each physical NIC, and “status” that indicates the status of each physical NIC. ing.

  Specifically, in the status information 133c1 illustrated in FIG. 20B, “NIC_01” is set as “NICID” and “OK” is set as “status” in the information whose “item number” is “1”. Has been. Description of the other information included in FIG.

  On the other hand, the status information 133c2 shown in FIG. 20C includes “item number” for identifying each information, “port ID” for identifying each port, and “status” indicating the status of each port as items. doing.

  Specifically, in the state information 133c2 shown in FIG. 20C, “port 1-1” is set as the “port ID” and “port 1-1” is set as the “state” in the information whose “item number” is “2”. “OK” is set. Note that information in which “device body” is set in “port ID” in the state information 133c2 illustrated in FIG. 20C indicates information regarding the network device 5 having each port. Description of other information included in FIG. 20C is omitted.

  That is, in the test result information 131c described in FIG. 20A, the “test result (fifth test)” of the information whose “item number” is “1” (information whose “monitoring VMID” is “xxx”) "And" Test result (sixth test) "are set to" Not acquired ". In the correspondence information 132c described with reference to FIG. 19, “NIC_01” is set in “NICID” and “1” is set in “NW device ID” in the information in which “xxx” is set in “monitoring VMID”. Is set, “Port 1-1” is set to “Port 1-1”, “NICID” is set to “NIC — 02”, “NW Device ID” is set to “2”, and “Port ID” is set to “Port ID”. Information in which “port 2-1” is set is included. Therefore, in the process of S35, the state acquisition unit 114 determines that the NIC whose “NICID” is “NIC_01”, the NIC whose “NICID” is “NIC_02”, the network device 5 itself, and the “port ID” is “port”. 1-1 ”and the port whose“ port ID ”is“ port 2-1 ”are accessed, and the status information 133c1 shown in FIG. 20B and the status information 133c2 shown in FIG. Get information contained in each of.

  Returning to FIG. 10, the result output unit 115 outputs the determination result of whether or not the monitoring VM 2 b is abnormal in the process of S <b> 34 and the status information 133 of the monitoring target acquired in the process of S <b> 35 (S <b> 36).

  Specifically, “OK” is set for all “states” in FIGS. 20B and 20C. Therefore, in this case, the result output unit 115 is, for example, in a virtual bridge in which information is not included in the state information 133c1 and the state information 133c2 among devices through which communication between the monitoring device 1 and the monitoring VM 2b passes. Information indicating that there is a possibility that an abnormality has occurred may be output as the notification information 134.

  Thus, for example, when the monitoring device 1 detects an abnormality that has occurred in the monitoring VM 2b, the result of the test executed by the monitoring VM 2b and the status of the monitoring target (for example, the network device 5) of the cloud operator Based on the above, it is possible to estimate the cause of the abnormality occurring in the monitoring VM 2b. Therefore, the monitoring device 1 can output not only the content of the abnormality detected in the monitoring VM 2b but also information that allows the cause of the detected abnormality to be investigated more quickly.

[Specific example of notification information (1)]
Next, a specific example of the notification information 134 will be described. FIG. 21 is a diagram for describing a specific example of the notification information 134.

  The notification information 134 (hereinafter also referred to as notification information 134a) illustrated in FIG. 21 includes an “item number” for identifying each piece of information (information corresponding to the detected abnormality), and an “emergency level” in which the urgency level of each abnormality is set. ”,“ Target resource ”in which the resource in which each abnormality is detected is set, and“ message ”in which the content of each abnormality is set. In addition, the notification information 134a illustrated in FIG. 21 includes an “estimated abnormal state” in which a “suspected place” in which a suspected place of each abnormality is set and an abnormal state (estimated) in a place set in the “suspected place” And “estimated influence range” in which the influence range (estimation) of each abnormality is set as items.

  Specifically, when it is determined that the monitoring VM (3) cannot be accessed in the process of S34, the result output unit 115, for example, “item number” is “1” as illustrated in FIG. “Monitoring VM (3)” is set as the “target resource” of the information, and “access impossible” is set as the “message”. Further, when the result output unit 115 acquires the state information 133 from the HV (3) and the NIC (1) in the process of S35, for example, “HV (3)” and “NIC (1)” as “suspected places”. Set. Further, the result output unit 115, when “NIC (1)” is set in “suspected place”, for example, “NIC (1)” is set in “suspected place” as “estimated abnormal state” “Hard abnormality” that is information (predetermined information) corresponding to is set. Further, the result output unit 115, when “HV (3)” is set in “suspected place”, for example, when “HV (3)” is set in “suspected place” as “estimated influence range” “HV (3)”, which is information corresponding to (predetermined information), is set. Furthermore, when the monitoring VM 2b is set in the “target resource”, the result output unit 115 sets “high” as the “emergency level”, for example.

