Microsoft patents AI tool to group cloud errors and find root causes
Microsoft describes a system that uses AI to sort through thousands of error signals in a cloud network. It combines different grouping methods to link related errors together, helping engineers quickly identify the single cause behind a service outage.
In the filing’s own words
This disclosure describes utilizing an anomaly-based mitigation system to accurately, flexibly, and efficiently determine groupings of anomalous signals from across a computing system by identifying and combining different logical groups of anomalous signals. For example, the anomaly-based mitigation system utilizes different grouping logic models, which identify various connection strategies to determine initial groupings of anomalous signals. The anomaly-based mitigation system then determines commonalities between the initial anomalous signal groups using graph models to identify connected groups of anomalous signals. Furthermore, the anomaly-based mitigation system refines the groups to enhance their effectiveness in identifying and resolving service incidents in the computing system. In some instances, the anomaly-based mitigation system presents the anomalous signal groups in an incident report interface that includes actions to take or actions that were automatically taken to resolve a service incident.
What exactly they claim (claim 1)
1. A computer-implemented method for generating anomaly groupings for incidents in a computing system using one or more generative artificial intelligence (AI) models, the computer-implemented method comprising: obtaining a set of detected anomalous signals corresponding to a cloud computing system; generating, using multiple different grouping logic models, multiple data graphs that each include groups of related anomalous signals from the set of detected anomalous signals; generating an aggregated data graph by combining the multiple data graphs to form multiple groups of connected anomalous signals; determining a root cause for a first group of the multiple groups of connected anomalous signals based on a first set of anomalous signals in the first group using a generative AI model; and providing the multiple groups of connected anomalous signals within an incident report interface, the incident report interface including the first group and the root cause for the first set of anomalous signals.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- GENERATING ENHANCED ANOMALOUS SIGNAL GROUPS IN A CLOUD COMPUTING SYSTEM USING GROUPING LOGIC MODELS
- Publication number
- US20260300474A1
- Application number
- 19091593
- Filed
- Mar 26, 2025
- Published
- Oct 1, 2026
- Inventors
- 8
- Claims
- 20
Classified under
G06F 21/552 Physics & computingG06F 21/6218 Physics & computingH04L 63/1425 Electricity & electronicsMore from Microsoft in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.