Job Execution Log Monitoring for Proactive Error Resolution
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Solution Overview
Problem
Software development projects involving distributed teams face inefficiencies in error resolution due to lengthy and resource-intensive support sessions when error events occur during job execution, such as build processes in CI/CD platforms.
Innovation Solution
A proactive error resolution system that monitors logs in real-time, identifies error events using machine learning models, and generates automated communications to users with resolution outputs, while also detecting and informing about broader incidents impacting computing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual support sessions are used to resolve errors during job execution, then users can receive assistance from support personnel, but the process becomes lengthy and consumes excessive computing and network resources
Solution Approach 1:
The system enables self-service by automatically detecting errors in job execution logs and generating resolutions without requiring manual support sessions. The error detection system continuously monitors logs, identifies error patterns, and provides automated resolutions, allowing the system to serve itself rather than relying on external support personnel.
Solution Approach 2:
The system performs preliminary action by pre-processing and analyzing logs in real-time to detect errors before they escalate. By continuously monitoring log entries and identifying error patterns proactively, the system can generate resolutions in advance, preventing the need for lengthy manual support sessions.
2Reliability
If manual support sessions are conducted for error resolution, then users can obtain assistance, but the process is time-consuming and reduces job execution efficiency
Solution Approach 1:
The system maintains continuous monitoring of job execution logs, ensuring uninterrupted error detection and resolution. By continuously analyzing log entries in real-time, the system provides ongoing error detection and resolution capabilities without interruption, eliminating the delays associated with manual support session scheduling and execution.
Solution Approach 2:
The automated error detection and resolution system operates independently without requiring manual intervention, providing immediate error resolutions as they occur. This self-service capability eliminates the time-consuming nature of manual support sessions while maintaining reliable error resolution.
3Measurement precision
If extensive support sessions are conducted to resolve errors, then comprehensive error analysis can be performed, but computing and network resources are significantly consumed
Solution Approach 1:
The system applies partial action by focusing error detection efforts only on relevant log entries and error patterns. Instead of analyzing entire log files comprehensively, the system identifies and focuses on specific error indicators, achieving sufficient error analysis accuracy while consuming minimal computing resources.
Solution Approach 2:
The system replaces manual mechanical support sessions with automated computational error detection. By substituting human analysis with automated log processing and pattern recognition algorithms, the system achieves comprehensive error analysis accuracy while consuming significantly fewer computing and network resources than manual sessions would require.
4Productivity
If real-time log monitoring and automated error detection are implemented, then error resolution time is reduced and support sessions are minimized, but the system complexity increases
Solution Approach 1:
The error detection system is designed with multi-functionality, serving multiple purposes: monitoring logs, detecting errors, analyzing patterns, and generating resolutions. By consolidating these functions into a single unified system, the patent reduces overall system complexity compared to having separate systems for each function, while maintaining high job execution efficiency.
5Productivity
If automated error detection and resolution systems are implemented, then support session requirements are reduced, but the initial system setup and configuration become more complex
Solution Approach 1:
The automated error detection and resolution system is designed to be self-configuring and self-maintaining where possible. The system automatically learns from error patterns and improves its detection capabilities over time, reducing the need for complex manual configuration and ongoing maintenance, thereby improving support session efficiency while managing system complexity.
Data Source
AI summary
In some implementations, a device may obtain one or more logs that relate an execution of a job in a platform. The log(s) may be generated by the platform, the platform may use one or more computing systems in connection with the execution of the job, and the job may be user-initiated. The device may process the log(s) to identify whether an entry in the log(s) indicates an error event for the job. The device may determine a resolution output relating to the error event. The device may obtain incident data that relates to the computing system(s), where the incident data indicates whether an incident impacting the computing system(s) has been detected. The device may generate a communication that may include at least one of the resolution output or an incident output relating to the incident, in accordance with whether the incident data indicates the incident.