Legacy Software Horizontal Scaling via Virtual Machine Snapshots
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy medical software deployed on traditional servers faces challenges in horizontal scaling while maintaining configuration control and minimizing code changes, especially in compliance with quality control systems and regulatory requirements such as HIPAA and GDPR.
Innovation Solution
A method involving the use of automated pipelines to generate software build artifacts and release artifacts, allowing for the installation of these artifacts to create a snapshot or 'picture' of the legacy software on a server system. This snapshot is then hosted through a virtual machine scale set, enabling horizontal scaling in a cloud computing environment while maintaining configuration control and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If legacy software is deployed on traditional servers, then configuration control and regulatory compliance are maintained, but horizontal scaling capability is limited
Solution Approach 1:
The patent creates a virtual machine image containing the legacy software application and deploys multiple copies (instances) of this image to a cloud platform. This copying approach enables horizontal scaling by allowing the system to spin up additional instances of the legacy software without modifying the original application code, thus achieving scalability while preserving configuration control and regulatory compliance.
Solution Approach 2:
The patent introduces a virtual machine image as an intermediary layer between the legacy software and the cloud infrastructure. This intermediary encapsulates the legacy application in a standardized format that can be deployed across different cloud environments, enabling horizontal scaling while maintaining the software's original configuration control mechanisms and compliance characteristics.
2Productivity
If automated pipelines are used to generate build artifacts and release artifacts, then deployment efficiency and horizontal scaling are improved, but pipeline configuration and automation complexity increase
Solution Approach 1:
The patent implements automated pipelines that perform preliminary actions by pre-building and pre-testing the legacy software application, creating virtual machine images in advance, and preparing deployment configurations before actual deployment is needed. This preliminary action approach improves deployment efficiency by eliminating the need for manual configuration and testing during deployment, while the automation handles the complexity of pipeline management.
Solution Approach 2:
The automated pipelines are designed to self-manage the deployment process, automatically generating build artifacts, creating release artifacts, spinning up virtual machine instances, and handling scaling operations without manual intervention. This self-service capability improves deployment efficiency while the pipeline's automated nature manages the complexity of coordination between multiple deployment components.
3Reliability
If multiple instances of legacy software are deployed through virtual machine scale sets, then load balancing and security are improved, but infrastructure resource consumption increases
Solution Approach 1:
The patent implements a dynamic scaling mechanism where the number of virtual machine instances is automatically adjusted based on demand. The virtual machine scale set can dynamically add or remove instances as needed, allowing the system to maintain optimal reliability and security through load balancing while minimizing infrastructure resource consumption by only provisioning additional resources when actually required.
Solution Approach 2:
The system changes the parameter of instance count dynamically, allowing the deployment to scale from a single instance to multiple instances based on workload demands. This parameter change approach enables the system to maintain reliability and security through load balancing across multiple instances while reducing resource consumption by avoiding unnecessary instances during low-demand periods.
Data Source
AI summary
An example system and method are described to provide automated pipelines used to build a horizontally scaled computing system for legacy controlled software. In existing systems, many legacy software implementations cannot be re-worked or redesigned to horizontally scale, for example to implement in a cloud computing environment or implementation of virtual machines. The systems and methods described herein provide a pipeline to take legacy web-based software deployed on traditional servers and increase performance and security while maintaining configuration control and minimizing code changes to the legacy application.