Methods and systems to identify anomalous behaving components of a distributed …

This invention helps identify parts of a large computer system that are behaving unusually. It works by gathering all the messages (logs) that different parts of the system generate over a period of time. Then, for each part, it counts how often different types of messages appear. By comparing these message patterns between different parts, especially those that are supposed to be identical copies, it can spot the outliers that might be having problems.

Why it matters: Since 2016, the widespread adoption of cloud-native observability platforms and stream processing technologies has dramatically simplified the collection and real-time analysis of log data at scale, making the core data processing steps of this invention much more accessible and cost-effective to implement.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: ModerateSoftware logic, data processing pipeline

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