The agent observability stack: traces, artifacts, grades, and replay
Production teams need traces, tool-call spans, artifacts, grades, and replayable run state.
Traditional logs answer what line of code ran. Agent observability must explain why the system chose an action and whether the result was worth it.
AstraRunner treats this as an execution-platform concern: the run needs durable state, traceable decisions, cost visibility, and enough structure for teams to review what happened after the agent finishes.
Patterns that work
- Capture model calls, tool calls, retries, approvals, and handoffs.
- Preserve artifacts and intermediate decisions.
- Grade outputs against explicit rubrics.
- Replay runs against changed prompts, models, or policies.
Implementation checklist
- Emit trace spans for every expensive or risky step.
- Link spans to artifacts.
- Store grade dimensions.
- Expose replay inputs and differences.
Watch outs
- Logs without prompts and tool arguments are incomplete.
- Observability without artifacts cannot explain quality.
- Replay without versioning produces misleading results.
Related reading
How this fits the Astra stack
AstraRunner owns the operational path for agent work: orchestration, scheduling, approval gates, traces, costs, and role-agent handoffs. AstraMemory owns durable context and retrieval. AstraGenie turns those capabilities into product workflows for teams that want automation without rebuilding the platform layer.