Monitoring optimization system, setting method, and program

Abstract

SOLUTION: A user input acquisition unit configured to acquire user input indicating a user's desire to change a setting of a monitoring setting to be changed among a plurality of monitoring settings set for a monitoring tool, a setting data acquisition unit configured to acquire setting data set for a plurality of monitoring setting items of the monitoring setting, a related function information acquisition unit configured to acquire related function information that is information about functions related to the plurality of monitoring setting items of the monitoring setting and the user input, and a setting data acquisition unit configured to input the related function information, the user input, and the setting data to a generation AI; A mediation unit that mediates a dialogue between the generation AI and the user until a setting change proposal of the monitoring setting for which it is determined that the generation AI satisfies the change request is generated by the generation AI, and presents the setting change proposal to the user in response to acquisition of the setting change proposal from the generation AI, and a setting unit that changes a setting of the monitoring setting of the monitoring tool according to the setting change proposal in accordance with an instruction from the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a monitoring optimization system, a setting method, and a program. [Background technology]

[0002] Patent Document 1 describes an OSS (Open Source Software) monitoring tool called Zabbix (registered trademark) and an OSS monitoring tool called Prometheus (registered trademark). [Prior art document] [Patent Documents] [Patent Document 1] JP 2021-069009 Summary of the Invention [Means for solving the problem]

[0003] According to one embodiment of the present invention, a monitoring optimization system is provided. The monitoring optimization system may include a user input acquisition unit that acquires user input indicating a user's desired change to a monitoring setting that is a target for change among multiple monitoring settings configured for a monitoring tool. The monitoring optimization system may include a setting data acquisition unit that acquires setting data configured for multiple monitoring setting items of the monitoring setting. The monitoring optimization system may include an intermediary unit that inputs associated function information, which is information on functions related to the multiple monitoring setting items of the monitoring setting, the user input, and the setting data to a generation AI, mediates a dialogue between the generation AI and the user until the generation AI generates a setting change proposal for the monitoring setting item that the generation AI determines satisfies the desired change, and presents the setting change proposal to the user upon receiving the setting change proposal from the generation AI. The monitoring optimization system may include a setting unit that changes the monitoring setting of the monitoring tool in accordance with the setting change proposal in response to an instruction from the user.

[0004] In the monitoring optimization system, the associated function information may include information on all functions required to set the plurality of monitoring setting items.

[0005] Any of the monitoring optimization systems may include an associated function information storage unit that stores a plurality of associated function information corresponding to a plurality of monitoring setting items, and the intermediary unit may select, from the plurality of associated function information, the associated function information that corresponds to the plurality of monitoring setting items of the monitoring setting that is the target of setting change, and input the selected associated function information, the user input, and the setting data to the generation AI.

[0006] Any of the monitoring optimization systems may include an interaction history memory unit that stores an interaction history between the generation AI and the user, and the intermediary unit may input the interaction history to the generation AI in addition to the user input, the setting data, and the related function information.

[0007] In any of the monitoring optimization systems described above, the intermediary unit may present the setting change proposal to the user in such a way that differences from the setting data acquired by the setting data acquisition unit can be identified.

[0008] In any of the monitoring optimization systems, the intermediary unit may obtain from the generation AI the proposed setting change and explanatory data that explains the changes to the proposed setting change in natural language, and present the proposed setting change and the explanatory data to the user.

[0009] In any of the monitoring optimization systems, the intermediary unit may input to the generation AI, in addition to the associated function information, the user input, and the setting data, a system setting indicating that the monitoring setting of the monitoring tool will be changed using the API of the monitoring tool as a setting change AI of the monitoring optimization system.

[0010] In any of the monitoring optimization systems, when the setting unit changes the monitoring settings of the monitoring tool in accordance with the setting change proposal, it may store the setting data of the monitoring settings before the change as a backup, and after the monitoring settings are changed, restore the monitoring settings using the setting data stored as a backup in accordance with instructions from the user.

[0011] In any of the above monitoring optimization systems, the user input acquisition unit may acquire the user input for each of the multiple monitoring settings designated by the user as targets for setting change, from among the multiple monitoring settings set for the monitoring tool, the setting data acquisition unit may acquire setting data set for each of the multiple monitoring settings targeted for setting change, the intermediation unit may input the multiple pieces of related function information, the multiple pieces of setting data, and the multiple user inputs corresponding to the multiple monitoring settings targeted for setting change to the generation AI, and mediate a dialogue between the generation AI and the user until the generation AI generates a setting change proposal for the monitoring setting that satisfies the change request for each of the multiple monitoring settings, and may present the multiple setting change proposals to the user in response to obtaining the multiple setting change proposals from the generation AI, and the setting unit may change the settings of the multiple monitoring settings of the monitoring tool in accordance with the multiple setting change proposals in response to instructions from the user.

[0012] In any of the above monitoring optimization systems, the user input acquisition unit may acquire user input indicating the user's setting preferences for new monitoring settings to be newly set for the monitoring tool, the intermediation unit may input the user input and associated function information, which is information on functions related to multiple monitoring setting items of the new monitoring setting, to the generation AI, and mediate interactions between the generation AI and the user until the generation AI generates a setting proposal for the new monitoring setting that the generation AI determines satisfies the setting preferences, and may present the setting proposal to the user upon obtaining the setting proposal from the generation AI, and the setting unit may configure the new monitoring setting of the monitoring tool in accordance with the setting proposal in response to instructions from the user.

