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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →A missing heartbeat means your monitor did not receive the signal it expected—not necessarily that the Node.js job never ran. The process may have failed, exceeded its allowed runtime, finished without reporting success, or been unable to reach the monitoring service. Healthchecks.io, Cronitor, and Better Stack can all monitor scheduled work, but the right choice depends on how you schedule jobs, report outcomes, route alerts, and operate the monitoring service.
What a cron heartbeat can—and cannot—tell you
A heartbeat is a dead-man’s switch: a scheduled job sends a signal to a monitoring service, which alerts when the expected signal does not arrive within its schedule and grace period. Healthchecks.io describes failures it can help expose, including a machine outage, a stopped or misconfigured cron entry, a nonzero exit, and abnormally long execution (Healthchecks.io cron monitoring; Healthchecks.io overview).
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The alert identifies a missing or late signal, not its cause. A job may have run but failed before sending its completion ping; the ping request itself may have failed; or the task may still be running. Sending separate start and completion signals helps distinguish a run that began and never completed from one that did not report a start. It still does not prove that the logistics work was correct: a successful ping confirms the signal arrived, not that an import, dispatch, or reconciliation produced the right business result.
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Choose a monitor based on the operating model
All three options have documented heartbeat or check-in capabilities. Their documented differences are about instrumentation, scheduling, and how monitoring connects to operational workflows—not proof that one is universally better. The official materials cited here do not establish an apples-to-apples current price comparison for a particular job count.
#1 Best Overall
| Option | Documented fit | What to assess |
|---|---|---|
| Healthchecks.io | URL-based check-ins; start, success, and failure signals; cron schedules and grace periods; integrations; management API. | Schedule and timezone fit, signal semantics, alert destinations, API needs, and hosted versus self-hosted operation. Cron monitoring; overview; check configuration; Management API. |
| Cronitor | JavaScript SDK for Node.js, run/complete/fail lifecycle events, schedules, failure tolerances, duration assertions, and alert integrations. | Whether SDK lifecycle instrumentation, duration thresholds, environment configuration, or broader monitoring capabilities fit your needs. Cronitor job monitoring documentation. |
| Better Stack | Heartbeat URL, expected frequency and grace settings, explicit failure requests, and incidents routed through on-call settings. | Whether you want heartbeats connected to a wider incident and on-call workflow, and whether current plan limits fit your volume. Better Stack heartbeat monitoring documentation. |
Before choosing, compare the job or check limits, history and retention, notification destinations, incident features, and maintenance required for your expected volume. Confirm current plan details directly with each provider; the cited documentation does not establish comparable prices for a specific deployment scale.
Instrument a Node.js job so its signals mean something
Send start and completion signals in order
Healthchecks.io documents a Node.js example using Node’s HTTPS client, including an asynchronous pattern that sends a start ping, runs the task, and then reports success or failure. Use promises or async/await to sequence these requests; firing them independently can let the completion signal arrive before the start signal. The provider also advises that a ping failure should be handled or logged without preventing the monitored task from running (Healthchecks.io Node.js examples).
Rank #2
async function runJob() {
await sendPing("/start").catch(logPingError);
try {
await performLogisticsWork();
await sendPing("").catch(logPingError); // success
} catch (error) {
await sendPing("/fail").catch(logPingError);
throw error;
}
}This is an illustrative pattern, not a drop-in implementation: define sendPing and logPingError for your chosen provider, and decide how your scheduler should handle the rethrown task error. Do not let a monitoring request failure suppress the actual work or turn a successfully completed task into a false business failure.
Place success after the meaningful work
For a logistics task, send success only after the work you intend to monitor has completed—for example, after an import or dispatch result has been committed or verified. If the process reports success immediately after starting, a later failure can go undetected. If a job can partially succeed, report failure when the outcome does not meet your completion criteria and include useful diagnostic output when the provider’s API and your implementation allow it. These application-level checks—not the heartbeat alone—must establish whether the expected data or state was produced.
Rank #3
Protect ping credentials
Treat a Healthchecks.io check UUID or project ping key as a secret: someone who obtains it can send telemetry to that check. Keep it out of source control and public logs, and load it from your deployment’s secret-management mechanism (Healthchecks.io overview).
Set schedules and grace periods to match production
Configure the monitor with the schedule actually deployed and the server’s timezone. Healthchecks.io supports Simple, Cron, and OnCalendar schedule formats; its documentation warns that timezone mismatches can make expected pings appear early or late. Choose a grace period that allows for ordinary startup delay, runtime variation, and delivery latency without delaying a useful alert excessively (Healthchecks.io check configuration; cron monitoring).
Rank #4
When using duration tracking, the start ping also changes what the grace period means: it bounds the time allowed between start and success. Set it with the task’s expected runtime in mind, not just the gap between scheduled runs. A short tolerance can create alerts during normal variance; an overly long one can postpone detection of a genuinely stuck job.
When self-hosting Healthchecks.io makes sense
Healthchecks is open source and can be self-hosted, which may suit teams that need custom extensions, in-house compliance controls, or a learning environment. The project’s self-hosting guide lists Python 3.12+, Django 6.0, and PostgreSQL or MySQL among its building blocks and identifies the software as BSD 3-clause licensed (Healthchecks self-hosting guide).
Best Value
Self-hosting transfers operational responsibility to your team. The alert-sending management process must keep running for notifications to be sent, and the project FAQ warns that production-grade operation requires maintenance rather than being fire-and-forget (Healthchecks.io FAQ and overview). Account for database and application upkeep, availability, backups, and the alert-delivery path when comparing self-hosting with a hosted service.
Manage checks programmatically with the current API
If your deployment provisions checks as part of infrastructure or application lifecycle automation, Healthchecks Management API v3 supports creating, updating, pausing, resuming, and deleting checks, as well as reading logged pings. The documentation marks API v2 deprecated, so new integrations should use v3 (Healthchecks Management API).
Use heartbeat monitoring for the failure it is designed to catch
Heartbeat services monitor whether scheduled signals arrive; they are not substitutes for website uptime probes, application performance monitoring, or log aggregation. Healthchecks.io explicitly excludes those use cases in its documentation (Healthchecks.io overview). If you need those capabilities as well, treat them as separate monitoring requirements rather than assuming a cron heartbeat covers them.
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