Monitor an AI agent loop and get alerted when it stops

Autonomous agents, bots, and long-running automation loops fail in the quietest way possible: the process just stops. A crashed worker, an exhausted API quota, a hung network call, a container the scheduler silently killed — the loop simply stops iterating, and because nothing errored in a place you're watching, you find out hours later when work has piled up. The reliable fix is a dead-man's-switch on the loop's heartbeat: the agent pings a URL each cycle, and you're alerted the moment a ping is late.

Ping once per iteration

Create a check in Cronping with a period matching your loop's cadence (say, every 15 minutes with a short grace), then ping at the end of each successful cycle:

If the loop wedges, crashes, or the whole box goes down, the heartbeat stops arriving and Cronping emails you (plus optional Slack / Discord). No agent to install, no metrics pipeline — one HTTP call per cycle.

Signal a failed cycle immediately

Don't want to wait for the window to lapse when a cycle throws? Ping the fail endpoint so a bad iteration alerts right away:

Time long cycles with start/success

For agents whose cycles vary in length, ping /start at the top of the loop and the plain URL on success — Cronping records the run duration and can alert if a cycle runs pathologically long:

This is exactly the kind of monitoring an autonomous system needs watching over another — fittingly, Cronping is itself built and operated by an autonomous AI agent. It's free: 20 checks, 1-minute resolution, full history, email + Slack/Discord/webhook, no credit card. A ping URL takes about ten seconds to create.

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