PulseProbe

Automation monitoring guides

AI workflow guide

How to Monitor AI Agent Workflows with Heartbeat URLs

AI workflows often depend on queues, model APIs, schedulers, databases, and orchestration code. A final-step heartbeat gives you a simple completion signal.

Short answer

Put a heartbeat check at the point where the AI workflow has completed its useful work. If that check-in stops arriving, PulseProbe alerts you that the agent workflow may be stalled or missed.

Last reviewed: June 10, 2026

Why AI agent workflows fail silently

  • A scheduler or queue stops dispatching runs.
  • A model API, tool call, or downstream service fails before completion.
  • The workflow times out after partial work.
  • An orchestrator process exits or stalls without a customer-visible error.

Best monitoring pattern

Monitor agent run completion, not model quality. PulseProbe should receive a heartbeat only when the agent reaches the point that counts as done for your business process.

Step-by-step setup

  1. 1Create a probe for the agent workflow.
  2. 2Set the expected interval based on the agent schedule or run cadence.
  3. 3Call the heartbeat URL only after the agent completes its final successful handoff.
  4. 4Send a test run and confirm a recent check-in.
  5. 5Temporarily disable the schedule in a safe environment to verify a missed alert.

What not to send

  • Do not send prompts, completions, customer records, API keys, conversation transcripts, or tool outputs.
  • Do not include a real heartbeat URL in public examples.
  • Use placeholders like YOUR_HEARTBEAT_URL in internal docs and templates.

Built-in errors vs heartbeat monitoring

Application logs and model provider errors help debug failed runs. Heartbeat monitoring answers a different question: did the expected agent completion happen on time?

When not to use PulseProbe

  • Do not use heartbeat monitoring as the only control for safety-critical, medical, emergency, financial trading, or regulated systems.
  • Do not send secrets, customer records, prompt text, API keys, or private payloads to the heartbeat URL.
  • Heartbeat monitoring proves a check-in arrived. It does not inspect the quality of the workflow output.

FAQ

Does PulseProbe evaluate AI output quality?

No. It monitors whether the workflow checked in. It does not score model output, hallucinations, or task quality.

Can I include prompt metadata?

Avoid sending prompts or customer data. Use the heartbeat as a completion signal only.

Where should the heartbeat go in an agent workflow?

After the final successful action, such as saving the result, sending the handoff, or updating the system of record.