Project 1 CAAT

Project 1 – CAAT: Cost‑Aware Adaptive Telemetry

1. Overview

CAAT is an intelligent observability system that adaptively tunes telemetry levels using reinforcement learning, eBPF probes, cost forecasting, and AI contextual reasoning.

2. Architecture

Components

• eBPF Runtime Sensing Layer
• OpenTelemetry Pipeline
• Telemetry Budget Engine
• RL Telemetry Optimizer
• Trace‑Native RAG Contextual Layer
• Multi‑Cloud Control Plane

3. Implementation Overview

• RL engine: projects/caat/rl_policy_engine/
• eBPF Go probes: projects/caat/ebpf_probes/
• RAG layer: projects/caat/rag_context_layer/
• Budget engine: telemetry_budget_engine/
• Helm chart: deploy/helm/caat/
• Grafana dashboard: grafana/

4. Deployment Steps

git clone https://github.com/Huzefaaa2/MindOps.git
cd MindOps/projects/caat

5. Roadmap

• Add live workload datasets
• Improve RL reward shaping
• Multi‑cluster adaptive telemetry