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"name": "Production AI Observability Monitor",
"problem": "Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.",
"domain": "ai-observability",
"architecture": "classifier",
"hugging_face_tasks": [
"text-classification",
"token-classification",
"summarization",
"zero-shot-classification"
],
"recommended_stack": [
"OpenTelemetry GenAI semantic conventions",
"OpenTelemetry Collector for vendor-neutral ingestion",
"ClickHouse or PostgreSQL for trace analytics",
"Prometheus and Grafana for service-level metrics",
"MLflow for model and prompt version linkage",
"FastAPI for trace search and regression APIs"
],
"real_world_data_sources": [
{
"name": "Prometheus HTTP API",
"url": "https://prometheus.demo.do.prometheus.io/api/v1/query?query=up",
"purpose": "Real time-series telemetry for anomaly pipelines"
},
{
"name": "GitHub Events API",
"url": "https://api.github.com/events?per_page=10",
"purpose": "Deployment-correlated public event metadata"
}
],
"job_description_skills": [
"LLMOps observability and trace instrumentation",
"Prompt, model, dataset, and deployment lineage",
"SLOs, anomaly detection, and incident diagnostics",
"High-volume telemetry storage and aggregation",
"Evaluation-driven production monitoring"
],
"impact_targets": [
"Ingest 1,000 synthetic traces/second without loss",
"Detect seeded latency and quality regressions with >= 0.90 precision",
"Link 100% of traces to model, prompt, and dataset versions",
"Generate a release health report in under 60 seconds"
],
"baseline_evaluation": {
"test_examples": 4,
"accuracy": 1,
"synthetic_evaluation": true
},
"estimated_delivery": "8-12 weeks for one engineer",
"generated_baseline_is_production_ready": false
}
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