Drag-and-Drop DevOps Pipeline Configuration
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Solution Overview
Problem
Current DevOps platforms and pipelines require significant time and human resources for configuration and execution, often involving manual processes and limited flexibility due to restricted resource configurations and tool choices, which hinders agility and automation in software delivery.
Innovation Solution
The development of declarative and policy-based pipelines that allow users to build and orchestrate pipelines across multiple cloud environments and tools with customer-choice flexibility, using a unified console for task execution and automation, reducing the need for custom code and enabling drag-and-drop workflow management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual processes are used for DevOps pipeline configuration and execution, then flexibility in tool selection and customization is maintained, but significant time and human resources are required
Solution Approach 1:
The DevOps pipeline configuration is segmented into reusable template components that can be independently selected and combined. Users can choose from predefined pipeline templates for different scenarios (CI/CD, testing, deployment) and customize specific stages without configuring the entire pipeline manually, thus reducing configuration time while maintaining flexibility.
Solution Approach 2:
Pre-configured pipeline templates and best practice configurations are prepared in advance with common toolchains and workflows already established. These templates include pre-defined stages, tools, and parameters that can be directly applied to new projects, eliminating the need to build pipelines from scratch while allowing customization through parameter adjustment.
2Adaptability or versatility
If manual processes are used for DevOps pipeline configuration and execution, then customization capability is maintained, but human resources are significantly expended
Solution Approach 1:
Existing successful pipeline configurations are copied as templates that can be reused across multiple projects and teams. The template system allows copying of entire pipeline definitions, tool configurations, and stage settings, which can then be adapted through parameter customization rather than manual recreation, significantly improving productivity while preserving customization capability.
Solution Approach 2:
The pipeline template system is designed to be universal, supporting multiple toolchains and deployment scenarios through a single configurable framework. Templates can be parameterized to work across different projects, teams, and environments, allowing one template to serve multiple functions and reducing the need for separate manual configurations for each scenario.
3Reliability
If restricted resource configurations are imposed by platform providers, then platform stability and manageability are improved, but customer flexibility and tool choice are limited
Solution Approach 1:
The platform provides dynamic configuration capabilities where resource allocations and toolchain selections can be adjusted based on project requirements while maintaining platform stability. The system allows customers to dynamically select from approved tool catalogs and configure resource parameters within defined boundaries, balancing platform manageability with customer flexibility through programmable interfaces.
4Ease of operation
If extensive manual configuration is required for DevOps pipelines, then precise control over each pipeline element is achieved, but the development lifecycle is lengthened
Solution Approach 1:
Pipeline templates include pre-configured best practices, approved toolchains, and optimized stage sequences that provide precise control over pipeline elements while eliminating the need for manual configuration of common parameters. The templates embed control precision requirements directly into the template definitions, allowing users to achieve precise control through template selection and parameter adjustment rather than extensive manual configuration.
Data Source
AI summary
The present invention extends configuring development and operations pipelines using drag and drop techniques. Through user interface gestures, users can form and manage pipelines that span any combination of: public cloud resources, private cloud resources, user on-premise resources, etc., in accordance with appropriate (cloud and/or on-premise) profile information. The user interface facilitates pipeline (re)configuration as appropriate to address alterations to workflows, upgrades to DevOps tools, removal of functionality from a workflow, etc. The user interface enables customers to build no-code pipelines for various use cases in a drag and drop manner. Users can integrate collaboration tools, notifications, and approval gates offering thresholds at each and every step. In addition, the pipeline framework captures logs and provides a summary via livestream and also upon completion of each pipeline activity and after each pipeline.