RESOURCE ANOMALY DETECTION

Organization Name

Inventor(s)

RESOURCE ANOMALY DETECTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240223479 titled 'RESOURCE ANOMALY DETECTION

Simplified Explanation

The patent application discusses systems and methods for detecting an unstable resource in a cloud service by analyzing health time-series data and comparing it to historical data to determine anomalous behavior.

Key Features and Innovation

Utilizes a resource behavior model trained on historical health time-series data to encode received data into embeddings.
Determines if a resource is operating in an anomalous behavior state by comparing embeddings to the received data.
Compares generated embeddings to those from other similar resources to determine anomalous behavior.
Reports anomalous behavior to indicate an unstable or unhealthy resource.

Potential Applications

This technology can be applied in cloud services, data centers, and IT infrastructure management to monitor resource health and stability.

Problems Solved

This technology addresses the challenge of detecting unstable resources in cloud services before they cause disruptions or failures.

Benefits

Early detection of unstable resources can prevent downtime and improve overall system reliability.
Allows for proactive maintenance and resource management in cloud environments.

Commercial Applications

"Cloud Resource Stability Detection System" can be used by cloud service providers, IT companies, and data centers to enhance service reliability and performance.

Prior Art

Readers can explore prior research on anomaly detection in cloud services and resource monitoring systems to understand the background of this technology.

Frequently Updated Research

Stay updated on advancements in cloud resource monitoring, anomaly detection algorithms, and predictive maintenance techniques to enhance the effectiveness of this technology.

Questions about Cloud Resource Stability Detection System

How does this technology improve resource management in cloud services?

This technology enhances resource management by providing early detection of unstable resources, allowing for proactive maintenance and minimizing downtime.

What are the potential implications of using this system in data centers?

Implementing this system in data centers can lead to improved operational efficiency, reduced risks of system failures, and enhanced overall performance.

Original Abstract Submitted

systems and methods for detecting an unstable resource of a cloud service. a set of health time-series data of a first resource is received and a resource behavior model trained on historical health time-series data of resources of a same type as the first resource is used to encode the received data into embeddings. in some examples, the model reconstructs the embeddings, compares the embeddings to the received data, and determines a reconstruction loss value for determining whether the first resource is operating in an anomalous behavior state. in some examples, the generated embeddings are compared to embeddings generated from health time-series data received from other resources of a same type as the first resource. a similarity-score is determined and used to determine whether the first resource is operating in an anomalous behavior state. the system and method further report anomalous behavior, indicating the first resource is unstable or unhealthy.