  If the result output unit 115 determines that a disk failure has occurred in the disk (3) included in the storage (1) in the process of S44, for example, as shown in FIG. “Storage (1)” and “disk (3)” are set as “target resources” of information whose “is” “5”, and “disk failure” is set as “message”. Further, when “storage (1)” and “disk (3)” are set in “target resource”, for example, the result output unit 115 sets “storage (1)” and “disk ( 3) ”is set. Further, when “storage (1)” and “disk (3)” are set in “suspected place”, the result output unit 115 sets “storage ( “Hardware failure”, which is information (predetermined information) corresponding to the case where “1)” and “disk (3)” are set. In addition, when only “storage (1)” and “disk (3)” are set in the “suspected place”, the result output unit 115 sets “storage ( 1) "and" None "which is information (predetermined information) corresponding to the case where only" Disk (3) "is set. Further, when “none” is set in the “estimated influence range”, the result output unit 115 sets “low” as the “emergency level”, for example.

[Second Embodiment]
Next, a second embodiment will be described. 22 to 25 are flowcharts for explaining the monitoring process in the second embodiment. FIGS. 26 to 29 are diagrams for explaining the monitoring process in the second embodiment. The monitoring process of FIGS. 22 to 25 will be described with reference to FIGS.

  The monitoring device 1 according to the second embodiment, instead of generating the monitoring VM 2b, instructs the cloud service provider (for example, the API server 4 described in FIG. 1 and the like) to execute a predetermined process ( Hereinafter, an API (also referred to as an application programming interface) is transmitted. And the monitoring apparatus 1 in 2nd Embodiment generate | occur | produced in each monitoring object by referring the status information 133 acquired from each monitoring object, and the execution result of API transmitted with respect to each monitoring object Detect anomalies.

[Processing when detected by API transmission]
First, of the monitoring process, a process when an abnormality is detected by transmitting an API will be described.

  As shown in FIG. 22, the execution instruction unit 115 of the monitoring device 1 waits until an abnormality determination timing is reached (NO in S61). When the abnormality determination timing is reached (YES in S61), the execution instruction unit 115 transmits an API instructing execution of a predetermined process to each of the one or more API servers (S62).

  Thereafter, the execution instruction unit 115 waits until the execution of the predetermined process corresponding to the execution instruction transmitted in the process of S62 ends (NO in S63).

  Specifically, for example, when the API transmitted in the process of S62 is a synchronous API (hereinafter also referred to as a synchronous API), the execution instruction unit 115 waits until there is a response of the API transmitted in the process of S62. .

  Further, for example, when the API transmitted in the process of S62 is an asynchronous API (hereinafter also referred to as an asynchronous API), the execution instruction unit 115 transmits the API in the process of S62 and then processes the processing status every predetermined time. API for confirming (hereinafter also referred to as reference API) is transmitted. Then, the execution instruction unit 115 waits until the completion of the process corresponding to the API transmitted in the process of S62 can be confirmed by transmitting the reference API. The process performed by the asynchronous API may be, for example, a process for generating a new user VM 2a or a process for deleting a generated user VM 2a.

  When the execution of the predetermined process corresponding to the API transmitted in the process of S62 is completed (YES in S63), the execution instruction unit 115 displays an API result indicating the result of the predetermined process executed in the process of S63. Information 135 is generated (S64). Thereafter, the execution instruction unit 115 stores the generated API result information 135 in the information storage area 130, for example. Hereinafter, a specific example of the API result information 135 generated by the process of S64 will be described.

[Specific example of API result information (1)]
FIG. 27 is a diagram illustrating specific examples of the API result information 135 and the state information 133 in the second embodiment. Specifically, FIG. 27A is a diagram for describing a specific example of the API result information 135 according to the second embodiment.

  The API result information 135 (hereinafter also referred to as API result information 135d1) shown in FIG. 27A includes an “item number” for identifying each information, an “API ID” for identifying each API server 4, and each API server 4 As an item, “execution result” indicating the execution result of the predetermined process in FIG. The “execution result” includes “OK” indicating that the execution result by the API server 4 is normal, “NG” indicating that the execution result by the API server 4 is abnormal, or execution from the API server 4 One of “not acquired” indicating that the result could not be acquired is set.

