Cross-platform Data Synchronization Framework
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Solution Overview
Problem
Current solutions for integrating data between cloud-based platforms face challenges in inter-platform communication, data representation, and data correctness, leading to customized and ad-hoc point solutions that are not easily reusable across different platform pairs.
Innovation Solution
A comprehensive software infrastructure for inter-platform communication is provided, enabling identification of triggers, data transmission, and interface management between remote network management platforms and other cloud-based platforms, using procedures for queuing and transforming data to ensure synchronization and secure integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If customized point solutions are developed for each platform integration, then data synchronization between specific platform pairs can be achieved, but the complexity of integration increases and solutions cannot be easily reused across different platform pairs
Solution Approach 1:
The patent implements a universal data synchronization framework that can handle multiple platform integrations through a single standardized interface. The system uses platform-agnostic data models and transformation rules that work across different cloud-based platforms, eliminating the need for customized point solutions for each platform pair while maintaining reliable data synchronization.
Solution Approach 2:
The integration system is divided into modular components including data extraction modules, transformation modules, and loading modules that can be independently configured for different platforms. This segmentation allows the same framework to be reused across multiple platform pairs by simply changing the configuration parameters rather than developing entirely new customized solutions.
2Manufacturing precision
If platform-specific integration solutions are created, then data correctness for specific applications can be ensured, but the ability to leverage solutions across different platform pairs is reduced
Solution Approach 1:
The system maintains data correctness across different platforms by using parameter-driven configuration rather than hard-coded platform-specific logic. Transformation rules and data models are defined with adjustable parameters that can be configured for different platform pairs, allowing the same core solution to adapt to various platforms while ensuring data correctness through standardized validation and transformation processes.
3Ease of operation
If ad-hoc integration procedures are implemented, then specific data transmission requirements can be met, but the overall system complexity and development time increase
Solution Approach 1:
The patent implements pre-configured data models, transformation templates, and integration patterns that can be directly applied to common platform integration scenarios. This preliminary preparation eliminates the need for ad-hoc development for each integration, reducing development time while maintaining the ability to meet specific data transmission requirements through configuration rather than custom coding.
Data Source
AI summary
Persistent storage may contain: (i) a database table containing entries, (ii) a definition of a communication endpoint of a remote system, and (iii) outbound flow processing. One or more processors may be configured to: detect a state change associated with a local entry in the database table; read, from the database table, a set of data representing the local entry; transform, using the outbound flow processing, the set of data into a format receivable by the remote system; create, for the set of data, a correlation record that contains a local correlation identifier, wherein the correlation record specifies the local entry; transmit, to the remote system, the set of data as transformed and the local correlation identifier; receive, from the remote system and for the set of data, a remote correlation identifier; add, to the correlation record, the remote correlation identifier; and write, to a correlation table, the correlation record.