Bot Behavior Video Streams for Faster Automation Failure Diagnosis
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Solution Overview
Problem
Existing bot monitoring systems are reactive and lack predictive capabilities, leading to inefficiencies in diagnosing and preventing software bot failures, and they often require significant computing resources for debugging and data collection across multiple platforms.
Innovation Solution
A bot monitoring system that captures time-ordered interaction data, including screenshots and logs, to generate video streams depicting bot behavior, allowing for proactive anomaly detection and reducing the need for resource-intensive debugging by providing user-friendly renderings on a separate device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional bot monitoring systems are used, then bot performance can be monitored, but the systems are reactive and require significant computing resources for debugging and data collection
Solution Approach 1:
The patent creates video stream copies of bot interactions that can be analyzed without requiring access to the original computing environment. These video representations capture essential bot behavior data while consuming minimal resources, enabling proactive anomaly detection through visual inspection rather than resource-intensive logging and debugging operations
Solution Approach 2:
The video stream generation system acts as an intermediary between the bot execution environment and the monitoring system. It captures and transforms bot interactions into standardized video formats that can be analyzed independently, reducing the need for direct access to and resource consumption from the original computing environment
2Loss of information
If comprehensive logging is performed to capture bot behavior, then diagnostic information is obtained, but the process is time-consuming and requires direct access to the computing environment
Solution Approach 1:
The system performs preliminary capture of bot interactions as video streams during normal bot execution. This proactive recording ensures that all relevant behavior information is already available when anomalies occur, eliminating the need for time-consuming post-hoc debugging and direct access to the computing environment to reconstruct bot behavior
3Ease of operation
If video streams are generated from screenshots, then visual representation of bot behavior is created, but processing and storage requirements increase
Solution Approach 1:
The system extracts only the essential visual information needed for anomaly detection by generating video streams at optimized frame rates and resolutions. It captures key bot interactions and UI states while omitting redundant frames, thereby maintaining effective visual representation while reducing overall data volume compared to capturing every screen change
Data Source
AI summary
In some implementations, a monitoring system may capture a set of screenshots that depict behavior associated with a bot during an automation run. The monitoring system may obtain one or more logs that include information describing the behavior of the bot during the automation run. The monitoring system may create, based on a portion of the set of screenshots, video data that includes a sequence of frames related to an anomaly or a failure event that occurred during the automation run. The monitoring system may annotate, based on the information included in the one or more logs, the sequence of frames with metadata describing the behavior of the bot. The monitoring system may provide, to a user device, user interface data that includes the video data and the metadata used to annotate the sequence of frames.