Data Flow Node Provisioning with Runtime Resource Estimation
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Solution Overview
Problem
Conventional techniques for designing and implementing data flow pipelines require specialized knowledge and significant time, hindering user access due to complexity, leading to inefficiencies in resource utilization.
Innovation Solution
A system that supports visual design and deployment of data flow pipelines with node validation and provisioning techniques, allowing for real-time management and automatic adjustments to ensure efficient operation without preemption or starvation, using a graphical user interface to select and connect nodes representing data science algorithms and estimating runtime resource provisioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques are used to design and implement data flow pipelines, then the pipelines can be functional and operational, but the process requires specialized knowledge and significant time, hindering user access
Solution Approach 1:
The patent introduces an automated provisioning system that acts as an intermediary between the user and the complex data flow pipeline implementation. This system automatically generates deployment configurations, manages resource allocation, and handles node provisioning, thereby shielding users from the underlying complexity while ensuring functional reliability
Solution Approach 2:
The system implements self-service capabilities through automated configuration generation and self-provisioning mechanisms. The provisioning system automatically adapts to available resources and configures pipelines without requiring manual intervention or specialized knowledge from users, reducing both time and complexity barriers
2Reliability
If conventional techniques are used to design and implement data flow pipelines, then the pipelines can be functional, but a significant amount of time is required to perform even by a technician with specialized knowledge
Solution Approach 1:
The patent implements preliminary action through pre-defined templates, automated configuration generation, and upfront resource assessment. The system prepares deployment configurations and validates pipeline designs before actual deployment, preventing time-consuming manual adjustments and ensuring functional reliability from the start
Solution Approach 2:
The automated provisioning system performs self-service by automatically configuring pipelines, managing resources, and handling deployments without requiring manual intervention. This eliminates the time burden on technicians while maintaining functional reliability through automated validation and error handling
3Productivity
If runtime resource provisioning is adjusted without preemption or starvation, then efficient operation is ensured, but complex estimation and adjustment mechanisms are required
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor pipeline performance and resource utilization. The system uses this feedback to dynamically adjust resource provisioning, ensuring efficient operation while maintaining simplicity through automated control loops that balance productivity with manageable complexity
Data Source
AI summary
Data flow node validation and provisioning techniques are described. In one or more implementations, a system is described that supports visual design and deployment of data flow pipelines to process streaming data flows. The system may be configured to include nodes and connections between the nodes to represent an arbitrary execution graph of data science algorithms (as algorithm action components) that are used to process the streaming data flows. The system may also support validation techniques to verify that the data flow pipeline may operate as intended. Further, the system may also support implementation and provisioning techniques that involve estimation and adjustment of runtime resource provisioning of a deployed data flow pipeline without preemption or starvation occurring for nodes within the pipeline.