Context Analysis Engine for IT Incident Resolution
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Solution Overview
Problem
Current methods for handling IT incidents, especially network issues between cloud services and software applications, are inefficient due to the need for extensive manual interactions and analysis across different infrastructure and development teams, leading to prolonged incident resolution times and potential system damage.
Innovation Solution
A context analysis engine is implemented to detect IT incidents using observability data, obtain context information from the affected network, and determine countermeasures proactively, reducing the need for manual intervention and improving incident handling efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis and interaction with multiple teams is used to handle IT incidents, then comprehensive context information can be obtained, but incident resolution time increases significantly
Solution Approach 1:
A context analysis engine is introduced as an intermediary system that automatically collects, analyzes, and correlates context information from multiple sources (client applications, server components, network infrastructure) without requiring manual intervention from multiple teams. This intermediary automates the information gathering process while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The system enables self-service incident analysis by automatically detecting incidents, gathering relevant context information from distributed systems, and generating analysis results without requiring human operators to manually interact with multiple infrastructure teams. The context analysis engine serves itself by autonomously performing the entire analysis workflow.
2Measurement precision
If extensive manual interaction and tool activation is required for incident analysis, then thorough investigation is possible, but operational complexity increases
Solution Approach 1:
Multiple separate functions (incident detection, context information collection from client and server, network analysis, and analysis generation) are merged into a single context analysis engine. This consolidation eliminates the need for multiple teams to manually activate different tools and coordinate their efforts, while maintaining thorough analysis capabilities.
Solution Approach 2:
The context analysis engine is designed as a universal system that can handle multiple types of IT incidents (communication issues, connection interruptions, performance degradation) and collect context information from various sources (client applications, server components, network infrastructure) through a single unified interface, reducing operational complexity.
3Device complexity
If connection interruption reasons are only available on the client side, then server-side analysis is simplified, but diagnostic completeness is reduced
Solution Approach 1:
The context analysis engine acts as an intermediary that automatically collects context information from both the client side (where connection interruption reasons are available) and the server side (where additional diagnostic information exists). It correlates this distributed information without requiring manual coordination between client and server teams.
4Productivity
If automated context analysis is implemented, then incident resolution speed increases, but system complexity increases
Solution Approach 1:
The automated analysis system is segmented into distinct functional modules: incident detection module, context information collection module (with client-side and server-side collectors), analysis engine, and countermeasure generation module. This segmentation allows each component to be independently developed and maintained, managing system complexity while achieving automated fast resolution.
Data Source
AI summary
A computer-implemented method may comprise detecting an occurrence of an information technology (IT) incident between a cloud service and a software application based on observability data of the cloud service, where the observability data indicates a current state of the cloud service, the cloud service runs within a first network, and the software application runs within a second network different from the first network. The computer-implemented method may further comprise obtaining context information for the IT incident from the second network in response to the detecting of the occurrence of the IT incident, where the context information indicating circumstances in which the IT incident occurred, and then determining a countermeasure for the IT incident based on the context information. The computer-implemented method may additionally comprise performing an action based on the countermeasure.