  Specifically, in the API result information 135 shown in FIG. 27A, “021” is set as “APIID” and “OK” is set as “execution result” for the information whose “item number” is “1”. Is set. In the API result information 135 shown in FIG. 27A, “022” is set as “APIID” and “NG” is set as “execution result” for the information whose “item number” is “2”. Has been. Description of other information included in FIG.

  Returning to FIG. 22, the abnormality presence / absence determination unit 113 refers to the API result information 135 stored in the information storage area 130, and determines whether or not there is an API having an abnormality in the execution result (S65).

  Specifically, the abnormality presence / absence determination unit 113 refers to, for example, the test result information 131 (the API result information 135 generated in the process of S64) stored in the information storage area 130, and “NG” is displayed in the “execution result”. It is determined whether the set information exists. If the abnormality determination unit 113 determines that there is no information in which “NG” is set in the “execution result”, it determines that the execution results of all APIs are normal. Further, when it is determined that there is information having “NG” set in the “execution result”, the abnormality presence / absence determination unit 113 determines that the execution result of the API corresponding to the information determined to exist is abnormal.

  As a result, as shown in FIG. 23, when it is determined that there is no API that is determined to be abnormal in the execution result (NO in S71), the execution instruction unit 115 performs the processing from S61 onward again.

  On the other hand, when it is determined that there is an API that is determined to be abnormal in the execution result (YES in S71), the state acquisition unit 114 refers to the correspondence information 132 stored in the information storage area 130, and performs the process of S71. The monitoring target corresponding to the API determined to have an abnormality in the execution result is specified (S72). Then, the status acquisition unit 114 acquires status information 133 indicating the specified status of the monitoring target (S72). Thereafter, the state acquisition unit 114 stores the acquired state information 133 in the information storage area 130. Hereinafter, specific examples of the correspondence information 132 stored in advance in the information storage area 130 and the status information 133 acquired in the process of S72 will be described.

[Specific example of correspondence information (4)]
First, a specific example of the correspondence information 132 in the second embodiment will be described. FIG. 26 is a diagram illustrating a specific example of the correspondence information 132 in the second embodiment. Note that the correspondence information 132 (hereinafter also referred to as correspondence information 132d) in the second embodiment will be described as information generated by a cloud operator and stored in the information storage area 130 in advance.

  The correspondence information 132d illustrated in FIG. 26 includes, as items, “item number” for identifying each information, “APIID” for identifying each API, and “monitoring target ID” for identifying each monitoring target by the cloud operator. . The “monitoring target ID” includes, in addition to the hypervisor 2c, the storage device 3, the API server 4, and the network device 5, a controller (not shown) that secures physical resources necessary for generating a new user VM 2a, an API, Information for identifying a load distribution server (not shown) that distributes processing requests to the server 4, a queue server (not shown) that accumulates processing requests to the controller, and the like is set.

  Specifically, in the correspondence information 132d shown in FIG. 26, “021” is set as the “APIID” and “1” and “2” are set as the “monitoring target ID” in the information whose “item number” is “1”. "Is set. Also, in the correspondence information 132d shown in FIG. 26, “022” is set as “APIID” and “4”, “8” and “monitoring target ID” are set in the information whose “item number” is “2”. “9” is set. Description of other information included in FIG. 26 is omitted.

[Specific example of status information (6)]
Next, a specific example of the state information 133 (hereinafter also referred to as state information 133d1) in the second embodiment will be described.

  The state information 133d1 illustrated in FIG. 27B includes “item number” for identifying each information, “monitoring target ID” for identifying each monitoring target by the cloud operator, and “state” indicating the status of each monitoring target. As an item. In “Status”, “OK” indicating that the status of the monitoring target is normal, “NG” indicating that the status of the monitoring target is abnormal, or information can be acquired from the monitoring target. “Non-acquired” is set to indicate that there was not.

  Specifically, in the status information 133d1 shown in FIG. 27B, “4” is set as the “monitoring target ID” and “OK” is set as the “status” in the information whose “item number” is “1”. Is set. In the status information 133d1 shown in FIG. 27B, “8” is set as the “monitoring target ID” and “OK” is set as the “status” in the information whose “item number” is “2”. Has been. Description of other information included in FIG. 27B is omitted.

