Deployment Pipeline Automation Using DAG-Based Container Orchestration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing software deployment processes are complex, inefficient, and prone to technical debt due to the use of artisanal scripts that are not portable, require manual orchestration, and lack effective pipeline automation, making it difficult to manage containers and audit deployment errors.
Innovation Solution
A script automation processor with a GraphQL-based API is introduced to manage container instantiation and automate workflows, allowing developers to write small scripts that leverage API extensions for scalable and modular pipeline automation, ensuring portability and ease of maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If artisanal scripts are used for pipeline automation, then deployment can be automated, but the scripts become difficult to maintain and accumulate technical debt
Solution Approach 1:
The patent segments the deployment pipeline into modular, reusable script components that can be independently maintained and updated. This modularization allows specific parts of the pipeline to be repaired or modified without affecting the entire system, reducing technical debt while maintaining automation.
Solution Approach 2:
The patent creates universal script templates and functions that can be applied across multiple deployment scenarios and platforms. These standardized components reduce maintenance burden by providing consistent, tested patterns that work across different environments, eliminating the need to maintain separate artisanal scripts for each case.
2Productivity
If platform-specific scripts are written for cloud services, then deployment can be optimized for that platform, but the scripts become incompatible with other platforms and require rewriting
Solution Approach 1:
The patent develops universal deployment scripts that can operate across multiple cloud platforms and environments. By designing platform-agnostic script templates with configurable parameters, the system maintains high deployment efficiency while enabling easy adaptation to different platforms without complete rewriting.
Solution Approach 2:
The patent uses parameter-based configuration to adapt deployment scripts to different platforms. By changing parameters and configuration values rather than rewriting the entire script, the system achieves platform-specific optimization while maintaining portability and compatibility across different cloud services.
3Ease of operation
If manual orchestration of deployment workflows is performed, then flexibility and control are maintained, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent implements pre-configured deployment templates, scripts, and workflows that are prepared in advance. This preliminary action allows automated execution of complex deployment sequences without manual intervention during actual deployment, significantly reducing deployment time while maintaining the flexibility to customize configurations when needed.
Solution Approach 2:
The patent incorporates automated feedback mechanisms that monitor deployment progress, detect issues, and trigger appropriate responses. This feedback-driven automation maintains operational control by allowing the system to self-correct and adapt during deployment, reducing manual oversight time while preserving flexibility through automated decision-making.
4Adaptability or versatility
If custom automation platforms are implemented for enterprises, then specific organizational needs are met, but the implementation requires large up-front costs and is time-consuming
Solution Approach 1:
The patent segments the automation platform into modular, independently deployable components that can be selectively implemented based on organizational needs. This segmentation allows enterprises to start with essential features and gradually add customization, reducing up-front costs and implementation time while maintaining the ability to meet specific organizational requirements.
Solution Approach 2:
The patent implements a dynamic automation platform that can adapt its complexity level based on organizational needs. The system allows enterprises to configure the degree of customization and automation, enabling simple organizations to use basic templates while more complex organizations can implement advanced custom workflows, thereby matching platform complexity to actual requirements rather than imposing maximum complexity on all users.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In one embodiment, a computer-implemented method comprises using a script automation processor that is hosted using a virtual compute instance and a virtual storage instance associated with one or more second non-transitory computer-readable storage media storing one or more second sequences of instructions defining an API implementation of the API, a graph server, and one or more programming language runtime interpreters, receiving a user pipeline automation script comprising one or more first sequences of instructions specifying one or more API calls to an application programming interface (API), and a user application; using the script automation processor, creating and storing one or more programmatic containers in memory of the script automation processor, the containers corresponding to functions that user pipeline automation script and user application invoke; using the script automation processor, creating and storing a directed acyclic graph (DAG) in the memory of the script processor, the DAG comprising nodes and edges corresponding to dependencies of the containers; using the script automation processor, interpreting the user pipeline automation script using a particular programming language runtime interpreter among the one or more programming language runtime interpreters; using the script automation processor, running the user pipeline automation script to automatically build, test, or deploy the user application in a cloud computing service.