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AI observability vs runtime governance
AI observability and runtime governance solve different problems. Observability explains what happened; governance controls what is allowed to happen.
What teams need to get right
- Observability tracks traces, latency, token usage, and failure trends.
- Runtime governance blocks or gates risky actions before side effects occur.
- Mature teams combine both for prevention, diagnosis, and continuous improvement.
How Stacksona helps
- Inline policy enforcement in the action path, not only post-hoc monitoring.
- Approval workflows that integrate with existing telemetry and SIEM tools.
- Unified evidence across runtime controls and operational observability data.
Why this matters now
As agent deployments move from prototypes to customer and operational workflows, governance needs to be embedded in execution paths. Teams that rely only on after-the-fact monitoring often discover risk too late.
