Real-Time Performance Monitoring via Segmented Metrics Buffering
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Solution Overview
Problem
Real-time performance monitoring of applications on computing devices faces challenges due to data loss during metric data transfer and increased machine overhead, primarily caused by large data volumes and concurrent data processing, leading to inaccurate results and decreased computational efficiency.
Innovation Solution
A method for real-time performance monitoring that involves a selection mechanism for choosing data storage locations based on status, allowing simultaneous read and write operations, ensuring lossless data transfer by designating some locations as read-only and others as write-only, and preserving data until successful transfer, thereby reducing overhead and ensuring accurate data delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time data monitoring is implemented to monitor performance metrics simultaneously with ongoing testing, then the user can access metrics data in real-time, but data loss occurs during transfer and machine overhead increases
Solution Approach 1:
The patent divides the monitoring system into separate components: a monitoring agent that collects metrics data and a separate monitoring application that receives and processes the data. This segmentation allows the agent to efficiently collect data without burdening the monitored application, reducing machine overhead while maintaining data accuracy.
Solution Approach 2:
The patent introduces a metrics buffer as an intermediary component that temporarily stores collected metrics data before transfer to the monitoring application. This buffer acts as a mediator that decouples the data collection process from the data processing process, preventing data loss during transfer while minimizing impact on the monitored application's performance.
2Speed
If real-time monitoring of metrics data is performed, then performance can be monitored simultaneously with testing, but data loss occurs while transferring the metrics data
Solution Approach 1:
The patent implements a pre-allocated metrics buffer that is prepared in advance to receive metrics data. By having the buffer ready before data collection begins, the system can immediately store incoming data without transfer delays, preventing data loss while maintaining real-time monitoring capability.
Solution Approach 2:
The patent creates a copy of the metrics data in the buffer before the monitoring application processes it. This copying mechanism ensures that the original data is preserved in the buffer while being transferred to the application, preventing data loss during the transfer process and enabling reliable real-time monitoring.
3Productivity
If metrics data is collected and transferred continuously, then real-time monitoring is achieved, but the overhead of the machine increases decreasing computational efficiency
Solution Approach 1:
The patent segments the monitoring functionality into a lightweight agent that only collects data and a separate application that performs analysis. This segmentation reduces the overhead on the monitored application since the agent performs only simple data collection and transfer operations, maintaining real-time monitoring capability while minimizing impact on computational efficiency.
Solution Approach 2:
The monitoring agent operates autonomously to collect and buffer metrics data without requiring active intervention from the monitored application. This self-service approach allows continuous real-time monitoring while keeping the monitored application's computational overhead minimal, as the agent handles all data collection and buffering operations independently.
Data Source
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AI summary
Systems and methods for real time performance monitoring of an application are described. In one implementation, when a metrics collection request is obtained from a user device (104), a data storage location (108-1) is selected from a plurality of data storage locations (108) based on a location status associated with the data storage location (108-1). The metrics data, for monitoring the performance of the application, is then provided to the user device (104) through a data store (114) from the selected data storage location (108-1) in real time.