System Lab and SOP Framework for Cross-Platform Test Automation
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Solution Overview
Problem
Existing cloud computing systems face challenges with manual and time-consuming operations that can lead to human errors and unnecessary delays, resulting in potential cloud outages, particularly in managing large volumes of tickets and maintaining cloud operations.
Innovation Solution
A system lab framework that supports automated testing across multiple machines and environments, including Windows, Mac, and Linux, with a central data collection system to manage System Operating Procedures (SOPs) and store test results, allowing for parallel execution of actions and real-time monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operations are used to handle cloud maintenance tickets, then flexibility and adaptability are maintained, but productivity is reduced and human error increases
Solution Approach 1:
The system enables self-service automation where the cloud maintenance system automatically processes tickets, performs diagnostics, and executes remediation actions without human intervention. The automated ticket handling system reads live log data, applies SOPs, and resolves issues autonomously, eliminating manual operations while maintaining high reliability through consistent automated execution.
Solution Approach 2:
Manual mechanical operations are replaced with an automated digital system. The patent substitutes human operators with an automated framework that reads log data, processes tickets through defined SOPs, and executes actions programmatically. This replacement eliminates human error while improving productivity through faster automated response times.
2Productivity
If automated actions are implemented to maintain cloud systems, then productivity and reliability are improved, but device complexity increases
Solution Approach 1:
The automated system is segmented into distinct modular components: a ticket reading module that ingests live log data, a SOP selection module that matches issues to predefined procedures, an execution module that performs actions, and a monitoring module that tracks results. Each component has a specific function, reducing overall system complexity while maintaining high productivity through coordinated automated operations.
Solution Approach 2:
The system manages complexity by parameterizing SOPs with configurable conditions, actions, and priorities. Rules can be defined with adjustable parameters such as execution thresholds, time windows, and resource limits. This parameterization allows the automated framework to handle diverse cloud maintenance scenarios without requiring complex hard-coded logic for each case.
3Productivity
If multiple SOPs are grouped and executed in parallel across different buckets, then productivity increases through concurrent processing, but device complexity and coordination requirements increase
Solution Approach 1:
SOPs are organized into separate executable buckets that can be processed in parallel. Each bucket represents an independent unit of work with its own set of SOPs and execution context. This segmentation enables concurrent processing across multiple cloud systems or ticket types while isolating coordination complexity within each bucket, allowing scalable parallel execution without system-wide complexity.
Data Source
AI summary
The present disclosure relates to systems and methods for a system lab and SOP framework to support testing based on customer environments. Longevity testing must be run on every build with different test cases; thus, the system lab framework allows this testing to be performed on multiple machines in a single run, also allowing test results to be stored. The system lab framework is adapted to recreate customer issues, allowing different environments typically not accessible to be replicated and tested. The system lab framework includes central code to trigger cases on different machines. A central data collection system is able to collect all of the results from the cases and store the respective data. This system lab framework is adapted to support multiple Operating Systems (OS) including Windows, Mac, Linux, and the like.