Bare-Metal Container Deployment via Embedded Hypervisor
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in scaling the deployment and management of containerized workloads, as tools used to instantiate, manage, monitor, and secure containers often require seamless scalability that is not adequately addressed by current virtualization software and architecture.
Innovation Solution
The method involves automatically deploying containerized applications on a device's operating system by booting the device, powering on a hypervisor and a container engine, and then automatically obtaining intended state configuration files to deploy a control plane pod and containers on bare-metal, thereby enabling scalable deployment and management of containerized applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If virtualization software and architecture are used to deploy containerized applications, then isolation and resource management are improved, but scalability and operational complexity increase
Solution Approach 1:
The patent extracts the control plane functionality from the traditional virtualization management architecture and implements it as automated self-bootstrapping procedures. The system removes the need for manual control plane deployment by embedding automated initialization logic directly in the worker node boot process, thereby reducing operational complexity while maintaining isolation benefits
Solution Approach 2:
The worker nodes automatically bootstrap themselves by obtaining control plane configuration and deploying necessary components without human intervention. The system performs self-service initialization where nodes automatically join the cluster, deploy control plane pods, and configure their own container runtime environments, significantly reducing operational complexity
2Measurement precision
If manual deployment procedures are used for control plane and worker nodes, then deployment accuracy can be monitored, but time consumption and labor requirements increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring intent state configuration files that define the desired cluster state before deployment. These configuration files contain all necessary control plane and worker node settings, allowing the system to automatically execute deployment steps in the correct sequence without manual intervention, thereby reducing time consumption while maintaining accuracy through predefined deployment playbooks
Solution Approach 2:
The system incorporates feedback mechanisms where the automated deployment process monitors its own execution, verifies configuration application, and reports deployment status. The control plane receives feedback from worker nodes about their bootstrapping progress and adjusts deployment actions accordingly, ensuring deployment accuracy while maintaining automation speed
3Adaptability or versatility
If traditional virtualization layers are used, then hardware abstraction and flexibility are improved, but performance overhead and resource utilization decrease
Solution Approach 1:
The patent segments the virtualization architecture by separating the control plane virtualization functions from the worker node execution environment. Worker nodes run containerized workloads directly on the host OS without requiring full virtual machine overhead, while the control plane maintains hardware abstraction capabilities. This segmentation eliminates unnecessary virtualization layers for workload execution, improving performance and resource utilization while preserving hardware abstraction where needed
Data Source
AI summary
An example method of automatically deploying a containerized application on an operating system (OS) of a device is provided. The method generally includes booting the device with the corresponding operating system; powering on a hypervisor as a first user processing running on the OS; powering on a container engine as a second user process running on the OS; booting a virtual machine (VM) running an embedded hypervisor, wherein the VM is running on the hypervisor; and in response to booting the VM: automatically obtaining, by the VM, intended state configuration file(s) defining a control plane configuration for providing services for at least deploying and managing the containerized application and application configuration parameters for the containerized application; deploying a control plane pod configured according to the control plane configuration; deploying container(s) on the OS based on the control plane configuration; and deploying the containerized application on the container(s).