Gearbox Cloud Infrastructure for Scalable Fault Tolerance
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Solution Overview
Problem
Existing cloud computing infrastructure becomes complex and difficult to scale efficiently and cost-effectively as demands for capacity, performance, and robustness increase, making it challenging for programmers to implement cloud services without detailed knowledge of technology, especially in providing fault tolerance and load balancing.
Innovation Solution
The introduction of a new cloud programming language that enables the use of 'gearboxes' – functionally equivalent web servers with physical storage and optional file stores, allowing for horizontal scaling and fault tolerance through a multi-master database and file storage system, along with a shared round robin load balancer for efficient load balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional cloud computing infrastructure is used with separate web servers, database nodes, and storage systems, then the system can provide basic functionality, but the infrastructure becomes complex and difficult to scale efficiently
Solution Approach 1:
The patent combines web server, database, and storage functionalities into a single integrated gearbox unit. Each gearbox contains a web server with embedded physical storage holding a master database, eliminating the need for separate dedicated database nodes and storage systems. This merging reduces infrastructure complexity while maintaining scalability, as gearboxes can be added horizontally to meet increasing demand without requiring complex reconfiguration of separate components.
Solution Approach 2:
The gearbox is designed as a universal unit that performs multiple functions: web serving, data storage, database management, and peer-to-peer communication. This multi-functional design allows any gearbox to potentially serve any purpose in the cluster, enhancing flexibility and simplifying the infrastructure. The universal gearbox eliminates the need for specialized hardware for different functions, reducing overall system complexity while maintaining high productivity through efficient resource utilization.
2Reliability
If programmers need detailed knowledge of software and hardware to implement cloud services with fault tolerance and load balancing, then the system can achieve high reliability, but the ease of operation decreases
Solution Approach 1:
The gearbox system implements self-service mechanisms where each gearbox automatically manages its own state, communicates with peers, and participates in load balancing without requiring manual configuration. The peer-to-peer architecture enables automatic fault detection and recovery, where gearboxes can take over failed peers' responsibilities automatically. This self-organizing behavior maintains high reliability while simplifying operation, as programmers don't need to manually configure fault tolerance or load balancing - the system handles these automatically.
Solution Approach 2:
The system employs dynamic load balancing through a shared round robin load balancer that automatically distributes requests across available gearboxes based on current system state. The peer-to-peer communication protocol dynamically routes requests and responses, adapting to failures and capacity changes in real-time. This dynamic behavior ensures fault tolerance without requiring static pre-configuration, allowing the system to maintain high reliability while being easy to operate - programmers simply add gearboxes without configuring fault tolerance parameters.
3Productivity
If complex load balancing software or hardware is used to distribute requests across multiple servers, then load balancing performance improves, but the device complexity increases
Solution Approach 1:
The system introduces a shared round robin load balancer as a simple intermediary that distributes incoming requests across gearboxes using a straightforward round-robin algorithm. This load balancer acts as a mediator between clients and the peer-to-peer gearbox cluster, providing efficient load balancing without requiring complex software or hardware. The simplicity of the round-robin approach, combined with the gearboxes' inherent peer-to-peer capabilities, achieves good load balancing efficiency while minimizing the complexity of the load balancing mechanism itself.
Data Source
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AI summary
A first node comprises a web server with a network interface configured to connect the web server to a plurality of second nodes of a cloud infrastructure. The first node has physical storage, connected to the web server, the physical storage comprising at least a master database of a multi-master database system of the cloud computing infrastructure, the master database configured to store atomic code units and data redundantly as part of the multi-master database system, the atomic code units defining the dynamic web application. The web server receives requests comprising input data and identifiers of individual ones of the atomic code units, at least some of the requests originating from client devices using the dynamic web application. The web server executes, in response to requests, individual ones of the atomic code units in dependence on state of the master database, such that the dynamic web application is executed.