Servicenow, Inc.

Stephen Scott Tucker

Kanwaldeep Kaur Dang

Qingbin Li

Purushottam Shridhar Amradkar

James Crotinger

Dustin Lennon

Purushottam Amradkhar

Haviv Rosh

Chinna Babu Polinati

Yuval Rimar

Sridhar Chandrashekar

Amit Chandulal Dhuleshia

Chris Nguyen

Kiran Kumar Bushireddy

Hardik Modi

Oron Subayi

Kelly Vincent

Vishal Rao

Eugen Ardeleanu

Evan Qu

Christopher Robert Mutzel

Greeshma Kulamarva Balasubrahmanya

A computing system and method for remote monitoring and forecasting of performance of a managed network is disclosed. The computing system may be disposed within a remote network management platform and be configured for monitoring respective performance of each of a plurality of network entities of the managed network. For each network entity, an alert may be issued in response to determining that the monitored respective performance is below a respective threshold performance level. Based on analysis of a group of alerts, a likelihood may be determined that a different alert will be issued for the monitored performance of a particular network entity of the plurality for which no respective alert has yet been issued. In response to the likelihood exceeding a threshold, an alert prediction for the performance of the particular network entity may be issued together with a score corresponding to the likelihood.

Operational analytics in managed networks

A system, includes: a distributed cache that stores state information for a plurality of configuration items (CIs). Management, instrumentation, and discovery (MID) servers form a cluster, each of the MID servers including one or more processors that receive, from the distributed cache, a subset of the state information associated with assigned CIs and perform a statistical analysis on the subset of the state information.

Systems and methods for robust anomaly detection

Systems and methods for mapping configuration items to business functions within a corporate infrastructure are disclosed. Discovery processes to automatically create and update service maps may introduce an artificial dependency between configuration items that is not necessary to the business function represented in the service map. These unnecessary dependencies may be considered 'noise' and unnecessarily complicate the service map. Using machine learning techniques and procedures to identify short lived connections embodiments in accordance with this disclosure, dependency connections that may be considered noise may be detected and flagged. Once detected, these connections may be automatically removed from the service map to improve its accuracy and usefulness. Additionally, a user interface is provided that explains the 'reason codes' for identification of noise connections. Reason codes allow a user to understand how the machine learning algorithm traversed a decision tree to identify a connection as noise.

Traffic based discovery noise reduction architecture

Systems and methods are disclosed for network event grouping. For example, methods may include generating a graph including vertices and edges, wherein at least one of the vertices is associated with an event type from a set of event types and wherein at least one of the edges is associated with a weight; removing, based on an associated weight and a first threshold, one or more edges from the graph; determining, after removing the one or more edges from the graph, whether the graph is chordal; responsive to determining that the graph is chordal, identifying a connected subgraph within the graph; determining a group of event types to include event types that are associated with vertices in the identified connected subgraph; and transmitting, storing, or displaying data specifying the group of event types.

Network event grouping

Disclosed are methods, apparatuses and systems for collecting transactional and dimensional data. One implementation includes a configuration management database, a first data collection agent operating on a first monitored server to collect metadata associated with the first monitored server from the configuration management database using the first data collection agent, collect metric data from the first monitored server regarding operation of the first monitored server, wherein the metric data includes at least one metric collected from at least one application executing on the first monitored server; and assemble the collected metric data and at least part of the collected metadata into a packet for transmission from the first monitored server to a message bus; and a distributed database configured to receive the packet from the message bus and to store the collected metric data and metadata included in the packet.

Streamlined transaction and dimension data collection

A system includes a non-transitory memory and a hardware processors configured to perform operations including receiving a plurality of events from one or more network monitoring systems, wherein each event includes a message output by a network monitoring system communicating a status of a network resource connected to a network, clustering similar events into one or more event clusters, extracting an event template for each event cluster, extracting a regular expression (regex) for each event cluster, grouping the events into one or more groups of events having the same or similar extracted regexes, and outputting the one or more groups of events.

Systems and method for event parsing

Growing community of inventors

Kirkland, WA, United States of America

Stephen Scott Tucker