Application of neural nets to determine the probability of an event being causal
An event clustering system 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 using 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. The system is configured to group two or more situations, where a situation is a collection of one or more events or alerts representative of a problem in the managed infrastructure.
1. An event clustering system, comprising:
an extraction engine in communication with a managed infrastructure that includes physical hardware;
a signalizer engine that includes one or more of an NMF engine (Non-negative matrix factorization), a k-means clustering engine (a method of vector quantization), and a topology proximity engine, the signalizer engine determining one or more common characteristics or features from events, the signalizer engine determining one or more common steps from events and produces clusters relating to events, the signalizer engine determining one or more common characteristics of events and producing clusters of events relating to the failure or errors in the infrastructure, where 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 infrastructure directed to supporting the flow and processing of information, where membership in a cluster indicates a common factor of the events that is a failure or an actionable problem in the physical hardware of the infrastructure directed to supporting the flow and processing of information;
one or more interactive displays that provide a collaborative interface coupled to the extraction and the signalizer engine with a collaborative interface (UI) for decomposing events from the infrastructure;
the signalizer engine with at one or more of the NMF engine and the k-means clustering engine using graph coordinates and optionally a subset of attributes assigned to each event to generate one or more clusters to bring together events whose characteristics are similar;
the signalizer engine with at one or more of the NMF engine and the k-means clustering engine factoring a matrix M into A and B, where A is inspected and substantially significant clusters are extracted, and B is used to assign a start and end time to each cluster, and an output of clusters is produced; in response to production of the clusters one or more physical changes in a physical hardware of the infrastructure is made;
wherein the system is configured to group two or more situations, where a situation is a collection of one or more events or alerts representative of a problem in the managed infrastructure.
2. The system of claim 1 , wherein a situation represents a point in time when one or more managed infrastructure related events occurred.
3. The system of claim 1 , wherein machine learning is utilized to educate the system.
4. The system of claim 1 , wherein the system learns from prior situations.
5. The system of claim 4 , wherein the prior situations are used to discard things that are not relevant to a situation.
6. The system of claim 4 , wherein the system focuses on one or more elements of a situation.
7. The system of claim 1 , wherein the user interface is configured to provide a summary view of a situation.
8. The system of claim 1 , wherein the interface is configured to provide a summary view of the plurality of situations.
9. The system of claim 1 , further comprising: filtering to reduce a number of situations displayed based on attributes.
10. The system of claim 1 , further comprising: a situation room.
11. The system of claim 10 , wherein the situation room includes a guide for a user.
12. The system of claim 11 , wherein the guide includes a start page.
13. The system of claim 11 , wherein the situation room contains a feed view that displays one or more activities in a situation's life cycle.
14. The system of claim 10 , wherein the system is configured to allow users to create a user post.
15. The system of claim 10 , wherein the system is configured to provide chat conversations relative to a situation.
16. The system of claim 10 , further comprising: a team room that includes members.
17. The system of claim 16 , wherein a situation is linked to the team room.
18. The system of claim 16 , wherein a situation is linked to a plurality of team rooms at the same time.
19. The system of claim 16 , wherein a team room has a longer duration than a situation room.
20. The system of claim 16 , wherein the team room includes a view of the system and user activity.
21. The system of claim 16 , wherein members of the team room create posts available to other members of the team room.
22. The system of claim 16 , wherein members of the team room can create posts.
23. The system of claim 22 wherein each of a post can be at least one of: a question; a tip to solve a problem and a text statement.
24. The system of claim 22 , wherein the posts provide a method for classifying one or more posts and enable at least one of: organization; search; and filtering for the one or more posts.