[0013] According to one embodiment of the present invention, a computer-executable setting method is provided. The setting method may include a user input acquisition step of acquiring a user input indicating a user's desired change to a monitoring setting to be changed, among multiple monitoring settings configured for a monitoring tool. The setting method may include a setting data acquisition step of acquiring setting data configured for multiple monitoring setting items of the monitoring setting. The setting method may include an intermediation step of inputting associated function information, which is information on functions related to the multiple monitoring setting items of the monitoring setting, the user input, and the setting data into a generation AI, mediating a dialogue between the generation AI and the user until the generation AI generates a setting change proposal for the monitoring setting that satisfies the desired change, and presenting the setting change proposal to the user in response to receiving the setting change proposal from the generation AI. The setting method may include a setting step of changing the monitoring setting of the monitoring tool in accordance with the setting change proposal in response to an instruction from the user.

[0014] According to one embodiment of the present invention, there is provided a program for causing a computer to execute the setting method.

[0015] The above summary of the invention does not list all of the necessary features of the present invention, and subcombinations of these features may also constitute inventions. [Brief explanation of the drawings]

[0016] [Figure 1] 1 illustrates a schematic diagram of an example surveillance optimization system 100. [Figure 2] 10 shows an example of a processing flow by the monitoring optimization system 100. [Figure 3] An example 150 of the Function Calling settings is shown below. [Figure 4] 1 shows an example input 160 from the monitoring optimization system 100 to the generated AI 400. [Figure 5] 1 shows an example of a functional configuration of a monitoring optimization system 100. [Figure 6] 10 is a schematic diagram showing an example 170 of proposed settings changes presented by the intermediary unit 138. [Figure 7] 10 shows an example of a processing flow by the monitoring optimization system 100. [Figure 8] 1 shows an example of a hardware configuration of a computer 1200 that functions as the monitoring optimization system 100. DETAILED DESCRIPTION OF THE INVENTION

[0017] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0018] Zabbix and Prometheus are known monitoring tools that monitor any system (such as a server, network, or application). To optimize monitoring using such monitoring tools, monitoring optimization systems are used to configure the monitoring tools. Registering monitoring settings using such monitoring optimization systems requires knowledge of the monitoring tool and the system it monitors, which is currently difficult for anyone other than an expert. The monitoring optimization system 100 according to this embodiment uses a generative AI to enable interactive configuration of the monitoring tool. This allows the person in charge of configuration to efficiently implement and change the monitoring settings. This also contributes to reducing problems such as the mandatory knowledge of the monitoring tool, the dependency on individual configuration details, input errors caused by differences in notation between departments, and human error in entering monitoring settings.

[0019] 1 shows an example of a monitoring optimization system 100. The monitoring optimization system 100 is a system that performs settings for a monitoring tool 200. The monitoring tool 200 is a tool that monitors a target system 300, which is a system to be monitored.

[0020] The monitoring optimization system 100 and the monitoring tool 200 may communicate via a network 20. The monitoring tool 200 and the target system 300 may communicate via a network 20. The network 20 may include a cloud. The network 20 may include the Internet. The network 20 may include a mobile communication network. The network 20 may include a LAN (Local Area Network).

[0021] The monitoring tool 200 may be open source software. However, it is not essential that the monitoring tool 200 be open source software, and the monitoring tool 200 may be closed source software.

[0022] The monitoring tool 200 is, for example, Zabbix. The monitoring tool 200 may be Prometheus. The monitoring tool 200 may be Datadog (registered trademark). The monitoring tool 200 may be Mackerel (registered trademark). The monitoring tool 200 may be NewRelic (registered trademark). The monitoring tool 200 may be Dynatrace (registered trademark). The monitoring tool 200 may be Instana. The monitoring tool 200 may be a system other than these that is known as a so-called monitoring tool. In this embodiment, a case where the monitoring tool 200 is Zabbix will be mainly described as an example.

[0023] The target system 300 may be any system that can be monitored by the monitoring tool 200. The target system 300 may be a server that provides any service, a virtual server, a network device, an application, or the like.

[0024] The monitoring optimization system 100 may perform settings, etc. for one monitoring tool 200. The monitoring optimization system 100 may perform settings, etc. for multiple monitoring tools 200.

[0025] The monitoring optimization system 100 configures the monitoring tool 200 in accordance with instructions from the user 102. If the user 102 has sufficient knowledge about the target system 300 and the monitoring tool 200, the user 102 can configure the monitoring tool 200 at his or her own discretion. However, for a user 102 with insufficient knowledge about at least one of the target system 300 and the monitoring tool 200, configuring the monitoring tool 200 may be difficult. Furthermore, for example, there are many cases in which a user 102 with sufficient knowledge about the target system 300 and the monitoring tool 200 configures the monitoring tool 200, and then another user 102 must change the configuration. However, if the other user 102 does not have sufficient knowledge, it is difficult for the other user 102 to appropriately change the configuration of the monitoring tool 200. This can result in problems such as a very heavy burden for configuration and configuration changes, or limited personnel available to perform configuration and configuration changes.

[0026] In contrast, the monitoring optimization system 100 has the functionality to allow the user 102 to interactively configure the monitoring tool 200 using the generated AI 400 .

[0027] The generated AI 400 may be a Large Language Model (LLM). The generated AI 400 may be, for example, ChatGPT (registered trademark). The generated AI 400 may be Bard. The generated AI 400 may be Gemini. The generated AI 400 may be Copilot. The generated AI 400 may be Claude (registered trademark). The generated AI 400 may be a generated AI other than these that is known as an interactive generated AI. Note that the generated AI 400 may be one generated for the monitoring optimization system 100. In this embodiment, a case where the generated AI 400 is ChatGPT will be mainly described as an example.

