Adaptive Observability Control for Resource-Aware Data Collection
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Solution Overview
Problem
Existing observability systems are static and unidirectional, leading to a trade-off between system performance and the amount of data collected, which restricts the usefulness of the collected data and increases CPU and network resource consumption.
Innovation Solution
A dynamic and adaptive approach that allows a controller computing node to adjust the detail level of observation data collection based on system conditions, instructing agent computing nodes to increase detail level collection when problems or anomalies are detected, and enabling agent nodes to adjust collection settings independently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more observation data is collected to improve observability, then measurement precision is improved, but CPU and network resource consumption increases
Solution Approach 1:
The patent implements dynamic adjustment of observation detail levels based on system state. The system transitions from static predefined collection to dynamic control where agents can adjust their observation granularity in real-time based on detected anomalies or normal conditions, resolving the contradiction between data volume and resource consumption
Solution Approach 2:
The system changes the parameter of observation detail level dynamically. By modifying the detail level parameter based on system conditions (normal operation vs. anomaly detection), the system optimizes the balance between collecting sufficient data for observability and minimizing resource consumption
2Measurement precision
If more observation data is collected to improve troubleshooting capability, then measurement precision is improved, but system performance deteriorates
Solution Approach 1:
The system dynamically adjusts observation intensity based on operational context. During normal operation, agents collect minimal data to maintain performance, while automatically increasing collection intensity when anomalies are detected, thus providing detailed troubleshooting data only when needed
Solution Approach 2:
The observability system serves itself by automatically detecting anomalies and triggering enhanced data collection without external intervention. The system monitors its own state and autonomously adjusts observation parameters to balance performance and troubleshooting capability
3Device complexity
If static observation data collection is used to simplify system design, then device complexity is reduced, but adaptability to changing system conditions deteriorates
Solution Approach 1:
The system introduces dynamic control mechanisms that allow agents to adjust their observation behavior based on system conditions. This adds adaptability while maintaining relative simplicity through a hierarchical architecture where controllers guide agents based on predefined policies and detected states
Data Source
AI summary
A method performed by a controller computing node to dynamically adjust a detail level of observation data collected by an observability system. The method includes receiving observation data collected by a plurality of agent computing nodes, determining, based on analyzing the observation data collected by the plurality of agent computing nodes, that a detail level of observation data collected by one or more of the plurality of agent computing nodes is to be changed, and responsive to determining that the detail level of observation data collected by the one or more agent computing nodes is to be changed, instructing the one or more agent computing nodes to change the detail level of observation data that they collect.