New Relic has been granted a patent for an automation method that enhances event logging and debugging in Kubernetes. The method involves using a distributed agent and edge modules to track and merge data coresets from multiple nodes, enabling the training of an unsupervised model for event identification and clustering. GlobalData’s report on New Relic gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on New Relic, Hybrid cloud mgmt was a key innovation area identified from patents. New Relic's grant share as of June 2024 was 47%. Grant share is based on the ratio of number of grants to total number of patents.
Event logging and debugging automation for kubernetes clusters
The patent US12045676B2 outlines a method and system for identifying and clustering events within a distributed application cluster. The method involves deploying a distributed agent across multiple nodes, each running at least one distributed application. A series of edge modules are configured to operate on each node, tracking data coresets that represent samples of the application data from their respective nodes. These data coresets are then merged to create a unified data coreset, which is transferred to the distributed agent. This agent utilizes an unsupervised machine-learning model to analyze the data and identify clusters of events across the entire application cluster.
Additionally, the patent details various functionalities, including the periodic updating of the unified data coreset and the ability to generate this coreset in response to specific data queries. The system also incorporates the deployment of Berkeley Packet Filter (BPF) probes and programs on each node to facilitate data tracking. The method ensures that the captured data is representative of the total application data, enhancing the accuracy of event identification and clustering. Overall, the patent presents a comprehensive approach to managing and analyzing data in distributed application environments, leveraging advanced machine-learning techniques for improved event detection.
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