1062 results about "Root cause" patented technology

A network appliance for monitoring, diagnosing and documenting problems among a plurality of devices and processes (objects) coupled to a computer network utilizes periodic polling and collection of object-generated trap data to monitor the status of objects on the computer network. The status of a multitude of objects is maintained in memory utilizing virtual state machines which contain a small amount of persistent data but which are modeled after one of a plurality of finite state machines. The memory further maintains dependency data related to each object which identifies parent / child relationships with other objects at the same or different layers of the OSI network protocol model. A decision engine verifies through on-demand polling that a device is down. A root cause analysis module utilizes status and dependency data to locate the highest object in the parent / child relationship tree that is affected to determine the root cause of a problem. Once a problem has been verified, a “case” is opened and notification alerts may be sent out to one or more devices. A user interface allows all objects within the network to be displayed with their respective status and their respective parent / child dependency objects in various formats.

A system and method for providing an accurate root cause failure by linking user incident reports to the root cause failure in a diagnostic database that reflects the system's current configuration. The system is pre-populated with pre-identified symptoms that are associated with assets in the system. The pre-identified symptoms are inactive until actual failures with assets are detected by a monitoring application. After the pre-identified symptoms become active, they are presented to service representatives who also answer calls from users. The activated pre-identified symptoms are used to assist the service representatives to solve problems observed by the users.

A network appliance for monitoring, diagnosing and documenting problems among a plurality of devices and processes (objects) coupled to a computer network utilizes periodic polling and collection of object-generated trap data to monitor the status of objects on the computer network. The status of a multitude of objects is maintained in memory utilizing virtual state machines which contain a small amount of persistent data but which are modeled after one of a plurality of finite state machines. The memory further maintains dependency data related to each object which identifies parent / child relationships with other objects at the same or different layers of the OSI network protocol model. A decision engine verifies through on-demand polling that a device is down. A root cause analysis module utilizes status and dependency data to locate the highest object in the parent / child relationship tree that is affected to determine the root cause of a problem. Once a problem has been verified, a “case” is opened and notification alerts may be sent out to one or more devices. A user interface allows all objects within the network to be displayed with their respective status and their respective parent / child dependency objects in various formats.

A method of root cause analysis in a virtual machine environment includes receiving a plurality of events from a system monitoring the virtualized environment. The events may include alarms or alerts, such as alarms or alerts associated with a resource reaching or exceeding a threshold. The capacity manager consumes these events and performs event correlation to produce a set of correlated events. The capacity manager performs a root cause analysis on the set of correlated events to identify one or more root causes. The capacity manager further performs an impact analysis to determine how the root cause impacts the system, such as other virtual machines, hosts or resource in the virtual environment. Based on the root cause and impact analysis, the capacity manager makes one or more recommendations to address issues with or to improve the operations and / or performance of the virtualized environment.

A metric monitoring and analysis system including dynamic sampling agents located in monitored system elements and a service management platform. Each sampling agent includes a data adapter collecting metric data in a common format, a threshold generator for determining dynamic metric threshold ranges, an alarm detector generating an indicator when a metric deviates outside a dynamic threshold range or a static threshold, and a deviation tracker generating an alarm severity scores. The service platform includes an alarm analyzer identifying root causes of system alarm conditions by correlation of grouped metrics or forensic analysis of temporally or statistically correlated secondary forensic data or data items from a service model of the system.

A method for self-determining a root cause of a system fault in a heating, ventilation, and cooling (HVAC) system includes receiving a fault message indicative of a fault condition in an operating characteristic of the HVAC system; determining a causal relationship between the fault condition and a predetermined list of root causes associated with the fault condition; receiving information indicative of operating conditions of the HVAC system; and eliminating at least one root cause that is unrelated to the fault condition in response to the receiving of the information.

A method for analyzing the root cause of system failures on one or more computers. An event is generated when a computer system detects a system failure. The cause of the failure is determined. The event, including the cause is transmitted from the computer system to a central repository. And the system failure is analyzed in the central repository.

A technique for determining a root cause of a condition (e.g., service outage) of at least one subject component in a computing environment comprises the following steps / operations. First, one or more components in the computing environment upon which the at least one subject component depends (e.g., antecedents) are identified. Identification comprises traversing at least a portion of a model representative of an existence of one or more relationships associated with at least a portion of components of the computing environment and which is capable of accounting for a full lifecycle (e.g., including deployment, installation and runtime) associated with at least one component of the computing environment. Then, one or more procedures are performed in accordance with the one or more identified components to determine a condition status associated with each of the one or more identified components. By way of example, the inventive techniques may be applied to a distributed computing environment. The computing environment may also be an autonomic computing environment.

