Container-Based Cloud Service System for Dynamic Load Balancing
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Solution Overview
Problem
Cloud services experience performance degradation when a large number of users access simultaneously due to limited resources, leading to delays and system inefficiencies.
Innovation Solution
A container-based cloud service system that includes an access server network-connected to user terminals through web sockets, an in-memory cluster for authentication and event data storage, and a manager module for load balancing, which dynamically adjusts the number of security, data storage, and service modules based on traffic to maintain performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud services use traditional resource allocation methods, then system structure is simple, but performance degrades when large number of users access simultaneously
Solution Approach 1:
The system segments cloud services into multiple independent container modules, each handling specific functions. This allows parallel processing and distribution of user requests across multiple containers, preventing performance degradation under heavy load while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The system dynamically adjusts the number and configuration of container instances based on real-time traffic conditions. When user demand increases, additional containers are instantiated to handle the load; when demand decreases, containers are scaled down. This dynamic adaptation maintains high performance without requiring permanently over-provisioned resources.
2Productivity
If cloud services allocate more resources to handle simultaneous users, then service performance is maintained, but resource cost increases
Solution Approach 1:
The container-based architecture enables automatic self-service through orchestration systems that monitor resource utilization and automatically provision or deprovision container instances based on demand. This eliminates the need for manual resource allocation and ensures resources are consumed only when needed, maintaining performance while optimizing resource cost.
Solution Approach 2:
The system changes operational parameters dynamically by adjusting the number of active container instances, CPU allocation, and memory resources based on real-time traffic patterns. This allows the system to maintain optimal performance during peak usage while minimizing resource consumption during low-usage periods.
3Ease of operation
If cloud services use static module configuration, then system management is simple, but load balancing capability is insufficient
Solution Approach 1:
The container modules are designed with universal interfaces and standardized communication protocols, allowing them to perform multiple functions and be deployed in various configurations. This multi-functionality enables flexible load balancing strategies while maintaining simple management through consistent operational procedures across all containers.
Data Source
AI summary
A container-based cloud service providing system of the present disclosure includes an access server network-connected to a plurality of user terminals through a web socket; an in-memory duster having an area allocated in a cloud and storing an authentication key and event data based on a container; a server module providing a cloud service to the user terminal; a manager module managing the server module; and a database. The server module includes a security module having a container structure and performing authentication of the user terminal; a data storage module having a container structure and periodically storing the event data stored in the in-memory cluster in the database; and a service module providing the cloud service by using the event data.