Troubleshooting: Agent Loops
An agent stuck in a loop can burn a GPU node and a token budget fast. Here is how to detect and stop it.
An agent retries the same failing tool forever, cycles between planning steps, or re-enters a state endlessly — and cost and GPU usage climb with nothing to show for it.
Agent loops on Kubernetes come from failing tool calls retried without backoff, planning cycles with no progress check, bad stopping conditions, or an MCP/tool error the agent cannot interpret. We help you add loop and progress detection, hard step and cost/token limits per task, timeouts, exponential backoff with circuit breakers on tool/MCP calls, and action-level tracing so you can see the cycle — so a misbehaving agent fails safe instead of running up unbounded spend.
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