  That is, in the API result information 135d1 described with reference to FIG. 27A, the “execution result” of the information whose “item number” is “2” (information whose “APIID” is “022”) is “NG”. Is set. In the correspondence information 132d described with reference to FIG. 26, “4”, “8”, and “9” are set in the “monitoring target ID” of the information in which “022” is set in the “APIID”. For this reason, the status acquisition unit 114 accesses the monitoring targets whose “monitoring target ID” is “4”, “8”, and “9” in the processing of S71, and is included in the status information 133d1 illustrated in FIG. Get information.

  Returning to FIG. 23, the result output unit 115 outputs the determination result of the presence / absence of abnormality in the execution result of the API in the process of S71 and the status information 133 of the monitoring target acquired in the process of S72 (S73).

  Specifically, the result output unit 115 generates notification information 134 from the determination result of the presence / absence of abnormality in the execution result of the API in the process of S71 and the monitoring target state information 133 acquired in the process of S72. The notification information 134 is output to the supervisor terminal 1a.

  As a result, the monitoring device 1 has an abnormality in the execution result corresponding to the API transmitted to each monitoring target regardless of whether or not the abnormality is detected in the monitoring target (for example, the hypervisor 2c) of the cloud operator. When detected, it is possible to output information related to the abnormality. Therefore, the monitoring device 1 can prevent omission of detection of an influence (an influence on the resource of the service provider) due to the abnormality in the monitoring target of the cloud provider. Further, the monitoring device 1 investigates the cause of the detected abnormality by outputting not only the content of the abnormality detected by transmitting the API but also information on the monitoring target corresponding to the API where the abnormality is detected. It is possible to quickly output information necessary for performing the operation.

[Processing when an abnormality is detected in the monitoring target of the cloud service provider]
Next, of the monitoring processing, processing when an abnormality is detected in the monitoring target of the cloud operator will be described.

  As shown in FIG. 24, the state acquisition unit 114 waits until the abnormality determination timing (NO in S81). When the abnormality determination timing is reached (YES in S81), the status acquisition unit 114 acquires status information 133 indicating the status of each of one or more monitoring targets (S82). Thereafter, the state acquisition unit 114 stores the state information 133 acquired from each monitoring target in the information storage area 130. Hereinafter, a specific example of the state information 133 will be described.

[Specific example of status information (7)]
FIG. 28 is a diagram illustrating a specific example of the API result information 135 and the state information 133 in the second embodiment. Specifically, FIG. 28B is a diagram illustrating a specific example of the state information 133 according to the second embodiment.

  In the status information 133 (hereinafter also referred to as status information 133d2) shown in FIG. 28B, “1” is set as the “monitoring target ID” for the information whose “item number” is “1”. "" Is set as "OK". In the status information 133d2 shown in FIG. 28B, “3” is set as the “monitoring target ID” and “NG” is set as the “status” in the information whose “item number” is “3”. Has been. Description of other information included in FIG.

  Returning to FIG. 24, the abnormality presence / absence determination unit 113 refers to the state information 133 stored in the information storage area 130 (the state information 133 acquired in the process of S82), and determines whether or not there is a monitoring target having an abnormality. Determine (S83).

  As a result, when it is determined that there is no monitoring target determined to be abnormal (NO in S84), the state acquisition unit 114 performs the processing subsequent to S81 again.

  On the other hand, when it is determined that there is a monitoring target determined to be abnormal (YES in S84), the execution instruction unit 115 corresponds to the monitoring target determined to be abnormal for each of the one or more API servers. API to be transmitted is transmitted (S85).

  Thereafter, the execution instruction unit 115 waits until execution of the predetermined process corresponding to the API transmitted in the process of S85 is completed (NO in S86).

  When the execution of the predetermined process corresponding to the API transmitted in the process of S85 is completed (YES in S86), the execution instruction unit 115 displays the result of the predetermined process that has been executed as shown in FIG. The API result information 135 shown is generated (S91). Thereafter, the execution instruction unit 115 stores the generated API result information 135 in the information storage area 130, for example. Hereinafter, a specific example of the API result information 135 generated in the process of S91 will be described.

[Specific example of API result information (2)]
FIG. 28 is a diagram for describing a specific example of the API result information 135 and the state information 133. Specifically, FIG. 28A is a diagram for describing a specific example of the API result information 135.

  In the API result information 135 (hereinafter also referred to as API result information 135d2) shown in FIG. 27A, “023” is set as “APIID” in the information whose “item number” is “1”, and “execute” “OK” is set as the “result”.