[0028] When the monitoring tool 200 is open source software, ChatGPT or the like has learned about the monitoring tool 200, and the monitoring optimization system 100 can use ChatGPT or the like to utilize a generated AI that has knowledge about the monitoring tool 200. In this way, the monitoring optimization system 100 according to this embodiment may directly utilize the generated AI 400 that has already learned about the monitoring tool 200, which is open source software. Note that the monitoring optimization system 100 may additionally learn knowledge about the monitoring tool 200 to the generated AI 400 that has already learned about the monitoring tool 200, which is open source software.

[0029] Even if the monitoring tool 200 is closed-source software, ChatGPT etc. has general knowledge about tools called monitoring tools, so the monitoring optimization system 100 may use ChatGPT etc. as is. The monitoring optimization system 100 may also make the monitoring tool 200 learn knowledge about closed-source software and use it.

[0030] The monitoring optimization system 100 supports, for example, using the generation AI 400, the user 102 changing the monitoring settings set in the monitoring tool 200. A plurality of monitoring settings are set in the monitoring tool 200. A monitoring setting for each target system 300 may be set in the monitoring tool 200. A plurality of monitoring settings may be set in the monitoring tool 200 for each target system 300.

[0031] The monitoring settings may include a plurality of monitoring setting items, such as a monitoring target, settings for data to be acquired from the monitoring target, and a trigger indicating a data condition for issuing an alert.

[0032] The monitoring target indicates the target system 300 to be monitored. The monitoring target may be referred to as a host. Settings for data acquired from the monitoring target include, for example, CPU usage, memory usage, and various logs. Settings for data acquired from the monitoring target may be referred to as an item. The trigger includes settings for the item, such as the conditions under which an alarm is to be issued (e.g., issuing an alarm when the condition is 90% or higher). The trigger may include various settings, such as the conditions under which an alarm is to be issued and the level of importance at which the alarm is issued. Examples of trigger setting values ​​include a trigger name indicating the name under which the alarm is issued, a conditional expression indicating the conditions under which the alarm is issued, a conditional expression indicating the conditions under which recovery is required, and the level of importance indicating the level of urgency of the failure for which alarm (whether an email should be sent or a phone call should be received, etc.).

[0033] The surveillance optimization system 100 provides various inputs to the generated AI 400 to support changes to the surveillance settings by the user 102 .

[0034] The monitoring optimization system 100 may input system settings to the generation AI 400. The system settings may include content indicating that the setting change AI of the monitoring optimization system 100 uses the API of the monitoring tool 200 to change the monitoring settings of the monitoring tool 200. The system settings may include content indicating that a monitoring setting change function is to be called with parameters according to the changes desired by the user 102. The system settings may include naming conventions such as a system name. The system settings may also include unique information such as unique rules. The system settings may include content indicating that, if there is missing information about the monitoring setting change, the missing information is to be obtained by interacting with the user 102. By the monitoring optimization system 100 inputting the system settings to the generation AI 400, the generation AI 400 can change the monitoring settings of the monitoring tool 200 while interacting with the user 102.

[0035] The monitoring optimization system 100 may input related function information, which is information on functions related to multiple monitoring setting items included in a monitoring setting to be changed, among multiple monitoring settings configured for the monitoring tool 200, to the generation AI 400. The function related information may include information on all functions required to set multiple monitoring setting items included in the corresponding monitoring setting. The function related information may include a description of each function. The description may include how to use the function. The function related information may include a setting example for each function. If the generation AI 400 is ChatGPT, the function related information may be an example of a function used in function calling and how to use it. By the monitoring optimization system 100 inputting the related function information to the generation AI 400, the generation AI 400 can identify functions that need to be set for the monitoring setting item to be changed, making it easier for the generation AI 400 to generate an appropriate design change proposal for the monitoring setting item.

[0036] The monitoring optimization system 100 inputs user input, entered by the user 102, indicating the changes desired by the user 102 into the generating AI 400.

[0037] The monitoring optimization system 100 may input a history of interactions with the user 102 to the generated AI 400. The monitoring optimization system 100 may store a history of interactions between the user 102 and the generated AI 400 and input the history to the generated AI 400. This may allow the generated AI 400 to execute interactions that reflect past interactions with the user 102.

[0038] The monitoring optimization system 100 may input current setting data of the monitoring setting to be changed to the generation AI 400. This allows the generation AI 400 to understand the current setting of the monitoring setting to be changed, making it easier for the generation AI 400 to generate a design change proposal for the monitoring setting.

[0039] 2 shows an example of a processing flow by the monitoring optimization system 100. The inputs and outputs in the example shown in FIG.

[0040] The monitoring optimization system 100 acquires, for example, a user input indicating that "I want to change the importance" for a monitoring setting specified by the user 102 from among multiple monitoring settings configured in a monitoring tool. The monitoring optimization system 100 inputs the system settings, the current setting data for the monitoring setting specified by the user 102, the user input, the dialogue history, and function-related information to be called by Function Calling to the generation AI 400. The monitoring optimization system 100 may input the function-related information corresponding to the monitoring setting specified by the user 102. FIG. 3 shows a setting example 150 of Function Calling. The monitoring optimization system 100 may set Function Calling in a format as exemplified in FIG. 3. FIG. 4 shows an input example 160 from the monitoring optimization system 100 to the generation AI 400. The monitoring optimization system 100 may input to the generation AI 400 in a format as exemplified in FIG. 4.

