Dynamic Microservice Logging Adjustment in HCI
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Solution Overview
Problem
In hyper-converged infrastructure (HCI) microservice systems, achieving an appropriate logging level is challenging due to insufficient logging omitting important information while excessive logging leads to high I/O and processor usage, burying critical details.
Innovation Solution
An information handling system configured to execute microservices that generate logging information, with a dynamically adjustable logging level based on API call failure rates, allowing for proactive adjustment of logging levels to optimize data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If logging level is increased to capture more detailed information, then measurement precision of system operations is improved, but use of energy and processor usage increase excessively
Solution Approach 1:
The patent implements dynamic adjustment of logging levels based on real-time system conditions. The logging level is not fixed but changes adaptively according to system state, allowing the system to capture detailed information when needed while reducing logging overhead during normal operation, thus resolving the contradiction between measurement precision and energy use
Solution Approach 2:
The system changes the logging parameter (logging level) dynamically based on system conditions such as failure rates. By adjusting this parameter according to operational context, the system achieves high measurement precision when problems occur while maintaining low processor usage during stable operation
2Measurement precision
If logging level is increased to capture more detailed information, then measurement precision of system operations is improved, but productivity decreases due to excessive I/O and processor usage
Solution Approach 1:
The logging system dynamically adjusts its operation based on system conditions. During normal high-throughput operation, logging is minimized to maintain productivity. When failures or anomalies are detected, logging detail increases automatically to capture diagnostic information, thus resolving the contradiction between measurement precision and productivity
3Loss of energy
If logging level is decreased to reduce resource usage, then use of energy and processor usage are reduced, but loss of information increases due to omitted critical details
Solution Approach 1:
The system uses feedback from system performance monitoring to adjust logging levels. When failures or anomalies are detected through monitoring, the system automatically increases logging detail to capture critical diagnostic information. During normal operation, logging is reduced to minimize resource usage. This feedback mechanism ensures that information is captured when needed without wasting resources during stable operation
Solution Approach 2:
The system prepares to capture detailed logging information in advance when failure conditions are detected. By monitoring system health and proactively increasing logging detail upon detecting anomalies, the system ensures critical information is captured before it may be lost, preventing information loss while minimizing unnecessary logging during normal operation
Data Source
AI summary
An information handling system may include at least one processor and a memory. The information handling system may be configured to: execute a plurality of microservices, wherein each microservice is configured to generate logging information relating to its operation, and wherein a logging level is configured to determine an amount of logging information generated by the microservice; monitor the execution of the plurality of microservices to determine a failure rate associated with application programming interface (API) calls to the plurality of microservices; and based on the determined failure rate, alter the logging level.