  That is, in the status information 133d2 described with reference to FIG. 28B, the “status” of the information whose “item number” is “3” (information whose “monitoring target ID” is “3”) is “NG”. Is set. In the correspondence information 132d described with reference to FIG. 26, “023” is set in “APIID” of information in which “3” is set in “monitoring target ID”. Therefore, the execution instruction unit 115 transmits an API whose “APIID” is “3” in the process of S85. Then, the execution instruction unit 115 generates API result information 135d2 shown in FIG.

  Returning to FIG. 25, the abnormality presence / absence determination unit 113 refers to the API result information 135 stored in the information storage area 130, and determines whether or not there is an API having an abnormality in the execution result (S92).

  As a result, when it is determined that there is an API determined to have an execution abnormality (YES in S92), the result output unit 115 determines the presence / absence of abnormality of each monitoring target in the process of S84 and the API in the process of S92. And the information indicating that the degree of abnormality detected in the process of S92 is a third abnormality (for example, an abnormality having an urgency level of “high”) (S93). ).

  Specifically, the result output unit 115 detects, for example, the determination result of abnormality of each monitoring target in the process of S84, the determination result of abnormality of the execution result of the API in the process of S92, and the process of S92. The notification information 134 is generated from the information indicating that the degree of abnormality is the third abnormality, and the generated notification information 134 is output to the supervisor terminal 1a.

  On the other hand, if it is determined that there is no API that has been determined to have an execution abnormality (NO in S92), the result output unit 115 determines the presence / absence of abnormality of each monitoring target in the process of S84, and the API in the process of S92. And the information indicating that the degree of abnormality detected in the process of S92 is a fourth abnormality (for example, an abnormality having an urgency of “low”) (S94). ).

  Specifically, the result output unit 115 detects, for example, the determination result of abnormality of each monitoring target in the process of S84, the determination result of abnormality of the execution result of the API in the process of S92, and the process of S92. Notification information 134 is generated from information indicating that the degree of abnormality is the fourth abnormality, and the generated notification information 134 is output to the supervisor terminal 1a.

  Thereby, when an abnormality is detected in the monitoring target (for example, the hypervisor 2c) of the cloud operator, the monitoring device 1 takes into account the execution result of the API transmitted to each monitoring target and detects the detected abnormality. It becomes possible to output information related to the. Therefore, the monitoring device 1 can output information according to the degree of the influence (impact on the resource of the service provider) caused by the abnormality in the monitoring target of the cloud provider. Therefore, the cloud provider can take measures according to the degree of influence on the resource of the service provider by referring to the information output by the monitoring device 1.

[Specific example of notification information (2)]
Next, a specific example of the notification information 134 (hereinafter also referred to as notification information 134b) in the second embodiment will be described. FIG. 29 is a diagram illustrating the notification information 134 according to the second embodiment.

  The result output unit 115 determines that there is an abnormality in the execution result of the API for performing the “virtual NW list display” in the processing of S71, and the error message included in the API response is “error 503”. 29, for example, “virtual NW list display” is set as “target resource” of information whose “item number” is “1”, and “error 503” is set as “message”. To do. Further, when the status output 133 is acquired from the controller (1) and the load distribution server (2) in the process of S72, the result output unit 115 sets “controller (1)” as “suspected location”, for example. Further, the result output unit 115, when “controller (1)” is set in “suspected place”, for example, when “controller (1)” is set in “suspected place” as “estimated abnormal state” “Virtual NW controller process down”, which is information (predetermined information) corresponding to is set. Further, the result output unit 115, when “controller (1)” is set to “suspected place”, for example, when “controller (1)” is set to “suspected place” as “estimated influence range” Information (predetermined information) indicating a list of APIs corresponding to is set. Further, when “virtual NW list display” is set in “target resource”, the result output unit 115 sets “high” as the “emergency level”, for example.

  If the result output unit 115 determines that the process down has occurred in the API server (1) in the process of S84, for example, as shown in FIG. 29, the “item number” is “4”. “API server (1)” is set as “target resource” of certain information, and “process down” is set as “message”. Further, when “API server (1)” is set in “target resource”, for example, the result output unit 115 sets “API server (1)” as “suspected location”. The result output unit 115 also displays information corresponding to a case where “process down” is set in “message”, for example, “process down” is set in “message” as “estimated abnormal state” (in advance). Set “Process Down”, which is defined information). In addition, when only “API server (1)” is set in the “suspected place”, the result output unit 115 sets “probable influence range” of information whose “item number” is “1”, for example, “None” which is information (predetermined information) corresponding to the case where only “API server (1)” is set in “location” is set. Further, when “none” is set in the “estimated influence range”, the result output unit 115 sets “low” as the “emergency level”, for example.

