Runbook Deployment Confidence Evaluation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In information technology systems, when failures occur, support teams face challenges in diagnosing and fixing issues due to the complexity across multiple layers, and existing runbooks may not be available for all types of failures, leading to manual and potentially risky operator interventions.
Innovation Solution
A computer-implemented method and system for runbook deployment based on confidence evaluation, which determines the aggregated skill level of operators and generates a confidence measure for the runbook, ensuring that only reliable runbooks are deployed, thereby mitigating the risk of negative consequences on live systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If runbooks are automatically generated from operator commands, then the quantity of runbooks increases and response time improves, but the reliability decreases due to potential errors from less skilled operators
Solution Approach 1:
The system evaluates and assigns different quality levels to runbooks based on the skill level of the specific operator who generated them. High-skill operators generate high-quality runbooks that can be automatically deployed, while low-skill operators generate runbooks requiring review. This local quality assessment resolves the contradiction by ensuring reliability varies appropriately with the source operator's expertise.
Solution Approach 2:
The system changes the deployment parameter (automatic vs. manual review) based on the operator's skill level parameter. By dynamically adjusting the deployment process according to operator competency, the system maintains high productivity while ensuring reliability through selective manual review of runbooks from less experienced operators.
2Reliability
If manual review of generated runbooks is performed, then the reliability of deployed runbooks improves, but the time and resources required for deployment increase
Solution Approach 1:
Instead of universally reviewing all runbooks manually, the system applies partial review action only to runbooks generated by low-skill operators or those with low confidence scores. High-skill operators' runbooks proceed with automatic deployment, reducing overall deployment time while maintaining reliability through targeted manual review where most needed.
Solution Approach 2:
The system enables self-service deployment for high-quality runbooks generated by skilled operators, allowing them to be deployed automatically without manual intervention. This self-service mechanism reduces deployment time for reliable runbooks while manual review serves as a backup safety mechanism for lower-quality submissions.
3Productivity
If runbooks from all operators are deployed automatically, then the productivity of incident resolution improves, but harmful factors increase due to potential erroneous commands
Solution Approach 1:
The system applies preliminary anti-action by implementing a confidence evaluation and skill-level assessment mechanism before automatic deployment. Runbooks from low-skill operators or with low confidence scores are flagged for manual review, preventing potentially harmful erroneous commands from being automatically executed on live systems while still allowing rapid deployment of high-quality runbooks.
Data Source
AI summary
Runbook deployment based on confidence evaluation. Obtaining a runbook based on commands, where the commands relate to resolving an incident and determining an aggregated skill level of operators for the runbook based on historical resolutions of incidents by the operators. A confidence measure of the runbook is determined according to the aggregated skill level for the runbook. Deployment of the runbook is performed in accordance with the confidence measure.