AI agent monitoring
Know when agents are slow, expensive, failing, or simply wrong.
SenalOps combines synthetic AI-agent checks with production agent telemetry. Synthetic checks validate whether a response meets expectations, while runtime telemetry captures latency, token usage, cost, tool spans, status, and errors for each agent run.
How AI agent monitoring works
SenalOps watches AI agents in two complementary ways. Synthetic agent checks send a scheduled prompt to your agent endpoint and judge whether the answer meets an expected outcome. Runtime agent telemetry records every production run so you can see what real users experience. Use both together to catch quality regressions before customers do and to investigate the runs that fail in production.
What SenalOps tracks for every agent run
- Latency for the whole run and for each tool call
- Token usage and cost, so spend spikes are visible quickly
- Tool spans that show which step in the workflow was slow or failed
- Run status and errors for fast investigation
Failures that uptime monitoring misses
- An AI support agent that starts giving incomplete answers while the endpoint stays up
- Cost spikes caused by tool loops, prompt regressions, or model changes
- Slow tool calls hidden inside a longer agent workflow
- Endpoint availability that looks healthy while answer correctness drops
FAQ
AI agent monitoring questions
How does SenalOps monitor AI agents?
SenalOps supports AI agents in two ways. Synthetic agent checks send scheduled prompts to an agent endpoint and judge whether the response meets expectations. Agent telemetry records production runs, latency, token usage, cost, tool spans, status, and errors so teams can investigate failures and spending changes.
Can SenalOps detect when an AI agent is online but wrong?
Yes. Synthetic AI-agent checks validate response quality against an expected outcome, so SenalOps can catch cases where the endpoint returns HTTP 200 but the agent response is incorrect, incomplete, or unsafe for the workflow being monitored.
What does a synthetic AI agent check need?
A synthetic check needs the agent endpoint, a prompt to send, and an expectation the response should satisfy. You can also add a request body template, a JSON response path that extracts the answer field, and an authorization header for protected endpoints.
Can I get alerts when an AI agent gets expensive or starts failing?
Yes. Create threshold rules for error rate or cost, scope each rule to one agent or all agents, choose a rolling time window, and route breaches to your alert channels. SenalOps sends a recovery notification when the agent drops back below the threshold.
Which plans include AI agent observability?
Scheduled synthetic AI agent checks and agent run telemetry are included on the Pro and Business plans, alongside services, SLOs, incidents, and OTLP telemetry. The Free and Builder plans cover uptime monitoring only, and anyone can try the free agent checker without an account.
Can I test an AI agent without creating an account?
Yes. The free AI agent checker sends your prompt to any agent or LLM endpoint and judges whether the response meets your expectation. It runs a few times per hour and needs no signup.