  As described above, the monitoring device 1 according to the present embodiment arranges the monitoring VM 2b used for monitoring a plurality of monitoring targets including the hypervisor 2c on the hypervisor 2c, for example.

  Then, the monitoring device 1 acquires a result of a predetermined test executed by the monitoring VM 2b at a predetermined interval, and determines whether there is an abnormality in the monitoring VM 2b from the acquired result. As a result, when the monitoring VM 2b is abnormal, the monitoring device 1 acquires a predetermined state of the plurality of monitoring targets, and obtains a determination result of whether or not the monitoring VM 2b is abnormal and a predetermined state of the plurality of monitoring targets. Output.

  That is, the monitoring device 1 according to the present embodiment arranges the monitoring VM 2b that can be accessed by the monitoring device 1 on the hypervisor 2c that operates the user VM 2a lent to the service provider, for example. Then, the monitoring device 1 estimates the operation state acquired by accessing the monitoring VM as the operation state of the user VM 2a (virtual machine that cannot be accessed by the monitoring device 1).

  Thus, for example, when the monitoring device 1 detects an abnormality that has occurred in the hypervisor 2c, the monitoring device 1 refers to the operation state acquired from the monitoring VM 2b, thereby determining the degree of influence that the generated abnormality has on the user VM 2a. It becomes possible to estimate. The monitoring device 1 can also detect an abnormality (abnormality caused by the hypervisor 2c) that cannot be detected by the hypervisor 2c, for example, by referring to the operation state acquired from the monitoring VM 2a. .

  The above embodiment is summarized as follows.

(Appendix 1)
On the virtualization software, a monitoring virtual machine used for monitoring a plurality of monitoring targets including the virtualization software is arranged,
Obtaining a result of a predetermined test executed by the virtual machine at a predetermined interval;
Determine whether the virtual machine is abnormal from the acquired results,
If the virtual machine is abnormal, obtain a predetermined state of the plurality of monitoring targets,
Outputting a determination result of whether or not there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring program for causing a computer to execute processing.

(Appendix 2)
In Appendix 1,
Obtaining a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
Determining the presence or absence of abnormalities of the plurality of monitoring targets from each of the acquired predetermined states;
If any of the monitoring targets is abnormal, obtain the result of the virtual machine;
Determining whether the virtual machine is abnormal from the acquired result;
Let the computer execute the process,
In the output process, when the virtual machine is abnormal, information indicating that the abnormality of any one of the monitoring targets is a first abnormality is output, and when the virtual machine is not abnormal, any of the monitoring is performed. Outputting information indicating that the target abnormality is the second abnormality;
A monitoring program characterized by that.

(Appendix 3)
In Appendix 1,
The predetermined test includes a test involving access to a storage area for monitoring by the virtual machine,
The plurality of monitoring targets include a storage device having the storage area,
In the process of determining whether or not there is an abnormality, it is determined whether or not there is an abnormality in the virtual machine or the storage area,
In the process of acquiring the predetermined state, when the virtual machine or the storage area is abnormal, the predetermined state of the storage device is acquired,
In the process of outputting, the determination result of the presence or absence of abnormality of the virtual machine or the storage area and a predetermined state of the storage device are output.
A monitoring program characterized by that.

(Appendix 4)
In Appendix 1,
The predetermined test is a test for determining whether or not there is a response from the virtual machine,
The plurality of monitoring targets include a network device through which communication with the virtual machine is performed,
In the process of determining whether there is an abnormality, it is determined whether there is a response from the virtual machine,
In the process of acquiring the predetermined state, when there is no response from the virtual machine, the predetermined state of the network device is acquired,
In the output process, the determination result of the presence or absence of a response from the virtual machine and a predetermined state of the network device are output.
A monitoring program characterized by that.

