Isolated Cell Architecture for Cloud Service Provisioning
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Solution Overview
Problem
Cloud-based platforms face issues with computing device failures, service unavailability, and resource overconsumption, which can negatively impact clients and lead to scalability problems.
Innovation Solution
Implementing an isolated cell architecture within a container engine across multiple computing devices, where each cell is self-sufficient and can be instantiated based on client requests, allowing for resource allocation and isolation to prevent impact on other clients and ensure partial functionality during device failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud services are provided on shared computing devices, then resource utilization is improved, but service reliability and client isolation deteriorate due to device failures and other customers' usage impacts
Solution Approach 1:
The patent divides the computing system into isolated cells, where each cell is a self-contained computing environment with its own container engine and resources. This segmentation allows multiple cells to run on the same physical computing device while maintaining complete isolation between them, thus improving resource utilization without compromising service reliability. Each cell can be independently instantiated, managed, and recovered, preventing failures in one cell from affecting others.
2Power
If more resources are allocated to a single service instance, then service performance is improved, but scalability and fault tolerance deteriorate
Solution Approach 1:
The patent segments services into multiple independent cell instances that can be distributed across different computing devices. Each cell contains a complete service environment with its own container engine, allowing services to be scaled horizontally by adding more cell instances rather than concentrating resources in a single instance. This enables both high performance within each cell and system-wide scalability through multiple cells.
Solution Approach 2:
The patent enables dynamic adjustment of cell parameters including resource allocation, replication factors, and distribution configurations. This allows the system to adapt resource distribution based on service performance requirements while maintaining scalability. Parameters such as the number of cell instances, resources per cell, and failover configurations can be modified without redesigning the overall system architecture.
3Productivity
If resources are shared across multiple clients, then resource efficiency is improved, but client isolation and security deteriorate due to resource overconsumption and interference
Solution Approach 1:
The patent implements client isolation through segmented cells, where each client's service runs in its own isolated cell environment. The container engine within each cell enforces resource boundaries and prevents any single client from overconsuming system resources or interfering with other clients. This segmentation maintains resource efficiency through controlled sharing while eliminating the harmful effects of uncontrolled resource access.
Solution Approach 2:
The container engine acts as an intermediary layer between the shared computing resources and individual client services. It mediates resource allocation and access control, ensuring that each client receives appropriate resources while preventing resource overconsumption and interference between clients. This intermediary mechanism enables efficient resource sharing with built-in protection against harmful effects.
4Device complexity
If a monolithic service architecture is used, then system simplicity is maintained, but fault isolation and recovery capability deteriorate
Solution Approach 1:
The patent segments the service architecture into independent cells, where each cell is a self-contained unit with its own container engine and resources. This segmentation provides automatic fault isolation - failures in one cell do not propagate to other cells - while maintaining relatively simple individual cell structures. Each cell can be independently recovered or restarted without affecting the overall system, improving fault tolerance while keeping cell-level complexity manageable.
Data Source
AI summary
The present disclosure relates to system and techniques for enabling provisioning of cloud services for a client in an isolated yet scalable manner. In some embodiments, various computing resources are implemented within a cell (a self-sufficient unit). A number of cells are generated for a service or a group of services and distributed across a number of computing devices. Various cells may be generated that each pertain to a different aspect, or particular functionality, of the service. In some embodiments, cells providing various functionality for the service are implemented and distributed across different computing devices.