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A Node.js /health route can show whether a service instance is alive or ready to receive traffic; it cannot prove that a scheduled report, backup, import, or queue task completed. Monitor those jobs separately with an external heartbeat: send success only after the work finishes, and let the monitor alert when the expected signal is late.
How do I know if my health check endpoint is working?
First decide what the endpoint is meant to tell its caller. A probe that reports whether the process should keep running answers a different question from one that says whether the instance should receive requests. For Kubernetes, these are liveness and readiness probes; a startup probe can defer the other checks while an application initializes. Other platforms may use different labels or behavior. See the Kubernetes probe documentation.
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Keep liveness focused on the process
A failed Kubernetes liveness probe can lead to a container restart. Avoid making liveness fail simply because a downstream service is temporarily unavailable if the Node.js process itself is still functioning: doing so can turn a dependency outage into unnecessary restarts. Liveness is for detecting a process that should no longer continue running.
Use readiness to control traffic
Readiness indicates whether an instance should receive traffic. If the application cannot serve requests safely, a failed readiness check can communicate that it should stop receiving them while it recovers. Keep the route fast and bounded, and define what “ready” means for the service rather than treating every dependency as an automatic reason to restart the process.
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Account for slow startup
If initialization takes time, Kubernetes startup probes can prevent liveness and readiness checks from acting too early. Configure the route and the deployment’s probe settings together: an endpoint only helps if the platform calls it at the right time and interprets its result as intended.
A health route is not a process supervisor. Node.js v26.10.0 documentation warns that it is not safe to resume normal operation after an uncaughtException, and recommends using an external monitor in a separate process to detect failures and recover or restart as appropriate. See the Node.js process documentation.
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How do I monitor my cron jobs?
Create an external heartbeat check for each independently important scheduled job. The monitor provides a unique ping URL and expects a request on the schedule you configure. If that request does not arrive within the expected interval and grace period, it can alert that the job is late or down. Because the monitor is outside the job’s process, it can detect a missed run even when the job crashes before it can log or report the problem.
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- Regular cadence: Set an expected interval and a realistic grace period for jobs that run at a steady frequency.
- Wall-clock schedule: Use a cron or calendar schedule when the job is intended to run at a particular time, such as nightly. Set the timezone used by the machine running the scheduler and allow for ordinary startup and runtime variation.
A monitor’s grace period is the time it tolerates a missed expected signal before alerting. Too little grace can create alerts for normal delays; too much can delay detection. Choose it with the scheduler’s actual timing and the cost of a late alert in mind.
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Send success only after useful work is complete
A start signal can show that a job began, while a success signal confirms it reached its meaningful completion point. For a job whose run time varies, configure the monitor to expect the completion signal within an appropriate window after the start. Never send success from a finally block that also runs after errors: that would mark a failed run as healthy.
- Record the task start and, if supported and useful, send a start signal.
- Run the scheduled work while preserving its exit status and useful diagnostic output.
- Send the success signal only when the work has completed successfully.
- On failure, send an explicit failure signal with safe diagnostic context, then return a nonzero exit code to the scheduler.
Keep heartbeat URLs secret. Treat each URL as a capability that can report a job’s status; do not put it in source control, public logs, or output visible to clients.
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Which heartbeat monitor features matter?
Healthchecks.io and Better Stack documentation describe two hosted options for missed-run monitoring. The comparison below is limited to the cited documentation; it does not establish which service is more reliable or less expensive.
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|---|---|---|
| Missed-run detection | Unique ping URL, expected timing, and grace period; alerts when a check is late or down. | Expected heartbeat frequency and grace period; a missed heartbeat triggers an incident. |
| Schedule type | Simple intervals, cron, and systemd OnCalendar schedules; cron checks require a timezone. | The cited heartbeat page describes a periodic cron-style example; verify exact schedule options for your use case. |
| Failure reporting | Optional start and failure signals. | A /fail path and documented reporting of exit-code and output information. |
| Other configuration considerations | Schedule model, timezone, grace period, allowed HTTP method, and integrations. | Frequency, grace period, escalation settings, and failure-payload needs. |
See Healthchecks.io documentation, its cron and schedule configuration guide, and Better Stack heartbeat-monitoring documentation. Check the current product documentation for schedule details and integrations relevant to your deployment.
How should health checks and heartbeats work together?
Use each signal for the failure it can actually detect. A platform probe answers whether a running service instance should continue or receive traffic. A job heartbeat answers whether an independently scheduled task reached its expected completion point. A service can pass its health check while a nightly export has silently stopped running; a heartbeat can report that missed run without changing how the service’s HTTP health route works.
Quick Recap
- Use liveness, readiness, and startup behavior according to the deployment platform’s semantics.
- Give each important scheduled task its own descriptive check and schedule.
- Route alerts to people or systems that can act on them, and include enough safe failure context to aid diagnosis.
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