Use cases
Every scheduled run should prove it finished
Start with your AI agents. Then cover the cron jobs you forgot about.
AI agents & LLM pipelines
Scheduled agents fail without errors. CronObserver alerts you when a run doesn't finish on time.
- Claude Code routines, Codex jobs, n8n and Make flows, LangGraph and CrewAI behind a cron
- Batch LLM jobs (OpenAI and Anthropic Batch APIs): know when the results never arrived
- RAG reindexing and document ingestion: catch a knowledge base that stopped updating
- Evals and retraining runs on a schedule
- Send the model, item count and duration in the check-in payload for context
Agent platforms with a built-in scheduler
When the scheduler lives inside the agent, it can't be its own watchdog. Step-by-step setup, tested on each platform:
DevOps & Platform
Kubernetes CronJobs, Airflow DAGs and CI schedules: every run confirms success with one HTTP ping.
- Catches suspended CronJobs and GitHub schedules that silently stopped
- Payload logging for debugging
- Works with any stack that can call curl
Fintech & Billing
Heartbeat every settlement, reconciliation or FX job, so a missed run is flagged before customers notice.
- Grace periods tuned per job
- Escalation to Slack, Teams or webhook (Orbital)
- 365-day history on Orbital
E-commerce & Operations
Catalog syncs, invoices and notification jobs that must run during peak hours.
- Email alerts on every plan, webhooks on Orbital
- Free plan covers 3 critical jobs
Health tech
Monitor lab imports, reminder schedulers and billing jobs to avoid silent failures.
- Check-ins for every scheduled import and reminder run
- Alerts routed to the on-call team
- Check-in history kept for 365 days on Orbital
Your agent will fail at some point. Hear about it first.
CronObserver works with any environment that can make an HTTP request. Add a check-in at the end of the run and we handle the rest.