Autonomous Information Provider for Development Data Retrieval
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Solution Overview
Problem
Current processes for resolving issues in computing environments during development and testing are tedious and manual, requiring testers and developers to manually query ticketing systems, documentation databases, and messaging systems, leading to inefficiencies in finding and filtering relevant information.
Innovation Solution
An autonomous information provider system that periodically queries and formats documents from approved internal sources, creating a master repository and providing real-time access to proprietary documentation, ticket information, and messages, eliminating the need for manual searching and filtering through an overarching program that monitors systems under test.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual querying of ticketing systems, documentation databases, and messaging systems is performed, then relevant information can be found, but the process is tedious and time-consuming
Solution Approach 1:
The system performs self-service by automatically querying multiple data sources, correlating metadata, and generating merged collections without human intervention. The autonomous information provider continuously monitors and updates the master repository, eliminating the need for manual information gathering and filtering operations.
Solution Approach 2:
The system performs preliminary actions by proactively querying data sources and pre-processing information before it is needed. The autonomous information provider continuously updates the master repository with correlated data from multiple sources, so that when queries are made, the information is already organized and ready for retrieval.
2Productivity
If an autonomous information provider system is implemented to automate searching and filtering, then efficiency is improved and manual labor is reduced, but system complexity increases
Solution Approach 1:
The system is segmented into distinct functional components: the autonomous information provider that queries data sources, the metadata correlation engine that processes and links data, the master repository that stores merged collections, and the query interface that users interact with. This segmentation allows each component to be developed, maintained, and scaled independently while working together to achieve high productivity.
Data Source
AI summary
Aspects of the invention include a method for providing a master computing environment containing a master repository. The method periodically conducts a search of proprietary data repositories and causes the master computing environment to create a merged collection in the master repository after the periodical conducted search of the proprietary data repositories. The method correlates metadata with the proprietary data repositories and puts the correlated metadata into the master repository. The method sets up a question feeder server to receive queries and to pass the queries to the master computing environment. The method causes the master computing environment to provide results in response to a query, where the master computing environment acts as an autonomous information provider that finds and sorts subject matter on a proprietary development project.