Generative AI Event Orchestration for Distributed DevOps Pipelines

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Solution Overview

Problem

Current distributed DevOps environments rely heavily on manual intervention, leading to bottlenecks, errors, and inconsistent workflows, which hinder efficiency and scalability, particularly in tasks such as task management, data creation, environment preparation, and production installation.

Innovation Solution

Utilizing Generative Adversarial Networks (GANs) to interpret UML diagrams and design documents, extract relevant information, and automate event orchestration by integrating with DevOps tools, analyzing dependencies, and continuously learning to generate and optimize DevOps event task rules.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual intervention is used in DevOps pipelines, then flexibility and control are maintained, but efficiency and speed are reduced due to bottlenecks

Engineering Contradiction:

ImproveDevOps pipeline efficiencyVSAvoidManual intervention level

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The system enables self-service automation where the DevOps pipeline automatically generates events, creates tasks, and orchestrates workflows without human intervention. The event orchestration engine autonomously processes pipeline events and triggers appropriate tasks based on predefined rules and contextual understanding.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical operations are replaced with an intelligent event orchestration system that uses natural language processing and contextual analysis to automatically generate and manage DevOps tasks, substituting human operators with an automated AI-driven mechanism.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If manual steps are used in DevOps pipelines, then adaptability to specific cases is maintained, but consistency and reliability deteriorate due to human errors

Engineering Contradiction:

ImprovePipeline consistencyVSAvoidManual operation level

Core Design Contradiction:

ReliabilityVSExtent of automation

Solution Approach 1:

The system implements feedback loops where the event orchestration engine continuously monitors pipeline execution, learns from outcomes, and refines its task generation and orchestration decisions, ensuring consistent and reliable automation while adapting to new scenarios.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Human manual operations are replaced with an automated event-driven system that uses contextual analysis and predefined rules to consistently generate and orchestrate tasks, eliminating human errors while maintaining adaptability through intelligent processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of time

If manual task creation and management is performed, then customization to specific needs is possible, but time consumption and resource usage increase

Engineering Contradiction:

ImproveTask creation timeVSAvoidManual task management level

Core Design Contradiction:

Loss of timeVSExtent of automation

Solution Approach 1:

The system performs preliminary actions by pre-defining event patterns, task templates, and orchestration rules that enable automatic task creation and management. When pipeline events occur, the system instantly generates and executes tasks without requiring manual intervention, significantly reducing time loss.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The event orchestration engine provides self-service functionality by automatically creating, managing, and executing DevOps tasks based on pipeline events, eliminating the need for manual task creation and management while maintaining full customization through contextual understanding.

Inventive Principle:

Principle #25Self-service

4Adaptability or versatility

If distributed DevOps teams are used, then collaboration and scalability are improved, but coordination complexity and communication overhead increase

Engineering Contradiction:

ImproveDistributed team collaborationVSAvoidOrchestration system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The event orchestration engine provides universal functionality by handling multiple types of pipeline events, task types, and coordination scenarios through a single unified system. This multi-functional approach simplifies the orchestration complexity while supporting distributed team collaboration across various DevOps processes.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250217740A1Orchestrate events in Distributed DevOps Apparatus Leveraging Generative AI

Publication Date: 2025.07.03 BANK OF AMERICA CORP

AI summary

Systems and methods for orchestrating events in distributed DevOps apparatus leveraging generative AI are disclosed to automate and streamline software development and deployment in distributed DevOps environments using Generative Adversarial Networks (GANs) and other AI techniques. The method involves interpreting UML diagrams, design documents, or the like with generative AI and computer vision to create DevOps tasks, integrating with various DevOps tools for task management, and deploying generated rules for automated event execution. Metadata is generated and processed in order to facilitate AI analysis. The systems and methods reduce manual intervention, increase efficiency, and improve accuracy, scalability, security, and compliance in DevOps workflows.