[0041] The generation AI 400 generates a setting change proposal in accordance with input from the monitoring optimization system 100. When the necessary information is available, the generation AI 400 uses that information to generate a setting change proposal. When the necessary information is not available, the generation AI 400 engages in a dialogue with the user 102 to obtain the missing information. In the example shown in FIG. 2 , the generation AI 400 outputs a message, “What settings do you want?” to the monitoring optimization system 100. The monitoring optimization system 100 presents the message acquired from the generation AI 400 to the user 102. The user 102 replies to the message presented by the monitoring optimization system 100. In this example, the user 102 replies, “Set it to the warning zone.” The monitoring optimization system 100 inputs the user 102’s reply to the generation AI 400. When the necessary information is available, the generation AI 400 generates a setting change proposal and outputs it to the monitoring optimization system 100. In the example shown in FIG. 2, a setting change proposal to set Priority to 3 is output.

[0042] After checking the setting change proposal displayed by the monitoring optimization system 100, if the user 102 is satisfied with the contents, the user 102 instructs the monitoring optimization system 100 to reflect the changes in the monitoring tool 200. The monitoring optimization system 100 changes the target monitoring setting of the monitoring tool 200 in accordance with the instruction.

[0043] 5 shows an example of the functional configuration of the monitoring optimization system 100. The monitoring optimization system 100 includes a storage unit 110, a registration unit 120, and a processing unit .

[0044] The storage unit 110 stores various types of information. The storage unit 110 stores information registered by the registration unit 120. The storage unit 110 may include a function-related information storage unit 112. The storage unit 110 may include a dialogue history storage unit 114.

[0045] The registration unit 120 registers various types of information. The registration unit 120 may register information input by an administrator of the monitoring optimization system 100 or the like.

[0046] The registration unit 120 may register the function-related information. The function-related information registered by the registration unit 120 may be stored in the function-related information storage unit 112.

[0047] The registration unit 120 may register function-related information for multiple monitoring setting items for each of multiple monitoring settings of the monitoring tool 200. The types of monitoring setting items differ depending on the type of monitoring tool 200. For example, the types of monitoring setting items differ between Zabbix and Prometheus. For example, if the monitoring tool 200 is Zabbix, the registration unit 120 registers function-related information for each of multiple monitoring setting items of Zabbix. For example, if the monitoring tool 200 is Prometheus, the registration unit 120 registers function-related information for each of multiple monitoring setting items of Prometheus.

[0048] The processing unit 130 executes various processes. For example, the processing unit 130 sets the monitoring settings of the monitoring tool 200 according to instructions from the user 102. The processing unit 130 sets the data required for each monitoring setting according to instructions from the user 102. There are various types of monitoring settings depending on the type of monitoring tool 200. As a specific example, the processing unit 130 sets the monitoring settings related to the memory usage rate of the target system 300 to output an alarm when the memory usage rate exceeds a threshold, set the importance level to a warning level, and so on.

[0049] The processing unit 130 changes the monitoring settings of the monitoring tool 200, for example, in accordance with an instruction from the user 102. For example, the processing unit 130 presents to the user 102 setting data for multiple monitoring setting items of the monitoring setting specified by the user 102 from among multiple monitoring settings. The user 102 instructs the presented setting data to change the settings, and the processing unit 130 changes the settings in accordance with the instruction.

[0050] The processing unit 130 may have a function for searching for monitoring settings. For example, the processing unit 130 may display a list of monitoring settings that match search conditions specified by the user 102, from among multiple monitoring settings.

[0051] The processing unit 130 according to this embodiment uses the generated AI 400 to execute processing to support changes to the monitoring settings by the user 102. The processing unit 130 may include a monitoring setting identification unit 132, a user input acquisition unit 134, a setting data acquisition unit 136, an intermediation unit 138, and a setting unit 140. It is not essential that the processing unit 130 include all of these units.

[0052] The monitoring setting identification unit 132 identifies a monitoring setting to be changed from among multiple monitoring settings set for the monitoring tool 200. For example, the monitoring setting identification unit 132 identifies, from among the multiple monitoring settings, a monitoring setting specified by the user 102 as the setting to be changed. The method of accepting the designation by the user 102 is not particularly limited. For example, when the processing unit 130 presents the setting data of a monitoring setting specified by the user 102 from among the multiple monitoring settings to the user 102, it displays a button or the like for accepting an instruction for the monitoring setting using the generation AI 400, and identifies the monitoring setting as the setting to be changed in response to the button being selected. Alternatively, a list of multiple monitoring settings may be displayed, and the monitoring setting specified by the user 102 from among the listed multiple monitoring settings may be identified as the setting to be changed.

[0053] The user input acquiring unit 134 acquires a user input indicating a change desired by the user 102 for the monitoring setting to be changed. The user input acquiring unit 134 may acquire a user input indicating a change desired by the user 102 for the monitoring setting identified by the monitoring setting identifying unit 132. The user input may be text data. For example, the user input acquiring unit 134 acquires a user input entered into an input field for user input. The user input acquiring unit 134 may acquire the user input by recognizing a voice uttered by the user 102.

[0054] The setting data acquisition unit 136 acquires setting data set for the monitoring setting to be changed. The setting data acquisition unit 136 may acquire the setting data from the monitoring tool 200. The storage unit 110 may store setting data for multiple monitoring settings of the monitoring tool 200, and the setting data acquisition unit 136 may acquire the setting data from the storage unit 110.

