Cross-Cloud Orchestration for Multi-Protocol Analytics
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Solution Overview
Problem
The challenge lies in creating a shared architecture that facilitates the development and execution of analytics across multiple research domains with diverse requirements and outcomes, particularly in handling vast amounts of data for decision-making purposes, where each domain has distinct expectations for result usage.
Innovation Solution
The cross-cloud orchestration system enables the execution of analytic workflows across various analytics computing environments with different access protocols, utilizing a command and control framework to generate and transmit native access requests, ensuring data integrity and reliability through storage and ingestion processes, and visualizing results for informed decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a shared architecture is created to facilitate analytics across multiple research domains, then adaptability and versatility are improved, but device complexity increases
Solution Approach 1:
The patent implements a universal command and control framework that can execute analytic workflows across multiple diverse analytics computing environments. The system uses a standardized interface layer that translates domain-specific requests into environment-specific commands, allowing one system to perform multiple functions across different research domains while maintaining a consistent user experience.
Solution Approach 2:
The patent introduces an intermediary command and control framework that sits between the user and multiple analytics computing environments. This mediator translates high-level workflow definitions into environment-specific execution commands, handling protocol conversions and environment-specific requirements without exposing complexity to the user.
2Adaptability or versatility
If native access requests are generated for different analytics computing environments, then adaptability is improved, but ease of operation deteriorates
Solution Approach 1:
The command and control framework automatically generates the appropriate native access requests for each analytics computing environment based on the workflow definition. The system self-adapts to different environments by selecting and configuring the correct protocols and parameters without requiring manual intervention from the operator.
Solution Approach 2:
The framework acts as an intermediary that handles the complexity of generating environment-specific access requests. It translates a single unified workflow definition into multiple environment-appropriate requests, shielding the user from the operational complexity of dealing with different protocols and environment requirements.
3Productivity
If data is extracted and stored from vast amounts of information, then productivity is improved, but reliability of derivation worsens
Solution Approach 1:
The patent implements feedback mechanisms that track and verify data extraction and storage processes. The system monitors the derivation chain from raw information to extracted knowledge, enabling validation of each transformation step and ensuring that productivity gains do not compromise the reliability of the derived information.
Data Source
AI summary
A system, apparatus, article of manufacture, method, and computer program product are disclosed for a cross-cloud orchestration of data analytics. A system operates by receiving one or more command and control (C&C) requests to execute one or more analytic applications of a workflow. The workflow includes the analytic applications for execution. The system further operates by generating one or more native access requests to execute the analytic applications at one or more analytics computing environments, and transmitting one or more native access requests to the analytics computing environments, wherein at least two native access requests are configured for different access protocol.