Observability agents
Observability agents: telemetry watched by agents
Observability agents are AI agents that watch telemetry instead of a person watching a dashboard. They look for anomalies across real-time metrics, logs and events; they also observe the agents themselves, tracking how autonomous agents behave and what they cost in tokens and spend against allocation.
What these agents take on
Two problems sit under this. The first is volume: nobody can watch the telemetry a modern estate produces. The second is newer - once agents are doing operational work, somebody has to observe the agents.
How this differs from what you have
| Dashboards | Threshold alerting | Observability agents | |
|---|---|---|---|
| Who watches | A person, when they look | A rule, when it trips | An agent, continuously |
| Finds the unexpected | Only if charted | No, thresholds are predefined | Yes, anomalies against learned baselines |
| Covers AI agents | No | No | Yes, behaviour, cost and token usage |
| Reporting | Built by hand | Not included | On demand and scheduled |
| Scales with telemetry | Poorly | Noisily | Designed for it |
The agents
- AI Observability Agent — provides deep observability into the behaviour and performance of autonomous agents.
- Agentic AI Observability Insights Agent — tracks cost, token usage and spend against allocation.
- Observability Summary & Reporting Agent — delivers on-demand and scheduled reports and dashboards via email, CSV and more.
What makes them safe to run in production
- Read-only by default. Analysis needs no write access. Anything that changes state waits for a person to approve it.
- Your data stays put. Agents query the systems where it already lives, with no copy and no migration.
- Every run is auditable. Inputs, tool calls, conclusion and approver are recorded.
- Your model, your environment. Cloud, Fabrix-managed or on-premises, including sovereign and air-gapped deployments.
Questions we get asked
What are observability agents?
Observability agents are AI agents that continuously watch telemetry - metrics, logs, events and traces - for abnormal patterns, and report what they find. Unlike a dashboard they do not need a person looking, and unlike threshold alerting they can surface patterns nobody defined in advance.
What is agent observability?
Agent observability is observability applied to the AI agents themselves: what each agent did, which tools it called, how it performed, and what it cost in tokens and spend against its allocation. Once agents take operational action, that record is what makes them auditable.
How is this different from an observability platform?
An observability platform stores and queries telemetry. These agents sit on top of that: they decide what is worth looking at, flag it, and summarise it. Fabrix.ai also integrates with the observability tools already in place rather than replacing them.
What does it cost to watch AI agent spend?
The Agentic AI Observability Insights Agent reports token usage and spend against allocation, so cost is visible per agent rather than arriving as one bill at the end of the month.
Can reports be scheduled?
Yes. The Observability Summary and Reporting Agent delivers both on-demand and scheduled reports and dashboards, by email, CSV and other formats.
See these agents at work in your own stack.
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