[0055] The mediation unit 138 selects function-related information related to multiple monitoring setting items of the monitoring setting to be changed from the multiple pieces of function-related information stored in the function-related information storage unit 112, and inputs the selected function-related information, the user input acquired by the user input acquisition unit 134, and the setting data acquired by the setting data acquisition unit 136 to the generation AI 400. Note that the mediation unit 138 may input all of the multiple pieces of function-related information stored in the function-related information storage unit 112 to the generation AI 400. The mediation unit 138 may further input system settings to the generation AI 400.

[0056] After inputting information to the generation AI 400, the intermediation unit 138 mediates the dialogue between the generation AI 400 and the user 102 until the generation AI 400 generates proposed configuration changes for the monitoring settings that the generation AI 400 determines satisfy the change requests of the user 102. For example, if the generation AI 400 is able to generate proposed configuration changes based on input from the monitoring optimization system 100, it generates the proposed configuration changes and transmits them to the monitoring optimization system 100. However, if the generation AI 400 is unable to generate proposed configuration changes based on input from the monitoring optimization system 100, i.e., if information is insufficient to generate proposed configuration changes, it generates a message requesting the user 102 for the missing information. The intermediation unit 138 receives the message from the generation AI 400 and presents it to the user 102. The user 102 inputs a response to the presented message, and the monitoring optimization system 100 inputs the input response to the generation AI 400. This exchange continues until the generation AI 400 generates proposed configuration changes. In response to acquiring the proposed setting changes from the generated AI 400, the intermediation unit 138 presents the proposed setting changes to the user 102.

[0057] The mediation unit 138 may present the proposed setting changes to the user 102 so that differences from the setting data acquired by the setting data acquisition unit 136 can be distinguished. For example, the mediation unit 138 presents the proposed setting changes to the user 102 by emphasizing the differences from the setting data acquired by the setting data acquisition unit 136. For example, the mediation unit 138 presents the data before the setting change and the data after the setting change so that the data can be distinguished for the changed setting. The mediation unit 138 may present the data before the setting change so that the data can be distinguished as the data before the setting change, and may present the data after the setting change so that the data can be distinguished as the data after the setting change. As a specific example, the mediation unit 138 may present the data before the setting change and the data after the setting change with different background colors, or may present the data before the setting change and the data after the setting change with different colors, or may emphasize the data before the setting change less than the standard emphasis and emphasize the data after the setting change more than the standard emphasis. The mediation unit 138 may darken the color of the data as the emphasis level increases. The mediation unit 138 may apply a more conspicuous color to the data as the emphasis level increases. The mediation unit 138 may increase the size of the data as the emphasis level increases. The mediation unit 138 may also express differences in emphasis levels in other ways. These may reduce the possibility of erroneous setting changes being reflected, contributing to preventing false detections and inappropriate mass alerts.

[0058] FIG. 6 schematically illustrates an example 170 of proposed setting changes presented by the intermediary unit 138. In the example illustrated in FIG. 6, the background of the unchanged portion 171 is plain, and both the before-change portion 172 and the after-change portion 174 are presented, each with a different background. The before-change portion 172 is marked with a symbol 173 indicating the before-change, and the after-change portion 174 is marked with a symbol 175 indicating the after-change. In the example illustrated in FIG. 6, the background of the before-change portion 172 is darker than the background of the after-change portion 174, but the difference in display mode for distinguishing between the before-change portion and the after-change portion is not limited to this. For example, the intermediary unit 138 may make the background of the before-change portion 172 lighter than the background of the after-change portion 174. For example, the intermediary unit 138 may make the background of the before-change portion 172 and the background of the after-change portion 174 different colors. In the example shown in FIG. 6, the symbol 173 is "-" and the symbol 175 is "+", but this is not limited to this and other combinations may be used as long as different symbols are used before and after the change.

[0059] The intermediary unit 138 may acquire from the generation AI 400, in addition to the proposed setting changes, explanation data that explains the changes in the proposed setting changes in natural language. The intermediary unit 138 may cause the generation AI 400 to generate the explanation data by including in the system settings content indicating that explanation data explaining the changes in the proposed setting changes will be generated. The intermediary unit 138 may present the proposed setting changes and the explanation data to the user 102. This makes it easier for the user 102 to understand the changes, and reduces the possibility of erroneous setting changes being applied.

[0060] The setting unit 140 changes the monitoring settings of the monitoring tool 200 in accordance with the proposed setting changes in response to an instruction from the user 102. The setting unit 140 may change the settings of one or more monitoring setting items of the monitoring settings in accordance with the proposed setting changes. For example, the intermediary unit 138 presents the user 102 with, in addition to the proposed setting changes, an reflect button that accepts an instruction to reflect the proposed setting changes in the monitoring tool 200, and in response to the user 102 selecting the reflect button, the setting unit 140 changes the monitoring settings of the monitoring tool 200 in accordance with the proposed setting changes.

[0061] The setting unit 140 may store a backup of the setting change so that the state before the setting change can be restored. For example, when changing the monitoring setting of the monitoring tool 200 in accordance with the setting change proposal, the setting unit 140 stores the setting data of the monitoring setting before the change as a backup, and after changing the monitoring setting, restores the monitoring setting using the setting data stored as the backup in accordance with an instruction from the user 102. This makes it possible to immediately return to the state before the change if any problem occurs after the setting change.

