Dynamic Pipeline Automates Multi-Cloud Infrastructure Deployment
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Solution Overview
Problem
Current software tools for Infrastructure as Code (IaC) lack features for orchestration and automation of infrastructure deployment across different cloud service providers, and are not capable of modularizing the deployment process or automating governance validation checks.
Innovation Solution
A dynamic pipeline system that automates software application infrastructure deployment in a cloud computing environment, using modularization and control abstraction, allowing deployment without expertise in specific modularization platforms, and enforcing governance validation during the initial stage of development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing IaC tools are used for infrastructure deployment, then deployment automation is achieved, but the tools lack multi-cloud compatibility and cannot be adapted to different service providers
Solution Approach 1:
The deployment system is segmented into modular components including pre-coded resource configuration modules, compliance validation modules, and cloud provider adapter layers. Each module handles specific aspects of deployment independently, enabling multi-cloud support without requiring complete system redesign for each cloud provider.
Solution Approach 2:
An intermediary deployment pipeline is introduced between the infrastructure code and cloud provider resources. This pipeline translates high-level infrastructure definitions into provider-specific configurations, allowing the same IaC tools to deploy to multiple cloud providers through standardized interfaces.
2Productivity
If manual infrastructure provisioning is performed, then flexibility and control are maintained, but deployment time and effort increase significantly
Solution Approach 1:
Resource configuration modules and compliance policies are prepared in advance and stored in a repository. During deployment, these pre-configured modules are automatically selected and executed, eliminating the need for manual configuration during deployment and significantly reducing deployment time.
Solution Approach 2:
The deployment system performs self-validation through automated compliance checking and error detection before deployment execution. This self-service capability identifies and corrects issues automatically without requiring manual review, accelerating the deployment process while maintaining quality control.
3Reliability
If infrastructure deployment is automated without validation, then deployment speed increases, but compliance and security risks increase
Solution Approach 1:
Compliance validation modules provide feedback loops that automatically check infrastructure configurations against defined policies before deployment. The system validates resource configurations, detects compliance violations, and prevents deployment of non-compliant infrastructure, ensuring reliability while maintaining automated workflows.
4Productivity
If infrastructure changes are deployed rapidly, then productivity improves, but the risk of errors and security issues increases
Solution Approach 1:
Error detection and compliance validation are performed as preliminary actions before infrastructure deployment executes. The system checks for configuration errors, security vulnerabilities, and policy violations in advance, preventing erroneous deployments while maintaining rapid provisioning capabilities through automated validation.
Data Source
AI summary
Methods and apparatuses for automating software application infrastructure deployment in a cloud computing environment include defining hierarchical infrastructure layers for a software application, generating a deployment pipeline for the software application comprising pre-coded resource configuration modules, and triggering execution of the deployment pipeline to deploy the software application in the cloud computing environment.