Composite Pipeline Framework for Scalable Distributed Systems
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Solution Overview
Problem
Existing software frameworks lack the ability to create highly scalable and composable systems that can seamlessly integrate on-premise and cloud-based services, limiting their flexibility and scalability in handling complex and distributed processes.
Innovation Solution
A composite pipeline framework is introduced, comprising a cooperative collection of interfaces and classes that enable the creation of systems with independent processors connected via input-output connectors, allowing for dynamic reconfiguration and communication across different machine boundaries, supporting hybrid cloud services and micro-service architectures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a software framework uses a fixed, monolithic architecture, then it provides simple structure and ease of implementation, but it lacks scalability and flexibility for complex distributed systems
Solution Approach 1:
The system is divided into independent processors that can be individually developed, deployed, and scaled. Each processor handles specific tasks and communicates through standardized connectors, allowing the system to grow by adding modular components rather than redesigning the entire architecture.
Solution Approach 2:
Standardized connectors and interfaces are designed to work across different processor types and deployment environments. The same connector patterns enable both on-premise and cloud-based services to interoperate, providing universal communication mechanisms that support multiple functions and deployment scenarios.
2Adaptability or versatility
If processors are tightly coupled in a single process space, then communication is simple and fast, but the system cannot communicate across different machine boundaries
Solution Approach 1:
Connectors serve as intermediary components that mediate communication between processors. These connectors handle the complexity of cross-machine communication, serialization, and protocol management, allowing processors to remain simple while enabling versatile communication across different boundaries.
3Productivity
If the system is designed for distributed execution across multiple machines, then scalability and parallel execution are improved, but system configuration and deployment become more complex
Solution Approach 1:
The system allows dynamic configuration of processor connections and deployment topologies. Processors can be dynamically added, removed, or reconfigured at runtime, and the framework supports both synchronous and asynchronous execution modes that can be adjusted based on operational requirements rather than being fixed at compile time.
Data Source
AI summary
A software framework is disclosed. The framework defines a system of a plurality of independent processors including compatible processors. A composite processor is created from the compatible processors.


