Script Automation Processor for Modular CI/CD Pipeline Management
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Solution Overview
Problem
Existing technologies face challenges in efficiently deploying computer program applications to distributed computing systems, particularly in managing containers and automating deployment pipelines, which leads to complexity and inefficiency.
Innovation Solution
The implementation of a script automation processor and API that allows for incremental evolution of pipeline automation scripts, enabling modularization and reuse of automation logic, and providing automatic container management through a GraphQL-based API.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional scripts are used for pipeline automation, then automation capability is achieved, but device complexity and maintenance difficulty increase
Solution Approach 1:
The patent introduces an intermediary system that sits between the user and the complex pipeline automation infrastructure. This intermediary provides a simplified interface that translates high-level user intentions into detailed automation scripts, thereby achieving pipeline automation without requiring users to directly manage complex scripts. The intermediary handles the complexity internally while presenting a simple interface to users.
Solution Approach 2:
The patent segments the pipeline automation process into distinct, manageable components or modules. Each module handles a specific aspect of pipeline automation (e.g., build, test, deploy), allowing the overall complex automation task to be broken down into simpler, independently manageable units. This segmentation reduces the perceived complexity while maintaining full automation capability.
2Extent of automation
If custom automation scripts are created, then specific workflow automation is achieved, but ease of operation and portability deteriorate
Solution Approach 1:
The patent implements a universal automation framework that can handle multiple different workflows and pipelines through a single standardized interface. The system is designed to be multi-functional, accommodating various automation scenarios (different CI/CD pipelines, build processes, test suites) without requiring custom scripts for each case. This universality improves ease of operation and portability while maintaining comprehensive automation capability.
Solution Approach 2:
Instead of requiring users to write scripts that adapt to specific platforms or environments, the patent inverts the approach by having the automation system adapt to user-defined workflows. The system provides platform-agnostic automation capabilities that work across different environments without requiring users to modify their automation logic for portability, thereby improving ease of operation while maintaining workflow automation.
3Reliability
If comprehensive container management is implemented, then deployment control is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service container management where the system automatically handles container lifecycle operations (creation, deployment, management, termination) without requiring manual intervention or complex user configuration. The automation framework includes built-in container management capabilities that operate autonomously, improving deployment control while hiding the underlying complexity from users. The system manages containers itself rather than requiring users to directly manage them.
Data Source
AI summary
In one embodiment, using a script automation processor hosted using a virtual compute instance and a virtual storage instance associated with media storing sequences of instructions defining an API implementation of an API, a graph server, and programming language runtime interpreters, a method includes obtaining access to a user pipeline automation script comprising sequences of instructions specifying API calls to the API, creating and storing modules extending the API from the user pipeline automation script, wherein some of the modules are re-usable, creating and storing programmatic containers corresponding to the modules, creating and storing a directed acyclic graph (DAG) comprising nodes and edges corresponding to dependencies of the containers, interpreting each module using a particular programming language runtime interpreter among the programming language runtime interpreters, installing the modules in association with the API implementation.