(Appendix 5)
In Appendix 1,
The plurality of monitoring targets include a plurality of information processing apparatuses that respectively execute a plurality of processes,
Instructing the plurality of information processing devices to execute the plurality of processes at a predetermined interval,
From the execution results of the plurality of processes corresponding to the execution instruction, determine whether there is an abnormality in the execution results of the plurality of processes, respectively.
When an execution result of at least one of the plurality of processes is abnormal, a predetermined state of the monitoring target corresponding to any one of the plurality of monitoring targets is acquired,
Outputting the determination result of the presence or absence of abnormality of the execution results of the plurality of processes and a predetermined state of the monitoring target corresponding to any of the processes;
A monitoring program for causing a computer to execute processing.

(Appendix 6)
In Appendix 5,
The plurality of processes include virtual machine creation and virtual machine deletion,
A monitoring program characterized by that.

(Appendix 7)
In Appendix 5,
Obtaining a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
Determining the presence or absence of each of the plurality of monitoring targets from each of the acquired predetermined states;
If any one of the plurality of monitoring targets is abnormal, an instruction to execute the processing corresponding to any one of the plurality of processing targets is given to the plurality of information processing apparatuses. ,
From the execution result of the process corresponding to any one of the monitoring targets, determine whether there is an abnormality in the execution result of the process corresponding to any of the monitoring targets,
Let the computer execute the process,
In the process of outputting the determination result of the presence / absence of abnormality of the execution results of the plurality of processes, if the execution result of at least one of the processes corresponding to any of the monitoring targets is abnormal, any of the above Information indicating that the monitoring target abnormality is the third abnormality, and if the execution result of the process corresponding to any of the monitoring targets is not abnormal, the monitoring target abnormality is the fourth abnormality Output information indicating that it is,
A monitoring program for causing a computer to execute processing.

(Appendix 8)
A virtual machine placement unit for placing a virtual machine for monitoring used for monitoring a plurality of monitoring targets including the virtualization software on the virtualization software;
A test result acquisition unit for acquiring a result of a predetermined test executed by the virtual machine at a predetermined interval;
An abnormality presence / absence determining unit that determines the presence / absence of an abnormality of the virtual machine from the acquired result;
When the virtual machine is abnormal, a state acquisition unit that acquires a predetermined state of the plurality of monitoring targets;
A result output unit that outputs a determination result of whether there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring device characterized by that.

(Appendix 9)
In Appendix 8,
The state acquisition unit acquires a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
The abnormality presence / absence determination unit determines the presence / absence of abnormality of the plurality of monitoring targets from each of the acquired predetermined states,
The test result acquisition unit acquires the result of the virtual machine when any of the monitoring targets is abnormal,
The abnormality presence / absence determining unit determines whether the virtual machine is abnormal from the acquired result,
When the virtual machine is abnormal, the result output unit outputs information indicating that one of the monitoring target abnormalities is a first abnormality, and when the virtual machine is not abnormal, any of the monitoring is performed. Outputting information indicating that the target abnormality is the second abnormality;
A monitoring device characterized by that.

(Appendix 10)
On the virtualization software, a monitoring virtual machine used for monitoring a plurality of monitoring targets including the virtualization software is arranged,
Obtaining a result of a predetermined test executed by the virtual machine at a predetermined interval;
Determine whether the virtual machine is abnormal from the acquired results,
If the virtual machine is abnormal, obtain a predetermined state of the plurality of monitoring targets,
Outputting a determination result of whether or not there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring method characterized by that.

(Appendix 11)
In Appendix 10,
Obtaining a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
Determining the presence or absence of abnormalities of the plurality of monitoring targets from each of the acquired predetermined states;
If any of the monitoring targets is abnormal, obtain the result of the virtual machine;
Determine whether the virtual machine is abnormal from the acquired results,
In the outputting step, when the virtual machine is abnormal, information indicating that any one of the monitoring target abnormalities is a first abnormality is output, and when the virtual machine is not abnormal, any of the monitoring is performed. Outputting information indicating that the target abnormality is the second abnormality;
A monitoring method characterized by that.

1: monitoring device 1a: supervisor terminal 2: physical machine 2a: user VM
2c: Hypervisor 3: Storage device 4: API server 5: Network device

Claims (9)

