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LLM Observability Stack Configurator for Evaluation Redesign Migration Sprint

Specify and configure a complete LLM observability stack for a production AI application, covering tracing, metrics, cost tracking, and quality signal collection.

• Best with Weights & Biases
• AI Engineering & LLMOps
• Observability

Open this agent in the library →

More Observability agents

• Alert on Error-Rate and Cost SpikesObservability · Python
• Alert on Error-Rate and Cost Spikes for Cross-Functional Rollout Scenario 0557Observability · Python
• Alert on Error-Rate and Cost Spikes for Cross-Functional Rollout Scenario 1637Observability · Python
• Alert on Error-Rate and Cost Spikes for Escalation Triage Scenario 0197Observability · Python
• Alert on Error-Rate and Cost Spikes for Escalation Triage Scenario 1277Observability · Python
• Alert on Error-Rate and Cost Spikes for Governance Audit Prep Scenario 0737Observability · Python
• Alert on Error-Rate and Cost Spikes for Governance Audit Prep Scenario 1817Observability · Python
• Alert on Error-Rate and Cost Spikes for Portfolio Prioritization Scenario 0377Observability · Python
• Alert on Error-Rate and Cost Spikes for Portfolio Prioritization Scenario 1457Observability · Python
• Alert on Error-Rate and Cost Spikes for Production Hardening Runbook RefreshObservability · Claude
• Alert on Error-Rate and Cost Spikes for Regional Launch Scenario 0917Observability · Python
• Alert on Error-Rate and Cost Spikes for Service Reliability Review Scenario 0017Observability · Python

All Observability agents · All AI Engineering & LLMOps agents