Abstract: Provided is a management system managing a computer system including apparatuses to be monitored. The management system holds configuration information on the computer system, analysis rules and plan execution effect rules. The analysis rules each associates a causal event that may occur in the computer system with derivative events that may occur by effects of the causal event and defines the causal event and the derivative events with types of components in the computer system. The plan execution effect rules each indicates types of components that may be affected by a computer system configuration change and specifics of the effects. The management system identifies a first event that may occur when a first plan changing the computer system configuration is executed using the plan execution effect rules and the configuration information, and identifies a range where the first event affects using the analysis rules and the configuration information.

Abstract: A management system has a topology display screen of a management target system with an area, where icons of system components are typically displayed in the related art, which is embedded and displayed with a graph of a monitor value of the system component. A band having a predetermined width is displayed to show a relation between system display objects indicating the system components. The width of the band is determined by the number of requests which are transmitted or received by the system components. When a time-sequential graph of the monitor value of a system component is displayed, a vertical bar which can be operated by an input/output device is displayed in the graph. When the operation of the vertical bar is detected, an icon indicating integrity of the management target system at a time indicated by the vertical bar is displayed in the vicinity of the vertical bar.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A management apparatus and a management method that enable parsing processing to be executed efficiently by means of a working memory of a fixed size are proposed. One or more predefined rules are divided into one or more rule segments that comprise a condition and a conclusion that each form part of the rule, and the rule segments obtained through the division are stored in the secondary storage, and when an event notification from the information processing device is received, one or more related rule segments are selected and, by linking the selected one or more rule segments in the memory as required, a rule parsing network is constructed that indicates relationships between rules in the memory, an inference is derived on the basis of the constructed rule parsing network, and rule segments that are not readily used in inference derivation are deleted from the memory.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A management apparatus and a management method that enable parsing processing to be executed efficiently by means of a working memory of a fixed size are proposed. One or more predefined rules are divided into one or more rule segments that comprise a condition and a conclusion that each form part of the rule, and the rule segments obtained through the division are stored in the secondary storage, and when an event notification from the information processing device is received, one or more related rule segments are selected and, by linking the selected one or more rule segments in the memory as required, a rule parsing network is constructed that indicates relationships between rules in the memory, an inference is derived on the basis of the constructed rule parsing network, and rule segments that are not readily used in inference derivation are deleted from the memory.

Abstract: In the system management server, an information processing apparatus that is an event-information acquisition target is registered as a monitored apparatus in configuration information; event information that complies with a rule stored in advance is identified from among a plurality of pieces of event information stored in the system management server; a server apparatus for a network service related to the event information is identified; and a message is displayed which indicates that the cause of the event that occurred in a client information processing apparatus which has generated event information is an event related to the network service, which occurred in the server apparatus.

Abstract: A management apparatus and a management method that enable parsing processing to be executed efficiently by means of a working memory of a fixed size are proposed. One or more predefined rules are divided into one or more rule segments that comprise a condition and a conclusion that each form part of the rule, and the rule segments obtained through the division are stored in the secondary storage, and when an event notification from the information processing device is received, one or more related rule segments are selected and, by linking the selected one or more rule segments in the memory as required, a rule parsing network is constructed that indicates relationships between rules in the memory, an inference is derived on the basis of the constructed rule parsing network, and rule segments that are not readily used in inference derivation are deleted from the memory.

Abstract: A management system, which manages an information processing system by identifying a cause location based on previously defined analysis rule information, displays a status that is a condition of the analysis rule information but is not receivable, based on acquirable status information of the apparatuses making up the information processing system or information about statuses received in the past.

Abstract: A management system comprises at the least a first analysis rule information and a second analysis rule information, acquires a first analysis result and a second analysis result based on a detected status of an information processing apparatus, and aggregates and displays a first analysis result and a second analysis result based on (A) a cause denoted by an analysis result, (B) a status condition of analysis rule information that forms the basis for the analysis result, or (C) a detected status.

Abstract: Provided is a management system for managing a plurality of management target information processing apparatuses including a plurality of network apparatuses and a computer. This management system determines the reachability of a route network apparatus as a network apparatus on a communication between the system and the computer, and calculates a certainty factor concerning the certainty on whether a prescribed network apparatus contained in a route network apparatus based on the reachability is the cause of unreachability from the management system to the computer. The management system subsequently displays information showing that communication from the management system to the computer is unreachable, and the certainty factor as the certainty that the prescribed route network apparatus is the cause of unreachability.

Abstract: A policy creation support system is provided, which is capable of reducing cost for creation of an effective autonomic control policy. The policy creation support system measures information indicating performance of a monitoring target system, with regard to a monitoring item of a designated type, for each resource amount of an expandable resource, and selects one representative measurement value from among measurement values on a resource-amount basis. Then, the policy creation support system outputs the monitoring item, the resource amount serving as the monitoring item, and a range of the measurement value corresponding to the resource amount, as a countermeasure decision condition within a policy, by setting a range including the selected representative measurement value as the range of the measurement value.

Abstract: To reduce the burden of processing for completing event cause information, which is carried out when a management target node apparatus is added, removed or changed. A management computer determines whether or not partial change to add, delete or change part of information related to an event related to an added, removed or changed node apparatus can be performed or not on the event cause information. The management computer adds, deletes or changes the part of information with respect to the event cause information, when the result of the determination is affirmative.

Abstract: A root cause analysis engine uses event survival times and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Certainty factors of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a survival time, and when the time has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the certainty factor of each rule by only performing the re-calculation with respect to affected rules that are related with the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally.

Abstract: A technique of performing concurrency control of policies is provided, which makes it possible to efficiently utilize resources of an overall information system. According to the present invention, a policy execution device creates a list of components of a application system which are influenced by execution of an action of a policy instance, for respective policy instances. If trigger conditions of another policy instance are newly met during execution of a policy instance, the policy execution device compares a list of components of the policy instance presently being executed with a list of components of the policy instance whose trigger conditions are newly met. If there are no common components in the lists, the policy execution device executes the policy instance whose trigger conditions are newly met, and if there are common components in the lists, the policy execution device suspends the policy instance whose trigger conditions are newly met.

Abstract: A root cause analysis engine uses event durations and gradual deletion of events to improve analysis accuracy and reduce the number of required calculations. Matching ratios of relevant rules are recalculated every time notification of an event is received. The calculation results are held in a rule memory in the analysis engine. Each event has a valid duration, and when the duration has expired, that event is deleted from the rule memory. Events held in the rule memory can be deleted without affecting other events held in the rule memory. The analysis engine can then re-calculate the matching ratio of each rule by only performing the re-calculation with respect to affected rules related to the deleted event. The calculation cost can be reduced because analysis engine processes events incrementally or decrementally. Analysis engine can determine the most possible conclusion even if one or more condition elements were not true.