Healtech Software India Pvt. Ltd.

Rambus Inc.

Sudhir Shetty

Atri Mandal

Palavali Shravan Kumar Reddy

Vidhya Thyagarajan

Raja Shekhar Mulpuri

Howard Zhang

Shainy Merin

Adityam Ghosh

Jaisri S

Arpit Rathi

Proactive avoidance of performance issues in computing environments. In one embodiment, a causal dependency graph representing the usage dependencies among the various components of a computing environment is formed, the components being associated with key performance indicators (KPIs). A probabilistic model is trained with prior incidents that have occurred in the components to correlate outliers of KPIs in associated components to prior incidents. The training includes determining the correlation based on the causal dependency graph. Upon detecting the occurrence of outliers for performance metrics, an imminent performance issue likely to occur in a specific component is identified based on the probabilistic model and the detected outliers. A preventive action is performed to avoid the occurrence of the imminent performance issue in the specific component.

Proactive avoidance of performance issues in computing environments using a probabilistic model and causal graphs

An aspect of the present disclosure provides a relevance ranking system for events identified by performance management systems. In one embodiment, a system receives, from one or more performance management systems, events associated with performance metrics and determines, based on the received events, a corresponding relevance score for each performance metric. The system generates a ranking list of the received events based on the corresponding relevance scores (determined for the performance metrics). The system then provides the ranking list of events to a user (such as an administrator). According to another aspect, the system (noted above) performs the steps of receiving, determining, and generating for each time interval of a set of time intervals.

Relevance ranking system for events identified by performance management systems

According to an aspect, a (recommendation) system constructs a knowledge graph based on problem descriptors and remediation actions contained in multiple incident reports previously received from a performance management (PM) system. Each problem descriptor and remediation action in an incident report are represented as corresponding start node and end node in the knowledge graph, with a set of qualifier entities in the incident report represented as causal links between the start node and the end node. Upon receiving an incident report related to an incident identified by the PM system, the system extracts a problem descriptor and a set of qualifier entities. The system traverses the knowledge graph starting from a start node corresponding to the extracted problem descriptor using the set of qualifier entities to determine end nodes representing a set of remediation actions. The system provides the set of remediation actions as recommendations for resolving the incident.

Recommending remediation actions for incidents identified by performance management systems

Methods and apparatuses that relate to an integrated circuit (IC) with adaptive power state management are described. The IC can be coupled with, and can control the operation of, a memory device. The IC and the memory device can be operated in multiple operational states, wherein each operational state may represent a tradeoff point between performance and power consumption. The IC may be capable of: (1) changing the operational state of the IC and/or the operational state of the memory device based on the occurrence of one or more conditions, and/or (2) changing the one or more conditions based on measuring one or more performance values associated with the IC and/or the memory device.

Integrated circuit with adaptive power state management

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Bengaluru, India

Sudhir Shetty