Production Support Module for Real-Time Application Tracing
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Solution Overview
Problem
Computing systems face inefficiencies in data logging and analysis due to the time-consuming process of writing logging code and the disorganization and lack of real-time data provision, which hinders effective issue detection and solution implementation.
Innovation Solution
The integration of a production support system with a processor and memory that includes a production support module, capable of receiving client application modules, selecting data collection levels, and transmitting data to users in real-time, allowing for adjustable tracing and monitoring, thereby enhancing data output and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If logging code is written to capture data, then data can be collected for issue detection, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system enables self-service data collection by automatically instrumenting modules without requiring manual logging code writing. The production support module autonomously captures execution data, events, and traces from client applications, eliminating the need for developers to write and maintain logging statements throughout the codebase.
Solution Approach 2:
An intermediary production support module is introduced between the client application and the data analysis system. This module intercepts and collects execution data, events, and traces automatically, serving as a mediator that provides comprehensive logging capabilities without requiring changes to the existing application code.
2Loss of information
If all logged data is provided to analysts, then complete information is available for analysis, but the data becomes disorganized and unfiltered resulting in inefficient analysis
Solution Approach 1:
The system applies local quality by providing different levels and types of data filtering based on specific analysis needs. The production support module can filter and organize data locally according to predefined criteria, trace objectives, and data output rules, delivering customized data sets that match specific analytical requirements rather than providing all raw data uniformly.
Solution Approach 2:
Preliminary action is implemented by pre-filtering and organizing data before it reaches analysts. The system automatically applies filters, sorts data according to trace objectives, and prepares organized data sets in advance, so analysts receive pre-processed, relevant information rather than raw unorganized logs that require manual sorting and filtering.
3Measurement precision
If data is collected at high levels of detail, then comprehensive tracing information is available, but storage requirements and data processing load increase
Solution Approach 1:
The system implements dynamic data collection by allowing trace levels and collection parameters to be adjusted based on specific needs. The production support module can dynamically change the amount and type of data collected for different modules or time periods, enabling high-detail tracing when necessary while reducing data volume during normal operation or for less critical systems.
Solution Approach 2:
Parameter changes are utilized by allowing the system to adjust data collection parameters such as trace level, sampling rate, and detail depth. The production support module can modify these parameters based on trace objectives, system importance, and storage capacity, enabling flexible control over the balance between tracing precision and data volume.
Data Source
AI summary
Embodiments for integrating production support features are included in systems for receiving modules from a client application associated with an operator device. The embodiments include selecting at least one client module from the received modules, identifying a trace objective for the at least one client module, selecting a data collection level based on the trace objective, and collecting, by a processor, data associated with the at least one client module in response to the selected data collection level. The systems are combinable with additional production support features including event monitoring.