Production Readiness Dashboard
Key metrics and pre-launch checklist for production automation
An automation that only works when you're watching isn't really an automation. Production-grade pipelines run reliably 24/7, recover from errors, alert you only when needed, and cost predictably.
The transition from development to production is where most automation projects fail. A pipeline that works perfectly in testing breaks in production because an API rate-limits you, a cron job overlaps with the previous run, or an edge case in the data causes a silent failure that compounds over days. This module covers the operational infrastructure that prevents these failures: scheduling strategies, heartbeat monitoring, structured error handling, cost tracking, and the observability patterns that let you sleep at night while your automations run.
Automation Cost Breakdown
Realistic monthly costs for a typical startup automation stack
| Service | Free Tier | Paid Pricing | Use Case |
|---|---|---|---|
| GitHub Actions | 2,000 min/mo | $0.008/min | Cron triggers, CI/CD |
| Claude API | None | $3/M input, $15/M output | AI processing, summarization |
| OpenAI API | None | $2.50/M input, $10/M output | Embeddings, classification |
| Vercel Cron | 1 cron/day | $20/mo (Pro) | Serverless triggers |
| n8n Cloud | None | $24/mo starter | No-code workflows |
| AWS SES | 3,000 emails/mo | $0.10 per 1,000 | Email delivery |