An analyzer arrangement for provision of information about a facility by means of root cause analysis. Storage assembly stores a data model that associates with the facility. The data model contains information about possible events, hypotheses for the root causes of the possible events and symptoms for the hypotheses. A processor provides root cause analysis based on the data model. An input inputs additional information for use in root cause analysis. An adaptor modifies the data model based on the additional information.

The present invention comprises a multi-tier system. Major goals of the system are to 1) clearly visualize BGP dynamics and alert / report important deviation of BGP dynamics to avoid overwhelming the operators with too much information and 2) analyze the root cause of the problems by using a multi-tier approach, with a light-computational analysis and high-level classification for a real-time problem identification followed by a more rigorous off-line analysis for a further and more detailed trouble shooting. An example embodiment is provided that comprises four modules. The first module comprises a distributed family of collectors in charge of collecting real-time network information. The second module filters out non-relevant prefixes and extracts and profiles key features of the network information. The third module monitors BGP activity from both an Internet-AS and single-AS perspectives by displaying the data in real time and highlighting major shifts or divergence from historical baselines with comprehensive layouts. The forth module is run off-line to focus on a few relevant events that are selected through the first three modules. This is usually a time-consuming phase of the process due to the different temporal and / or spatial correlation that must be run across several sets of data. During this phase, the system can spend more time to better identify the real cause of the problem.

A life support and monitoring apparatus with malfunction correction guidance is provided. The life support and monitoring apparatus of the present disclosure identifies the root cause or potential cause of a fault / failure and then prompts an operator to take appropriate steps to assure the continuance of life support and critical physiologic monitoring. When multiple faults / failures exist, the apparatus automatically prioritizes them based on risk to the patient and prompts the operator to do the most appropriate intervention to assure patient safety.

Thousands of process and equipment measurements are gathered by the modern digital process control systems that are deployed in refineries and chemical plants. Several years of these data are historized in databases for analysis and reporting. These databases can be mined for the data patterns that occur during normal operation and those patterns used to determine when the process is behaving abnormally. These normal operating patterns are represented by sets of models. These models include simple engineering equations, which express known relationships that should be true during normal operations and multivariate statistical models based on a variation of principle component analysis. Equipment and process problems can be detected by comparing the data gathered on a minute by minute basis to predictions from these models of normal operation. The deviation between the expected pattern in the process operating data and the actual data pattern are interpreted by fuzzy Petri nets to determine the normality of the process operations. This is then used to help the operator localize and diagnose the root cause of the problem.

A method and apparatus are described for auditing and tracking changes in a managed hosting server. Embodiments of the present invention track changes made to systems in a server farm or data center. More specifically, embodiments of the present invention track changes to the operating system, file system, registry, application software files, and other important files and maintain the changes in a database. This database of changes can then be queried to identify the root cause of problems and aid in systems and applications management in the data center.

The invention discloses a method and equipment for positioning a fault root. The method comprises the steps of: acquiring a service fault to be processed, and finding log information associated with the service fault to be processed according to the service fault to be processed; determining a log analysis strategy corresponding to the service fault to be processed according to a preset relationship between service faults and log analysis strategies; and utilizing the determined log analysis strategy, analyzing the found log information, and positioning to obtain the fault root which causes the occurrence of the service fault to be processed. Thus, once a fault occurs in the service execution process, the fault root causing the service fault can be analyzed quickly by adopting the method and the equipment provided by the invention without consuming a lot of manpower, the manpower resources are saved, the fault root analysis efficiency can be improved, and the use experience of the user using application software can be improved.

A computer system includes a symptoms database having symptoms that relate to problems, where each symptom includes an event correlation rule having corresponding predicates. To identify a root cause of a problem, collected events are correlated with symptoms based upon their associated event correlation rule(s). For each symptom at least partially matched to an event, visualization information is associated with corresponding events based upon the visualization attribute of the symptom, and textual information is associated with event based upon the recommendation of the symptom. Moreover, recommendations may be provided to an operator, such as based upon information associated with the symptom. The event and symptom data is analyzed by grouping events in the set of events based upon their associated visualization information and presenting the textual information associated with an operator-selected event.