On the virtualization software, a monitoring virtual machine used for monitoring a plurality of monitoring targets including the virtualization software is arranged,
Obtaining a result of a predetermined test executed by the virtual machine at a predetermined interval;
Determine whether the virtual machine is abnormal from the acquired results,
If the virtual machine is abnormal, obtain a predetermined state of the plurality of monitoring targets,
Outputting a determination result of whether or not there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring program for causing a computer to execute processing. The claim 1, further comprising:
Obtaining a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
Determining the presence or absence of abnormalities of the plurality of monitoring targets from each of the acquired predetermined states;
If any of the monitoring targets is abnormal, obtain the result of the virtual machine;
Determining whether the virtual machine is abnormal from the acquired result;
Let the computer execute the process,
In the output process, when the virtual machine is abnormal, information indicating that the abnormality of any one of the monitoring targets is a first abnormality is output, and when the virtual machine is not abnormal, any of the monitoring is performed. Outputting information indicating that the target abnormality is the second abnormality;
A monitoring program characterized by that. In claim 1,
The predetermined test includes a test involving access to a storage area for monitoring by the virtual machine,
The plurality of monitoring targets include a storage device having the storage area,
In the process of determining the presence / absence of abnormality, it is determined whether there is an abnormality in the virtual machine or the storage area,
In the process of acquiring the predetermined state, when the virtual machine or the storage area is abnormal, the predetermined state of the storage device is acquired,
In the process of outputting, the determination result of the presence or absence of abnormality of the virtual machine or the storage area and a predetermined state of the storage device are output.
A monitoring program characterized by that. In claim 1,
The predetermined test is a test for determining whether or not there is a response from the virtual machine,
The plurality of monitoring targets include a network device through which communication with the virtual machine is performed,
In the process of determining whether there is an abnormality, it is determined whether there is a response from the virtual machine,
In the process of acquiring the predetermined state, when there is no response from the virtual machine, the predetermined state of the network device is acquired,
In the output process, the determination result of the presence or absence of a response from the virtual machine and a predetermined state of the network device are output.
A monitoring program characterized by that. The claim 1, further comprising:
The plurality of monitoring targets include a plurality of information processing apparatuses that respectively execute a plurality of processes,
Instructing the plurality of information processing devices to execute the plurality of processes at a predetermined interval,
From the execution results of the plurality of processes corresponding to the execution instruction, determine whether there is an abnormality in the execution results of the plurality of processes, respectively.
When an execution result of at least one of the plurality of processes is abnormal, a predetermined state of the monitoring target corresponding to any one of the plurality of monitoring targets is acquired,
Outputting the determination result of the presence or absence of abnormality of the execution results of the plurality of processes and a predetermined state of the monitoring target corresponding to any of the processes;
A monitoring program for causing a computer to execute processing. In claim 5,
The plurality of processes include virtual machine creation and virtual machine deletion,
A monitoring program characterized by that. In claim 5, further:
Obtaining a predetermined state of each of the plurality of monitoring targets at a predetermined interval,
Determining the presence or absence of each of the plurality of monitoring targets from each of the acquired predetermined states;
If any one of the plurality of monitoring targets is abnormal, an instruction to execute the processing corresponding to any one of the plurality of processing targets is given to the plurality of information processing apparatuses. ,
From the execution result of the process corresponding to any one of the monitoring targets, determine whether there is an abnormality in the execution result of the process corresponding to any of the monitoring targets,
Let the computer execute the process,
In the process of outputting the determination result of the presence / absence of abnormality of the execution results of the plurality of processes, if the execution result of at least one of the processes corresponding to any of the monitoring targets is abnormal, any of the above Information indicating that the monitoring target abnormality is the third abnormality, and if the execution result of the process corresponding to any of the monitoring targets is not abnormal, the monitoring target abnormality is the fourth abnormality Output information indicating that it is,
A monitoring program for causing a computer to execute processing. A virtual machine placement unit for placing a virtual machine for monitoring used for monitoring a plurality of monitoring targets including the virtualization software on the virtualization software;
A test result acquisition unit for acquiring a result of a predetermined test executed by the virtual machine at a predetermined interval;
An abnormality presence / absence determining unit that determines the presence / absence of an abnormality of the virtual machine from the acquired result;
When the virtual machine is abnormal, a state acquisition unit that acquires a predetermined state of the plurality of monitoring targets;
A result output unit that outputs a determination result of whether there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring device characterized by that. On the virtualization software, a monitoring virtual machine used for monitoring a plurality of monitoring targets including the virtualization software is arranged,
Obtaining a result of a predetermined test executed by the virtual machine at a predetermined interval;
Determine whether the virtual machine is abnormal from the acquired results,
If the virtual machine is abnormal, obtain a predetermined state of the plurality of monitoring targets,
Outputting a determination result of whether or not there is an abnormality in the virtual machine and a predetermined state of the plurality of monitoring targets;
A monitoring method characterized by that.

Images