Multi-Level Stack Deployment for Isolated Component Reuse
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Solution Overview
Problem
Existing software development paradigms face challenges in automating the deployment of software components across multiple stacks while maintaining operational isolation and resource efficiency, leading to increased costs and potential code overwriting or independent testing issues.
Innovation Solution
A Multi-Level Multi-Deployment (MLMD) model that automates the deployment of software components across different layers and stacks, using a Deployment as a Service (DaaS) to provision and configure isolated stacks, leveraging cloud provider-specific models to ensure operational independence and resource reuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate software stacks are provided to multiple developers for independent development and testing, then operational isolation and independent testing are ensured, but the number of stacks increases quickly leading to increased costs
Solution Approach 1:
The patent segments the software stack into multiple hierarchical levels (IaaS, PaaS, SaaS) that can be independently shared or isolated. This allows different portions of the stack to be reused across developers while maintaining isolation where needed, reducing the total number of stacks required.
Solution Approach 2:
The patent implements universal base stacks that can serve multiple developers simultaneously through controlled sharing mechanisms. The DaaS system enables a single stack instance to be universally accessed by multiple users with appropriate permissions, reducing duplication while maintaining operational isolation through configuration management.
2Quantity of substance
If software stacks are shared among multiple developers to reduce the number of stacks, then costs are reduced, but developers may have their code overwritten or be unable to test their versions independently
Solution Approach 1:
The patent implements dynamic stack provisioning where the DaaS system can dynamically create, configure, and isolate stack instances based on real-time development needs. Developers can dynamically request isolated environments for testing while sharing common infrastructure, with the system automatically managing the transitions between shared and isolated states.
Solution Approach 2:
The DaaS system acts as an intermediary layer between developers and the underlying software stacks. It manages the complexity of isolation and sharing by providing automated deployment, configuration management, and environment provisioning, allowing developers to work independently without directly managing stack isolation mechanics.
3Productivity
If manual or traditional deployment processes are used across multiple stacks, then operational control is maintained, but automation and efficiency are reduced
Solution Approach 1:
The patent implements self-service deployment capabilities where the DaaS system automatically provisions, configures, and deploys software components across stacks without manual intervention. The system autonomously manages resource allocation, environment configuration, and deployment orchestration, significantly improving efficiency while reducing operational complexity through automation.
Solution Approach 2:
The patent incorporates feedback mechanisms where the DaaS system continuously monitors deployment status, resource utilization, and operational metrics. This feedback enables automated adjustments and optimizations in the deployment process, improving efficiency while maintaining control through closed-loop management of the deployment lifecycle.
Data Source
AI summary
A method comprising: receiving a request for a new stack that is to comprise a plurality of components at a plurality of levels of the new stack, wherein the request indicates the supporting components; in response to the request: interacting with a cloud services provider to provision instances of the components of the new stack, wherein at least one the instances of the components of the new stack is included in another stack hosted by the cloud services provider; generating configuration mapping data that relate the instances of the components of the other stack with the new stack; converting the configuration mapping data to one or more cloud provider-specific models that are specific to the cloud services provider; and deploying the new stack at the cloud-services provider for use by the first user based on the one or more cloud provider-specific models.