Expectation monitoring for automated work.
Glnc catches the quiet failure: your automation reports success, but the expected result does not happen.
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Example expectation
Passing
Completed on timeWarning
Running later than usualFailing
Run #1842 Reported OK
The sync reported success, but created only 12 of the 50 expected records.
Frequently asked questions
Expectation monitoring checks whether recurring automated work produced the expected result, not only whether its process ran. In Glnc, a Check combines a schedule with optional output rules, and Runs report status and metadata so missing, late, failed, slow, or unmet output becomes visible.
Read the expectation monitoring guideHave the cron job report Run status and output metadata to a scheduled Glnc Check. An output rule compares the reported value with the expected threshold, so a succeeded Run can still show a warning or failing status when the output is wrong.
Follow the cron output guideA heartbeat shows that a process checked in within an expected window. Expectation monitoring can also evaluate completion, duration, and reported output, so use it when a timely check-in may still hide an incomplete, slow, or low-output result.
Compare heartbeats and expectationsKeep the existing scheduler or automation platform, then report Run status and metadata to Glnc. Define rules for a useful result, such as a record count or artifact flag, so Glnc evaluates the outcome after execution rather than whether the process merely ran.
Learn about automation outcomesGlnc supports latest-run and windowed output rules over reported Run metadata. Rules compare values with equality or numeric operators; windowed rules can evaluate an average, sum, minimum, maximum, or count across a trailing period.
Explore output expectationsWith a full-access API key, an agent POSTs the complete Check configuration, including its name, to create it. It PUTs the complete configuration to update an existing Check, then POSTs each Run with result, a stable report_id, and observational evidence. Account-level monitoring requests do not use X-Entity.
Read the API referenceWhy existing monitors miss it
Cron jobs, Zapier and Make scenarios, custom scripts, AI agents, webhook-driven pipelines — each one can finish, report success, and still not produce the expected business result.
Uptime monitoring asks
Is the endpoint available?
Job monitoring asks
Did the process run?
Glnc asks
Did the expected outcome happen — even when the run itself reports success?
How it works
Define the result you expect.
Send the result when the automation runs.
See whether the work met the expectation.
Private beta
Join the beta and monitor your first expected result.