[0062] The intermediary unit 138 may store a dialogue history with the user 102 in the dialogue history storage unit 114. The intermediary unit 138 may store a dialogue history for each user 102 in the dialogue history storage unit 114. The intermediary unit 138 may input the dialogue history with the user 102 to the generation AI 400 in addition to the function-related information, user input, and setting data. This may prevent a similar dialogue from continuing based on the history, for example, if there is a history of poor communication between the user 102 and the generation AI 400 in the past, resulting in a continued exchange of messages and replies that eventually led to communication. Furthermore, for example, if the user 102 has previously been forced to enter a large amount of user input, the amount of user input may be reduced based on the history, thereby reducing the burden on the user 102.

[0063] The processing unit 130 may change multiple monitoring settings in parallel. For example, the monitoring setting identification unit 132 accepts designation of multiple monitoring settings from among the multiple monitoring settings, the user input acquisition unit 134 acquires user input for each of the multiple monitoring settings identified by the monitoring setting identification unit 132, the setting data acquisition unit 136 acquires setting data set for each of the multiple monitoring settings identified by the monitoring setting identification unit 132, and the mediation unit 138 combines multiple pieces of related function information corresponding to multiple monitoring setting items of the multiple monitoring settings identified by the monitoring setting identification unit 132 with the multiple setting data acquired by the setting data acquisition unit 136. The generation AI 400 mediates dialogue between the generation AI 400 and the user 102 until the generation AI 400 generates a proposed monitoring setting change that satisfies the change request for each of the multiple monitoring settings identified by the monitoring setting identification unit 132, and presents the multiple proposed setting change to the user 102 in response to acquiring the multiple proposed setting change from the generation AI 400, and the setting unit 140 changes the multiple monitoring settings of the monitoring tool 200 in accordance with the multiple proposed setting change in response to instructions from the user 102. By making it possible to change multiple monitoring settings simultaneously, the efficiency of the change work by the user 102 can be improved.

[0064] The processing unit 130 according to this embodiment may use the generation AI 400 to execute processing to support the user 102 in setting new monitoring settings. For example, the monitoring setting identification unit 132 identifies a new monitoring setting to be set for the monitoring tool 200 (sometimes referred to as a new monitoring setting), the user input acquisition unit 134 acquires a user input indicating the user's 102 setting preferences for the new monitoring setting, the intermediation unit 138 inputs the user input and associated function information, which is information on functions associated with multiple monitoring setting items of the new monitoring setting, into the generation AI 400, and mediates interactions between the generation AI 400 and the user 102 until the generation AI 400 generates a setting proposal for a new monitoring setting that the generation AI 400 determines satisfies the setting preferences. In response to acquiring the setting proposal from the generation AI 400, the intermediation unit 138 presents the setting proposal to the user 102, and the setting unit 140 configures the new monitoring setting for the monitoring tool 200 in accordance with the setting proposal in response to an instruction from the user 102. By supporting not only changes to already set monitoring settings but also the setting of new monitoring settings, convenience for the user 102 can be further improved.

[0065] In the monitoring optimization system 100 according to this embodiment, the generation AI 400 may be configured to identify the target system 300, the monitoring settings, and the monitoring setting items in response to user input from a user. For example, the user input acquisition unit 134 acquires user input from the user 102 that does not specifically identify the target system 300. Then, the intermediation unit 138 inputs, for example, the user input and the system settings into the generation AI 400. The system settings may further include instructions for identifying the target system 300, the monitoring settings, and the monitoring setting items whose settings are to be changed in response to the user input. The intermediation unit 138 may obtain the monitoring settings identified by the generation AI 400 from the generation AI 400 and input the current setting data of the monitoring settings into the generation AI 400. Then, as described above, after inputting to the generation AI 400, the intermediary unit 138 may mediate the dialogue between the generation AI 400 and the user 102 until the generation AI 400 generates a proposed change to the monitoring settings that the generation AI 400 determines satisfies the change requests of the user 102.

[0066] 7 shows an example of the flow of processing by the monitoring optimization system 100. Here, the processing will be explained starting from a state where the monitoring setting to be changed, among multiple monitoring setting items set for the monitoring tool 200, is designated by the user 102, and continuing until the setting change of the monitoring setting is completed.

[0067] In step (sometimes abbreviated as S) 102, the monitoring setting identification unit 132 identifies the monitoring setting designated by the user 102 as the monitoring setting to be changed. In S104, the user input acquisition unit 134 acquires a user input indicating a change desired by the user 102 for the monitoring setting to be changed.

[0068] In S106, the setting data acquisition unit 136 acquires setting data set for the monitoring setting to be changed. In S108, the mediation unit 138 selects function-related information corresponding to the monitoring setting to be changed from among the plurality of pieces of function-related information stored in the function-related information storage unit 112. S104 to S108 may be performed in parallel.

[0069] In S110, the intermediation unit 138 executes input to the generation AI 400. The intermediation unit 138 may input the system settings, the user input acquired in S104, the setting data acquired in S106, and the function-related information selected in S108 to the generation AI 400. Note that the intermediation unit 138 may further input the dialogue history stored in the dialogue history storage unit 114 to the generation AI 400.

[0070] If the intermediation unit 138 has acquired a setting change proposal for the monitoring setting to be changed from the generation AI 400 (YES in S112), the process proceeds to S118; if not (NO in S112), the process proceeds to S114. In S114, the intermediation unit 138 acquires a message for the user 102 from the generation AI 400 and presents it to the user 102. In S116, the intermediation unit 138 acquires changes made by the user 102 in response to the message presented in S114 and inputs them into the generation AI 400. The intermediation unit 138 repeats S114 and S116 until it acquires a setting change proposal.

