Establish pattern for adaptive Signal Correlation & Noise filtering across distributed environments

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We need examine how to correlate signals and filter noise out from log/metrics/traces at both infrastructure and application level.

This will directly impact feature definition and model training.

Desired Outcome: A pattern that enables model trainig based on initial data collection from:

• application level telemetry data
• infrastructure level telemetry data
• compare LLM vs predictive models and anomaly detection algorithms.