Data Management Server for Decoupled Application Logging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Applications face challenges in managing and processing data, particularly log data, due to high latency systems like hard drives and networks, which complicate scalability and development, as they need to handle increased computing resources to maintain throughput.
Innovation Solution
A method for processing application data involves receiving packets from emitters, identifying emitter IDs, determining data processing destinations, and processing data according to associated rules, allowing for centralized management and scaling of data processing tasks without requiring applications to handle logging and other functions directly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If applications directly handle logging and data processing to high latency systems, then data processing functionality is achieved, but system latency increases and scalability becomes complex
Solution Approach 1:
The patent extracts the data processing functionality from the application layer and places it in a separate data management server. The application merely emits data packets, while the server handles routing, filtering, and processing to destinations like log files and databases. This separation removes the time-consuming I/O operations from the application's critical path, reducing latency while maintaining full data processing capability.
Solution Approach 2:
The data management server acts as an intermediary between applications and high latency systems. It receives data packets from applications, applies routing rules, and manages communication with destinations such as log files and databases. This mediator absorbs the latency of disk I/O and network operations, preventing these slow operations from directly impacting application performance.
2Adaptability or versatility
If applications handle their own data processing and logging, then self-sufficiency is achieved, but device complexity and scaling requirements increase
Solution Approach 1:
The patent extracts complex data management functionality from individual applications and consolidates it in a centralized data management server. Applications become simpler by only needing to emit data packets, while the server handles routing rules, destination management, and processing logic. This reduces device complexity at the application level while maintaining versatility through the server's configurable rule engine.
Solution Approach 2:
The data management server provides universal data processing capabilities that serve multiple applications simultaneously. A single server instance can handle routing for numerous applications, manage multiple destinations, and apply different processing rules to different data streams. This multi-functionality reduces overall system complexity compared to each application having its own dedicated processing infrastructure.
Data Source
AI summary
Techniques for processing application data are described. The techniques include transmitting packets of application data to a data management server. The data management server maintains rules that dictate where the packets go as well as what actions are taken in response to the packets. Based on the rules, the data management server transmits the packets to destinations that may perform various actions. The actions performed by destinations may include logging data received from the applications, or performing other actions such as notifying an administrator or other entity of a particular event, or the like. The described architecture decouples functions such as logging, notification, and the like from the applications for which they are performed, which provides benefits such as improved scalability, as well as removing the need for application developers to build such functionality directly into the applications. This reduces application development time and improves the robustness of application functionality.