Abstract:
An event clustering system is configured to generate reports. An extraction engine is in communication with an infrastructure. The extraction engine in operation receives data from the infrastructure and produces events. An alert engine receives the events and creates alerts mapped into a matrix, M. A sigalizer engine includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine. The sigalizer engine determines one or more common steps from events and produces clusters relating to the alerts and or events. A reporting engine is configured to be coupled to the event clustering system.
Abstract:
A computer-implemented method is provided that is stored on computer readable non-transitory media. One or more data fields are accessed within a file. Accessed data field, are mapped mapping on a display computer system. The accessed one or more data fields are from one or more data sources that relate to situations from clustering messages received from managed infrastructure. The mapping being performed based on a input of the situation summaries using a graphical user interface. Displayed on the display computer system are one or more dashboards of situations relative to summaries from clustering messages received from managed infrastructure. The one or more dashboards include at least one of actions that a user can take relative to clustered messages.
Abstract:
An event clustering system includes a processor. An extraction engine is in communication with an infrastructure. The extraction engine receives data from the infrastructure. A signalizer engine includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine. The signalizer engine determines one or more common steps from events and produces clusters relating to the alerts and or events. In response to production of the clusters one or more physical changes are made in a managed infrastructure hardware. Multi-systems interact with each other.
Abstract:
A system texecutes automatic attribute inference and includes: a processor; a memory coupled to the memory; a first engine that executes automatic attribute inference; an extraction engine in communication with a managed infrastructure and the first engine, the extraction engine configured to receive managed infrastructure data; and a signaliser engine that includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine, the signaliser engine inputting a list of devices and a list a connections between components or nodes in the managed infrastructure, the signaliser engine determining one or more common characteristics and produces one or more dusters of events.
Abstract:
A system provides for management of a managed infrastructure. A processor is coupled to various engines. An extraction engine is in communication with the managed infrastructure. The extraction engine in operation receives messages from the managed infrastructure, produces events that relate to the managed infrastructure and converts the events into words and subsets used to group the events into clusters that relate to failures or errors in the managed infrastructure, including managed infrastructure physical hardware. The managed infrastructure supports the flow and processing of information. A sigalizer engine includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine. The sigalizer engine determines one or more common steps from events and produces clusters relating to events; the sigalizer engine determining one or more common characteristics of events and producing clusters of events relating to the failure or errors in the managed infrastructure, where membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to supporting the flow and processing of information.
Abstract:
An event clustering system that has an extraction engine in communication with a managed infrastructure. A signalizer engine includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine. The signalizer engine determines one or more common characteristics or features from events. The signalizer engine uses the common features of events to produce clusters of events relating to the failure or errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to supporting the flow and processing of information. A feedback signalizer functor is provided that is a supervised machine learning approach to train to reproduce a situation. In response to production of the clusters one or more physical changes in a managed infrastructure hardware is made, where the hardware supports the flow and processing of information.
Abstract:
A system is provided for clustering events. At least one engine is configured to receive message data from managed infrastructure that includes managed infrastructure physical hardware that supports the flow and processing of information. The at least one engine is configured to determine common characteristics of events and produce clusters of events relating to the failure of errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to supporting the flow and processing of information. The at least one engine is configured to create one or more situations that is a collection of one or more events or alerts representative of the actionable problem in the managed infrastructure. A situation room includes a collaborative interface (UI) for decomposing events from managed infrastructures. In response to the production of the clusters one or more physical changes is made in managed infrastructure hardware. A reference tool provides for a decomposition of events.
Abstract:
Methods and system are provided for decomposing events from managed infrastructures. The system decomposes events from a managed infrastructure and includes a first engine that receives data from a managed infrastructure which includes managed infrastructure physical hardware. The infrastructure physical hardware supports the flow and processing of information. A second engine determines common characteristics of events and produces clusters of events relating to the failure of errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware managed infrastructure directed to support the flow and processing of information. Events are produced that relate to the managed infrastructure. The events are converted into words and subsets used to group the events that relate to failures or errors in the managed infrastructure, including the managed infrastructure physical hardware. The events have textural context. Semantic meaning is applied to the textual context of the events. A change to a managed infrastructure physical hardware component is made.
Abstract:
A system is provided for decomposing events from managed infrastructures. A first engine is configured to receive message data from a managed infrastructure that includes managed infrastructure physical hardware that supports the flow and processing of information, the at least one engine is configured to determine common characteristics of events and produce clusters of events relating to the failure of errors in the managed infrastructure. Membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in a physical hardware of the managed infrastructure directed to supporting the flow and processing of information. The first engine is configured to create one or more situations that is a collection of one or more events or alerts representative of the actionable problem in the managed infrastructure. A second engine is configured to determine one or more common steps from events and produces clusters relating to events. The second engine determines one or more common characteristics of events and produces clusters of events relating to the failure or errors in the managed infrastructure. The system is configured to use data-driven fault localization, more particularly using semantic clustering.