Automated Dataflow Management With Centralized Version Control
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Solution Overview
Problem
Existing systems lack the capability to manage dataflow scope and version control, do not provide user authorization, and lack scaling and continuous integration capabilities in automated dataflow systems, posing security and efficiency risks.
Innovation Solution
An integration and management system that manages automated dataflow servers, provides dataflow version control, user authorization, and scaling capabilities, and supports continuous integration and continuous delivery through a centralized registry and monitoring system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized management system is implemented to manage multiple dataflow instances, then dataflow version control and authorization are improved, but system complexity increases
Solution Approach 1:
The patent introduces a centralized registry as an intermediary component that manages dataflow instances, version control, and authorization. This registry acts as a mediator between users and multiple dataflow instances, coordinating deployment requests and tracking instance status without requiring direct complex interactions between all system components.
Solution Approach 2:
The centralized registry performs multiple functions including storing instance locators, tracking status indicators, managing version control information, and handling authorization. By consolidating these diverse functions into a single universal component, the system avoids the complexity of separate specialized systems for each function.
2Adaptability or versatility
If multiple dataflow instances are deployed across different servers, then system scalability is improved, but monitoring and management difficulty increases
Solution Approach 1:
The system implements feedback mechanisms where dataflow instances report their status indicators back to the centralized registry, and the registry provides deployment instructions based on current system state. This continuous feedback loop enables automated monitoring and management of distributed instances, reducing the complexity of managing multiple servers.
Solution Approach 2:
Dataflow instances automatically register themselves with the centralized registry and provide self-reported status information. The registry autonomously processes deployment requests and allocates instances based on current capacity and requirements, reducing the need for manual management intervention across multiple servers.
3Productivity
If automated deployment processes are implemented, then deployment efficiency is improved, but security risks increase due to lack of authorization
Solution Approach 1:
The system implements preliminary authorization checks before deployment actions are executed. The centralized registry stores authorization information and validates user permissions before processing deployment requests, ensuring security constraints are established in advance rather than added as a separate step after automated deployment processes begin.
Data Source
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AI summary
Methods, apparatuses, and systems for integrating and managing automated dataflow systems are provided. An example method may include receiving a dataflow request from a tenant device; retrieving dataflow data associated with a plurality of instances from a flow and status registry; and determining a selected instance from the plurality of instances based on the dataflow data.