Data Release Manager for Multiple Service Cycles
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Solution Overview
Problem
Current approaches to servicing user requests at the frontend and backend fail to effectively manage multiple data release cycles and stages, leading to complexities in updating and rendering data, which negatively impacts user experience and resource utilization.
Innovation Solution
A system that includes a controller, configuration data engine, matching engine, and rendering engine to determine the appropriate release cycle and stage for user requests, ensuring seamless data retrieval and response generation, with features like atomic updates and debugging parameter-driven request forwarding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data files are updated on different schedules and made available during different stages of development, then the service can support multiple release cycles and stages, but it becomes complicated to manage which service front end and back end is loading what kind of data release files
Solution Approach 1:
The patent introduces a data release manager as an intermediary component that sits between the multiple service front ends/back ends and the various data release files. This manager maintains a data release registry that tracks which services are using which data releases, and it automatically routes services to the appropriate data files based on their release cycle and stage requirements. This intermediary abstraction layer eliminates the complexity of direct management while preserving support for multiple release cycles and stages.
Solution Approach 2:
The data release manager is designed as a universal system that can handle multiple service front ends and back ends across different release cycles and stages through a single unified interface. Rather than requiring separate management mechanisms for each service or release type, the universal manager provides a common platform that adapts to various release scenarios, thereby reducing overall system complexity while maintaining versatility.
2Adaptability or versatility
If updates are pushed out on different schedules for test, beta or production stage, then the service can accommodate different development stages, but it negatively impacts on providing a seamless user experience
Solution Approach 1:
The data release manager acts as a mediator that ensures seamless transitions between different development stages. It maintains the data release registry to track which data files are associated with which stages (test, beta, production), and it automatically routes users to the appropriate stage-appropriate data releases. This mediation ensures that users experience consistent, stage-appropriate functionality without noticing the underlying complexity of multiple update schedules.
Solution Approach 2:
The system performs preliminary actions by pre-configuring the data release registry with all necessary data files and their associated stage information before users access the service. The data release manager proactively determines which stage a user should access and prepares the appropriate data release routing in advance, ensuring seamless user experience without requiring users to manually switch between stages or experience disruptions during transitions.
Data Source
AI summary
A system and method for serving requests using multiple release cycles is disclosed. The data release application includes a controller, a configuration data engine, a matching engine and a rendering engine. The controller receives a request from a client. The configuration data engine determines a set of criteria and a collection of release datasets corresponding to configuration data. The matching engine matches the request with the set of criteria and determines a combination of release cycle and release stage for servicing the request. The rendering engine retrieves a release dataset from the collection of release datasets that corresponds to the combination of release cycle and release stage and generates a response based on the release dataset.