Decoupled Policy Layer for Data Pipeline Flexibility
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Solution Overview
Problem
Existing data pipeline systems require time-consuming updates when system settings or constraints change, often leading to inefficient or noncompliant data handling due to tightly coupled pipeline definitions that are specific to particular implementations, and developers may not be aware of changes necessitating updates.
Innovation Solution
Implementing separate pipeline and policy declarations, where a server receives a pipeline definition for data operations and a policy definition with additional instructions, allowing the server to create an execution plan by layering policy into the pipeline definition, enabling flexible and efficient handling of system updates without altering the pipeline definition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If data pipeline definitions are tightly coupled to specific implementations, then the pipeline can be optimized for particular cloud platforms or network devices, but the pipeline requires time-consuming updates when system settings or constraints change
Solution Approach 1:
The patent segments the data pipeline definition into two independent parts: a platform-agnostic pipeline definition and platform-specific policy definitions. This segmentation allows the core pipeline logic to remain unchanged while only the policy layer needs updating when platform settings change, resolving the contradiction between optimization and adaptability.
Solution Approach 2:
The patent introduces dynamic policy definitions that can be updated independently of the pipeline definition. The system dynamically applies policies to pipeline definitions based on platform-specific requirements, allowing the pipeline to adapt to changing system settings without requiring complete redefinition.
2Reliability
If developers manually update pipeline definitions when system constraints change, then the pipeline can comply with new settings, but developers may not be aware of changes and the process is time-consuming
Solution Approach 1:
The system implements self-service by automatically detecting changes in system settings and generating updated policy definitions. The platform automatically applies these policies to existing pipeline definitions, eliminating the need for developers to manually monitor and update pipelines, thus maintaining compliance while improving ease of operation.
Solution Approach 2:
The patent establishes a feedback mechanism where the system monitors changes in system constraints and automatically communicates necessary pipeline updates to developers. This feedback loop ensures developers are informed of required changes without needing to continuously monitor system settings themselves.
3Adaptability or versatility
If separate pipeline and policy declarations are implemented, then updates to system policies do not affect pipeline definitions, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary policy layer that sits between the pipeline definition and the execution environment. This policy intermediary handles all platform-specific adaptations, allowing the core pipeline definition to remain simple and unchanged while the intermediary manages the complexity of policy application and interpretation.
Data Source
AI summary
Methods, systems, and devices for data processing are described. In some systems, data pipelines may be implemented to handle data processing jobs. To improve data pipeline flexibility, the systems may use separate pipeline and policy declarations. For example, a pipeline server may receive both a pipeline definition defining a first set of data operations to perform and a policy definition including instructions for performing a second set of data operations, where the first set of data operations is a subset of the second set. The server may execute a data pipeline based on a trigger (e.g., a scheduled trigger, a received message, etc.). To execute the pipeline, the server may layer the policy definition into the pipeline definition when creating an execution plan. The server may execute the execution plan by performing a number of jobs using a set of resources and plugins according to the policy definition.