Virtual Machine Launcher Automation for Secure Container Workloads
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Solution Overview
Problem
Existing container orchestration architectures face security issues and increased workload deployment times due to the manual deployment of application workloads in virtual machines, exposing user data and requiring user login.
Innovation Solution
Automatically deploying application workloads in containers within virtual machines using custom resource definitions, eliminating the need for user login through a virtual machine launcher and workload interpreter, which generates and configures virtual machines and containers based on predefined definitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual deployment of application workloads in virtual machines is used, then user data can be accessed and workloads can be deployed, but security issues arise due to user login requirements and exposure of user data
Solution Approach 1:
The system enables self-service deployment where the virtual machine launcher and workload interpreter automatically deploy application workloads without requiring user login. The virtual machine launcher receives custom resource definitions, starts virtual machines automatically, and the workload interpreter generates and deploys containers automatically, eliminating the need for manual user authentication while maintaining secure deployment operations.
Solution Approach 2:
The patent introduces intermediary components including the virtual machine launcher and workload interpreter that act as mediators between users and the virtual machine/container infrastructure. These intermediaries receive custom resource definitions, process deployment requests, and execute workloads automatically, thereby eliminating direct user login requirements while maintaining security through controlled intermediary processing.
2Productivity
If manual deployment processes are used, then users can control workload deployment, but deployment time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by pre-defining custom resource definitions that contain all necessary configuration information for virtual machine and container deployment. The virtual machine launcher and workload interpreter have pre-configured automation logic that processes these definitions immediately upon receipt, eliminating manual deployment steps and significantly reducing workload start times while maintaining user control through the definition interface.
Solution Approach 2:
The patent replaces manual mechanical deployment operations with automated computer-based processes. The virtual machine launcher automatically starts virtual machines based on custom resource definitions, and the workload interpreter automatically generates and deploys containers without manual intervention. This substitution of manual operations with automated systems dramatically increases deployment speed and reduces time loss.
3Extent of automation
If automated deployment using custom resource definitions is implemented, then deployment time is reduced and security is improved, but system complexity increases
Solution Approach 1:
The patent implements multi-functionality by designing the virtual machine launcher to handle multiple operations including receiving custom resource definitions, starting virtual machines, and coordinating with the workload interpreter. The workload interpreter similarly performs multiple functions including generating containers, deploying workloads, and managing container lifecycles. This universal approach consolidates multiple functions into unified components, managing complexity through functional integration rather than separate systems.
Solution Approach 2:
The system manages complexity by parameterizing deployment configurations through custom resource definitions that accept various parameters for virtual machine and container configuration. By changing parameters in these standardized definition formats, users can adapt deployments to different scenarios without increasing system complexity. The automated components process these parameterized definitions uniformly, maintaining simplicity despite the flexibility of configurations.
Data Source
AI summary
Virtual machine management is provided. A virtual machine is started automatically based on a custom resource definition of the virtual machine in response to the receiving the custom resource definition of the virtual machine. A container is generated to run an application workload in the virtual machine based on a container configuration file in response to the virtual machine starting. The application workload is deployed on the container automatically based on a container image corresponding to the container. The application workload is run on the container automatically in accordance with a definition of the application workload.