[0071] In S118, the intermediation unit 138 presents the proposed setting changes acquired from the generation AI 400 to the user 102. If the intermediation unit 138 receives an instruction to reflect the proposed setting changes in the monitoring settings of the setting change target (YES in S120), the process proceeds to S122. In S122, the setting unit 140 changes the settings of the monitoring settings of the setting change target in accordance with the proposed setting changes. Then, the process ends.

[0072] The monitoring optimization system 100 may change multiple monitoring settings in parallel. In this case, in S102, the monitoring setting identification unit 132 identifies multiple monitoring settings, in S104, the user input acquisition unit 134 acquires multiple user inputs, in S106, the setting data acquisition unit 136 acquires multiple setting data, in S108, the mediation unit 138 selects multiple pieces of function-related information, in S110, the mediation unit 138 executes input to the generation AI 400, and repeatedly executes S114 and S116 until all setting change proposals for the multiple monitoring settings are acquired, in S118, the multiple setting change proposals are presented to the user 102, and the setting unit 140 changes the monitoring settings in accordance with the setting change proposals in response to receiving a reflection instruction for each of the multiple setting change proposals.

[0073] The monitoring optimization system 100 may use the generation AI 400 to execute processing to support the user 102 in configuring new monitoring settings. In this case, S106 is not executed, and in S102 the monitoring setting identification unit 132 identifies new monitoring settings to be configured for the monitoring tool 200, in S104 the user input acquisition unit 134 acquires user input indicating the user 102's configuration preferences for the new monitoring settings, in S108 the intermediation unit 138 inputs the system settings, the user input, and associated function information corresponding to multiple monitoring setting items of the new monitoring settings into the generation AI 400, and repeatedly executes S114 and S116 until a proposed configuration is acquired, in S118 the proposed configuration is presented to the user 102, and in response to receiving an instruction to reflect the proposed configuration, the configuration unit 140 configures the new monitoring settings in accordance with the proposed configuration.

[0074] 8 schematically illustrates an example of the hardware configuration of a computer 1200 that functions as the monitoring optimization system 100. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of an apparatus according to the present embodiment, or to perform operations associated with the apparatus according to the present embodiment or one or more "parts" thereof, and / or to perform a process according to the present embodiment or steps of the process. Such a program can be executed by the CPU 1212 to cause the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0075] The computer 1200 according to this embodiment includes a CPU 1212, a RAM 1214, and a graphics controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communications interface 1222, a storage device 1224, a DVD drive, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive may be a DVD-ROM drive, a DVD-RAM drive, or the like. The storage device 1224 may be a hard disk drive, a solid-state drive, or the like. The computer 1200 also includes a ROM 1230 and legacy input / output units such as a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0076] The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into the graphics controller itself, and causes the image data to be displayed on the display device 1218.

[0077] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0078] The ROM 1230 stores therein a boot program or the like that is executed by the computer 1200 upon activation, and / or programs that depend on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, etc.

[0079] The programs are provided by a computer-readable storage medium such as a DVD-ROM or an IC card. The programs are read from the computer-readable storage medium, installed in the storage device 1224, RAM 1214, or ROM 1230, which are also examples of computer-readable storage media, and executed by the CPU 1212. Information processing described in these programs is read by the computer 1200, and causes cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be configured by implementing operations or processing of information in accordance with the use of the computer 1200.

[0080] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 may execute a communication program loaded into the RAM 1214 and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in the RAM 1214, the storage device 1224, a DVD-ROM, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes reception data received from the network to a reception buffer area or the like provided on the recording medium.

[0081] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), an IC card, etc. to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0082] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and may undergo information processing. The CPU 1212 may perform various types of processing on data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries, each having an attribute value of a first attribute associated with an attribute value of a second attribute, are stored on the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0083] The above-described programs or software modules may be stored in a computer-readable storage medium on or near the computer 1200. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0084] The blocks in the flowcharts and block diagrams in the present embodiments may represent stages of a process in which an operation is performed or "parts" of an apparatus responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable storage medium, and / or a processor provided with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuitry may include digital and / or analog hardware circuits, including integrated circuits (ICs) and / or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits, such as field programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements.

[0085] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture, including instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable storage media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray disc, memory stick, integrated circuit card, etc.

[0086] The computer readable instructions may include either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0087] Computer-readable instructions may be provided to a general-purpose computer, a special-purpose computer, or another programmable data processing device, or a programmable circuit, either locally or via a local area network (LAN) or a wide area network (WAN) such as the Internet, so that the processor of the programmable data processing device, such as a computer, or the programmable circuit executes the computer-readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Here, the computer may be a personal computer (PC), a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, a special-purpose computer, or the like, or may be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system, and is a broad definition of computers. In a distributed computing system, multiple computers collectively execute a program by each executing a portion of the program and passing data between the computers as needed during program execution.

[0088] Examples of processors include computer processors, central processing units, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc. A computer may have one or more processors. In a multiprocessor system with multiple processors, each processor executes a portion of a program and passes data between processors as needed during program execution, allowing the multiple processors to collectively execute the program. For example, in multitasking, each of the multiple processors may execute a portion of each task in small chunks by switching tasks at time slice intervals. In this case, which portion of a program each processor executes changes dynamically. Which portion of a program each of the multiple processors executes may also be statically determined by multiprocessor-aware programming.

