Monitoring Depth vs. Processing Overhead
Apply adaptive telemetry that escalates monitoring depth automatically on anomaly detection, keeping baseline collection lightweight to protect production capacity.
CyberTRIZ analysis · Telecommunications contradiction RO015 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Detailed monitoring improves understanding of network behavior by collecting metrics, traces, logs, events, packet information, and service-level measurements. Increasing monitoring depth, however, consumes network bandwidth, storage, computing capacity, and analytical resources. In extreme cases, observability infrastructure can become a significant workload of its own.
Telecommunications TRIZ Resolution
Monitoring depth should vary according to risk, condition, and diagnostic need. Routine operation can use lightweight measurements, while anomalies automatically trigger more detailed telemetry for affected components or services. Sampling, aggregation, edge processing, and selective retention can preserve diagnostic value without continuously collecting maximum-detail information everywhere.
Applicable TRIZ Principles
Principle 1 – Segmentation applies different monitoring levels to different services and components.
Principle 15 – Dynamics increases telemetry detail when abnormal conditions appear.
Principle 23 – Feedback uses detected conditions to determine when deeper observation is required.
Expected Outcome
Stronger diagnostic visibility
Lower telemetry processing overhead
Reduced storage requirements
More efficient observability infrastructure
Decision Indicators
Early indicators include:
Monitoring platforms consume rapidly increasing computing and storage resources.
Large telemetry datasets are collected but rarely analyzed.
All network elements use identical monitoring depth.
Diagnostic teams still lack useful information despite growing data volumes.
Increasing observability requires significant production-network capacity.