Distributed Pod Orchestration for Scalable Service Deployment
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Solution Overview
Problem
Existing resource management strategies for distributed computing environments, particularly in cloud computing, are inadequate for managing containerized environments and multi-cloud solutions, leading to scalability and operational cost challenges, and fail to address compliance with healthcare data privacy and security regulations.
Innovation Solution
A kernel-based approach for service orchestration that provisions and deploys subservices or services using customized resource allocation and isolation, utilizing image templates tailored to service types, and includes security best practices and performance optimizations, enabling deployment across multiple distributed computing environments while ensuring compliance with regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing resource management strategies are used in distributed computing environments, then resource allocation can be achieved, but scalability and operational cost efficiency deteriorate in containerized environments
Solution Approach 1:
The patent changes the fundamental parameters of resource management by transitioning from traditional virtual machine-based allocation to container-based allocation, and further to pod-based allocation where multiple containers share resources. This parameter change enables better scalability and operational efficiency in distributed computing environments while maintaining effective resource allocation.
Solution Approach 2:
The patent segments resources into discrete pods that can be independently allocated and managed. Each pod contains one or more containers that share common resources such as storage volumes and networks. This segmentation allows for granular control over resource allocation while improving scalability across distributed environments.
2Adaptability or versatility
If customized resource allocation is implemented for different service types, then service deployment flexibility improves, but system complexity increases
Solution Approach 1:
The patent creates a universal pod structure that can accommodate multiple different service types (batch processing, stream processing, machine learning, etc.) through a common interface and resource allocation mechanism. This multi-functionality approach allows customized resource allocation for different services without proportionally increasing system complexity, as the underlying pod management system remains consistent across service types.
3Reliability
If security best practices are integrated into deployment processes, then data privacy and security compliance improves, but deployment time and operational complexity increase
Solution Approach 1:
The patent implements security best practices as preliminary actions during the pod creation and configuration phase. Security policies, access controls, and compliance configurations are established upfront when pods are defined, rather than being added later during deployment. This preliminary integration of security measures ensures HIPAA and GDPR compliance while minimizing impact on deployment time, as security is built-in rather than bolted-on.
Data Source
AI summary
The present disclosure relates to techniques for service orchestration within a distributed pod based system. Particularly, aspects are directed to receiving, at a kernel residing on a distributed computing environment, a request to initiate deployment for a subservice or service on the distributed computing environment. The subservice or service has a type, and in order for the subservice or service to be deployed on the distributed computing environment, the type of the subservice or service has to be one that the distributed computing environment is configured to support. In response to receiving the request and the type of the subservice or service being one that the distributed computing environment is configured to support, specified resources are provisioned, and the subservice or service is deployed using a replica of a pod containing the provisioned specified resources and a modified image for the type of the subservice or service.