[0089] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0090] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order. [Explanation of symbols]

[0091] 20 network, 100 monitoring optimization system, 102 user, 110 memory unit, 112 function-related information memory unit, 114 dialogue history memory unit, 120 registration unit, 130 processing unit, 132 monitoring setting identification unit, 134 user input acquisition unit, 136 setting data acquisition unit, 138 mediation unit, 140 setting unit, 150 setting example, 160 input example, 170 presentation example, 171 no change, 172 before change, 173 symbol, 174 after change, 175 symbol, 200 monitoring tool, 300 target system, 400 generation AI, 1200 computer, 1210 host controller, 1212 CPU, 1214 RAM, 1216 graphics controller, 1218 display device, 1220 input / output controller, 1222 communication interface, 1224 storage device, 1230 ROM, 1240 I / O chip

Claims

1. a user input acquisition unit that acquires a user input indicating a user's desire to change a monitoring setting that is a setting change target among a plurality of monitoring settings that are set for the monitoring tool; a setting data acquisition unit that acquires setting data set for a plurality of monitoring setting items of the monitoring setting; an intermediary unit that inputs related function information, which is information on functions related to the plurality of monitoring setting items of the monitoring setting, the user input, and the setting data into a generation AI, mediates a dialogue between the generation AI and the user until a setting change proposal for the monitoring setting that the generation AI determines satisfies the change request is generated by the generation AI, and presents the setting change proposal to the user upon obtaining the setting change proposal from the generation AI; a setting unit that changes the monitoring settings of the monitoring tool in accordance with the setting change proposal in response to an instruction from the user; A monitoring optimization system comprising:

2. The monitoring optimization system according to claim 1 , wherein the associated function information includes information on all functions required to set the plurality of monitoring setting items.

3. a related function information storage unit for storing a plurality of pieces of related function information corresponding to a plurality of monitoring setting items; Equipped with 2. The monitoring optimization system of claim 1, wherein the intermediary unit selects, from the plurality of pieces of related function information, the related function information that corresponds to the plurality of monitoring setting items of the monitoring setting that is the target of setting change, and inputs the selected related function information, the user input, and the setting data to the generation AI.

4. A dialogue history storage unit that stores a dialogue history between the generated AI and the user. Equipped with The monitoring optimization system according to claim 1 , wherein the intermediary unit inputs the interaction history to the generating AI in addition to the user input, the setting data, and the related function information.

5. The monitoring optimization system according to claim 1 , wherein the mediation unit presents the setting change proposal to the user in such a way that a difference from the setting data acquired by the setting data acquisition unit can be identified.

6. 4. The monitoring optimization system according to claim 1, wherein the intermediary unit obtains from the generation AI the proposed setting change and explanatory data that explains the changes to the proposed setting change in natural language, and presents the proposed setting change and the explanatory data to the user.

7. 4. The monitoring optimization system of claim 1, wherein the intermediary unit inputs to the generating AI, in addition to the associated function information, the user input, and the setting data, a system setting indicating that the monitoring setting of the monitoring tool is to be changed using an API of the monitoring tool as a setting change AI of the monitoring optimization system.

8. 4. The monitoring optimization system of claim 1, wherein when the setting unit changes the monitoring settings of the monitoring tool in accordance with the setting change proposal, the setting unit stores the setting data of the monitoring settings before the change as a backup, and after the monitoring settings are changed, restores the monitoring settings using the setting data stored as the backup in accordance with an instruction from the user.

9. the user input acquisition unit acquires the user input for each of a plurality of monitoring settings designated by the user as setting change targets from among the plurality of monitoring settings set for the monitoring tool, the setting data acquisition unit acquires setting data set for each of the plurality of monitoring settings to be changed; The intermediary unit inputs to the generation AI a plurality of pieces of related function information, a plurality of pieces of setting data, and a plurality of user inputs corresponding to the plurality of monitoring settings to be changed, mediates a dialogue between the generation AI and the user until the generation AI generates a setting change proposal for the monitoring setting that satisfies the change request for each of the plurality of monitoring settings, and presents the plurality of setting change proposals to the user in response to obtaining the plurality of setting change proposals from the generation AI; The monitoring optimization system according to claim 1 , wherein the setting unit changes the plurality of monitoring settings of the monitoring tool in accordance with the plurality of setting change proposals in response to an instruction from the user.

10. the user input acquisition unit acquires a user input indicating a user's setting preference for a new monitoring setting to be newly set for the monitoring tool; The intermediary unit inputs the user input and associated function information, which is information on functions related to multiple monitoring setting items of the new monitoring setting, to the generation AI, mediates interactions between the generation AI and the user until the generation AI generates a setting proposal for the new monitoring setting that the generation AI has determined to satisfy the setting desire, and presents the setting proposal to the user in response to obtaining the setting proposal from the generation AI, the setting unit sets the new monitoring setting of the monitoring tool in accordance with the proposed setting in response to an instruction from the user. A monitoring optimization system according to any one of claims 1 to 3.

11. 1. A computer-implemented configuration method, comprising: a user input acquisition stage for acquiring a user input indicating a user's desire to change a monitoring setting to be changed among a plurality of monitoring settings set for the monitoring tool; a setting data acquisition step of acquiring setting data set for a plurality of monitoring setting items of the monitoring setting; an intermediation step of inputting related function information, which is information on functions related to the plurality of monitoring setting items of the monitoring setting, the user input, and the setting data into a generation AI, mediating a dialogue between the generation AI and the user until a setting change proposal for the monitoring setting that satisfies the change request is generated by the generation AI, and presenting the setting change proposal to the user upon obtaining the setting change proposal from the generation AI; a setting step of changing the monitoring settings of the monitoring tool in accordance with the setting change proposal in response to an instruction from the user; A setting method comprising:

12. A program for causing a computer to execute the setting method according to claim 11.

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