Adaptive Workflow Manager for Cloud Infrastructure
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Solution Overview
Problem
Existing cloud computing services struggle to adapt to changes in infrastructure or processing environments, leading to decreased efficiency in pipelines and workflows.
Innovation Solution
The implementation of an adaptive workflow manager that uses planning algorithms and AI models to generate and adapt optimal pipelines and workflows based on developer objectives and context changes in the infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-defined pipelines and workflows are used, then implementation is simple, but adaptability to infrastructure changes is poor
Solution Approach 1:
The patent implements dynamic workflow management by using planning algorithms to automatically generate and adjust pipelines based on real-time infrastructure context. The system transitions from static pre-defined workflows to dynamic adaptive workflows that self-adjust to infrastructure changes, improving adaptability while managing complexity through automation.
Solution Approach 2:
The system incorporates feedback mechanisms where the planning algorithm continuously monitors infrastructure context and uses this information to adjust workflow pipelines. This feedback loop enables the system to adapt to changing conditions automatically, resolving the contradiction between adaptability and complexity through intelligent automation.
2Productivity
If manual workflow configuration is used, then control is precise, but efficiency decreases due to time consumption
Solution Approach 1:
The planning algorithm performs preliminary actions by pre-computing optimal pipeline configurations based on developer objectives and infrastructure context before execution is needed. This preliminary planning eliminates the need for manual configuration during execution, significantly improving productivity while reducing time loss through automated preparation.
Solution Approach 2:
The system implements self-service workflow configuration where the planning algorithm automatically generates and adjusts pipelines without requiring manual intervention. The system serves itself by using its own resources (planning algorithm, infrastructure context) to configure workflows, thereby improving efficiency and eliminating time-consuming manual configuration.
3Speed
If fixed pipelines are used, then implementation is straightforward, but responsiveness to context changes is slow
Solution Approach 1:
The patent transforms fixed pipelines into dynamic adaptive pipelines that can respond quickly to context changes. The planning algorithm continuously monitors infrastructure state and automatically adjusts workflows in real-time, enabling fast response to changes while managing system complexity through automated decision-making.
Solution Approach 2:
The system performs preliminary analysis of infrastructure context and pre-plans adaptive responses before changes occur. By continuously preparing and pre-computing optimal pipeline adjustments, the system achieves rapid response to context changes without the complexity overhead of reactive manual intervention.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed that optimize workflows. An example apparatus includes an intent determiner to determine an objective of a user input, the objective indicating a task to be executed in an infrastructure, a configuration composer to compose a plurality of workflows based on the determined objective, a model executor to execute a machine learning model to create a confidence score relating to the plurality of workflows, and a workflow selector to select at least one of the plurality of workflows for execution in the infrastructure, the selection of the at least one of the plurality of workflows based on the confidence score.