Serverless Event Routing System for Cloud Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing solutions for routing network traffic from multiple sources to distinct destinations often require a dedicated server, leading to inefficiencies in resource utilization and lack of adaptability when sources or destinations change.
Innovation Solution
A method and system that receive event objects from cloud providers, normalize them using cloud-specific handlers, and forward them to service providers based on an importance score, all without relying on a dedicated server.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dedicated server is used to route data from multiple sources to distinct destinations, then data routing capability is improved, but resource utilization efficiency deteriorates due to wasted computing resources during low bandwidth periods and insufficient resources during high bandwidth periods
Solution Approach 1:
The patent implements dynamic resource allocation by transitioning from a static dedicated server to a serverless architecture where computing resources are allocated on-demand based on actual traffic conditions. The system automatically scales resources up during high bandwidth periods and releases them during low bandwidth periods, making the resource allocation dynamic rather than fixed.
Solution Approach 2:
The system employs event-driven architecture where cloud event sources automatically publish events to event streams without requiring a dedicated server to continuously poll or manage data collection. The serverless functions automatically trigger and execute based on event occurrence, eliminating the need for continuous server monitoring and manual resource management.
2Reliability
If a dedicated server is configured to receive and forward data constantly, then data routing function is improved, but adaptability deteriorates when sources and/or destinations of the data change
Solution Approach 1:
The serverless architecture uses universal event streams and standardized event formats that can accommodate multiple cloud event sources and various destinations. The same event stream infrastructure handles events from different cloud providers and routes them to different service providers, making the system universally applicable rather than dedicated to specific source-destination pairs.
Solution Approach 2:
The system segments the data routing function into independent serverless functions that can be individually configured and deployed. Each function handles specific event routing logic, allowing the system to adapt to new sources or destinations by adding or modifying individual functions rather than reconfiguring an entire dedicated server system.
3Reliability
If a dedicated server is used for data routing, then routing capability is improved, but system complexity increases due to server configuration, maintenance, and scaling requirements
Solution Approach 1:
The patent introduces event streams as an intermediary layer between cloud event sources and service providers. This event stream mediator abstracts the complexity of direct server-to-server communication, providing a standardized interface for event publication and subscription while handling routing logic, thereby reducing the complexity of server configuration and maintenance.
Solution Approach 2:
The serverless architecture enables automatic provisioning and management of routing infrastructure. The system automatically creates and configures event streams, triggers, and functions based on declarative configurations, eliminating the need for manual server setup, configuration, and maintenance that would otherwise require specialized expertise and time.
Data Source
AI summary
Systems, methods, and computer-readable storage media for routing event data from cloud-based sources to various service providers without using a permanently dedicated server (or similar solution). The solution disclosed herein is source agnostic, meaning that the data being received can be from any provider of cloud-based data, with the data received being in a format specific to the given provider. The system can normalize the data from the respective sources into a common format based on properties on the data and, based on the normalized data, identify what type of analysis, process, or other service should be executed on data received. The system can then forward the data to respective service providers for the execution of those services.