1. Instrument behaviour, not only spans
Emit traces plus decision telemetry — intent, tool candidates, confidence, and state transitions — so operators reconstruct why an agent acted, not only that it logged.
Guide · Agent Observability
Agent Observability that operators can run
Beyond uptime and raw traces — behaviour signals, intent, multi-tenant situation views, and recovery when fleets misbehave.
What Agent Observability means here
Agent Observability is the practice of seeing what autonomous agents do in production: sessions, decisions, tool calls, state transitions, and recovery — not only whether a process is up. PUVINoise implements this as Behaviour Runtime Intelligence on a multi-tenant control plane.
Four pillars of Agent Observability
2. Scope by tenant
Put tenant.id on every resource. Multi-tenant fleets need observation boundaries so one customer’s failure does not become another’s noise.
3. Situation in Command Centre
Aggregate fleet state into shared situation views for engineering, SRE, and agent ops — without ad hoc dashboards per team.
4. Close with Runtime Cases
Connect detection to triage, mitigation, and learning. Measure MTTR. Keep policy and human override in the recovery path.
Category clarity
Agent Observability vs adjacent stacks
vs APM (Datadog, New Relic, …)
APM watches services and infra. Agent Observability watches intent and recovery when uptime is green but behaviour is wrong.
vs Datadog →vs LLM tracing (Langfuse, …)
LLM tracing debugs generations and prompts. Agent Observability runs fleets: cases, tenancy, governed remediation.
vs Langfuse →vs OpenTelemetry-only
OTel is portable plumbing. Agent Observability is the productized behaviour plane on top of good telemetry.
vs OTel-only →Implementation checklist
Use this when standing up Agent Observability with PUVINoise.
Install puvinoise-sdk and call bootstrap() before agent work
Verify tenant-scoped traces in Command Centre
Adopt decision telemetry for intent and tool selection
Define Runtime Case ownership and escalation
Align security review on isolation and audit narratives
Start free evaluation before wide fleet rollout
FAQ
Agent Observability — common questions
Do we still need Datadog or Azure Monitor?
Usually yes for infra and classic APM. PUVINoise specializes the agent behaviour and recovery layer. See Compare for side-by-side framing.
Is this the same as LLM monitoring?
Related but not identical. LLM monitoring emphasizes model/request quality; Agent Observability emphasizes multi-step agent behaviour and ops recovery. See the LLM Monitoring guide.
How do we start?
Start a free evaluation on app.puvilabs.com, instrument one agent, verify signals, then expand. Pair with Engineering if you need delivery help.
Put Agent Observability on your fleet
Start free on app.puvilabs.com — review Pricing for commercial plans, or compare PUVINoise to your current stack.