A network monitoring system is provided that includes a processor, a memory coupled to the processor and a database that includes key performance indicator (KPI) records for monitoring a wireless communication system. The network monitoring system further includes a rules engine configured and operable to store in the memory KPI rules associated with at least one rule set. The network monitoring system also includes an analysis engine configured and operable to identify a list of root causes identifying failure events based on the at least one KPI rule in the at least one rule set.

Methods, systems, and media for thermal analysis are disclosed. Embodiments of the invention receive temperatures associated with elements of a system. The temperatures received are dependant upon airflow and heating patterns of the elements. Differences between the temperatures received and expected temperatures are detected. Potential airflow and heating patterns associated with a thermal problem are then determined, the potential airflow and heating patterns being substantially consistent with the temperatures received, to identify a root cause of the thermal problem as a probable source of the differences. More specifically, embodiments collect temperature readings from temperature sensors within an enclosure of the system; identify and upward temperature gradient or temperature that exceeds a threshold temperature; and select a failure scenario associated with a root cause of a thermal problem that is similar to the thermal problem described by the temperature readings collected.

A technique is provided for designing and evaluating service models for components, functions, subsystems and field replaceable units in a complex machine system. At a component or item level, each model identifies various items, failure modes, and so forth which may be the root cause of anticipated serviceable events or faults. The design tools permit numerous interfaces to be used in the design of service models, and in the evaluation of the degree to which the models address detectability and isolation capabilities for the root causes of serviceable events and faults.

The present invention provides a method, apparatus, and computer program product for displaying real-time service level performance, breach, and guaranteed uniformity with automatic alerts and proactive rebating for a utility computing environment. Service level agreement parameters, based on a service level agreement between a customer and a service provider, are used to identify discrepancies in a promised service level for the utility computing environment. A real-time view of a current service level and the promised service level for the customer are displayed. When a discrepancy between the promised service level and the current service level occurs, a rebate is generated for the customer. Alerts identifying the discrepancy and its root cause are provided to the customer and the service provider for the discrepancy. Alerts may also be provided prior to the occurrence of the discrepancy so that an action may be performed to eliminate the potential discrepancy.

An arrangement for provision of information about causes of events in association with an equipment. The arrangement includes a data storage medium for storing beforehand prepared data that associates with the equipment. The data provides predetermined information about events that can associate with the equipment, hypotheses for the root causes of the events and symptoms for the hypotheses. A processor analyses a plurality of root cause hypotheses by processing information obtained from the data storage medium.

Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.

A virtual domain management system is provided which associates application, physical and virtual domains to enable propagation of events, symptoms and other information across the domains. The virtual domain manager collects events and symptom information across multiple domains by correlating domain topology models. Using a causality matrix and codebook technology the virtual domain manager uses the information to perform root cause and impact analysis across domains. Information from the analysis may be fed back into the domains to enhance domain management.

An improved root-cause approach to problem diagnosis in data networks in the form of a method comprising the steps of: associating each metric in a at least one set of metrics with at least one component and / or network device; obtaining values for each such metric from a monitoring system; determining whether each such metric is indicative of a problem within the data network; and ranking and correlating indicative problems to determine whether a problem may be symptomatic of another problem based on an interconnection and / or interdependency between a physical machine and a virtual machine, between components or between components and network devices.

A system and method are provided for enhanced navigation along execution time and code space in a debugger to assist a user in remediating errors, streamlining, or reverse engineering a computer program and the source code thereof. Snapshots of system states are recorded, a causality tree of commands is constructed through execution of the program to be debugged, and an intelligent display of system states captured during runtime and indexed or cross-referenced by time are displayed to the user in an intelligent manner to aid the user with certain debugging tasks. Additionally, further features in assisting the user to locate a root cause of an error or unexpected value and remediate that cause are also provided.

A method for visual representation of end user response time (EURT) in a multi-tiered network application is provided. Search criteria for searching a repository of client statistics records is received. The search criteria specifies identification information pertaining to a user of a multi-tiered network application experiencing application performance problems and a time period associated with the application performance problems. The identification information identifies an IP address of user's computing device. A plurality of client statistics records matching the search criteria is retrieved from the repository. The retrieved plurality of client statistics records is sorted based on measurements of performance parameters. A graph representing relevant topology hierarchy of the multi-tiered network application is presented to a user based on the sorted client statistics records. The graph visually identifies connections between nodes of the multi-tiered application. The identified connections include potential root-causes of the specified application performance problems.