Most agent monitoring is "log everything and grep later." That's not monitoring — that's archaeology. What We Actually Need Live execution view — Which agent is running right now? State inspection — What data is Agent C holding? Failure forensics — Why did Agent B timeout? What were its inputs? Performance metrics — Per-agent latency, token usage, error rate AgentForge's Monitoring Stack Execution Trace (Structured JSON) Every pipeline run generates a trace: { "run_id" : "uuid" , "status" : "completed" , "agents" : [ { "name" : "data_fetch" , "status" : "ok" , "latency_ms" : 1200 , "tokens" : 450 }, { "name" : "analyzer" , "status" : "ok" , "latency_ms" : 3400 , "tokens" : 2100 }, { "name" : "reporter" , "status" : "ok" , "latency_ms" : 890 , "tokens" : 1200 } ] } Enter fullscreen mode Exit fullscreen mode WebSocket Dashboard Real-time WebSocket feed showing: Active agents (with heartbeat) Queue depth per agent Error rate (1-min sliding window) Cost per run (token usage × model price) Alert Rules alerts : -…