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Build workflows that recover gracefully from failures and never lose data.
Read through the lesson, mark it complete when the concept is clear, then move to the next lesson in the sequence or jump back to the module map.
Production workflows must be reliable. A workflow that fails 5% of the time in production is broken — it just takes longer to notice. Every failure mode needs a handled path.
Transient failures — network timeouts, rate limits, temporary service unavailability. Fix: retry with backoff.
Data failures — unexpected input format, missing required fields, type mismatches. Fix: validate inputs before processing, route invalid data to a review queue.
Logic failures — your workflow has a bug. Fix: test coverage, monitoring, immediate alerting.
Dependency failures — an upstream service is down. Fix: circuit breaker, degraded mode, alerting.
Implement exponential backoff for all external API calls:
Attempt 1: immediate
Attempt 2: wait 1s
Attempt 3: wait 2s
Attempt 4: wait 4s
Attempt 5: fail permanently
Add jitter (random variation) to prevent thundering herd when many workflows fail simultaneously.
Any item that fails after all retries goes to a Dead Letter Queue (DLQ) — not the trash. The DLQ stores failed items with full context (input data, error, timestamp) for manual review.
Without a DLQ, failures are silent and data is lost. With a DLQ, failures are visible and recoverable.
Alert on:
Errors that don't alert are errors you'll find out about from users.