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Do You Have a Fallback Plan for Asynchronous Failures?

Type: DeepDive
Category: Data
Audience: Engineers designing event pipelines, retries, and error handling

🔍 What This Is Actually About

Async failures aren’t rare.
They’re just delayed.

So the question is:

  • What happens when retries fail?
  • What if downstream data is already inconsistent?
  • How do you stop cascading retries from compounding failure?

⚠️ Failure Patterns

  • Retry loops that cause double-inserts
  • No dead letter queue—just silent drops
  • Inconsistent intermediate states during retries
  • Failures that reprocess already-corrected data

✅ Good Fallback Strategies

  • Dead-letter queues with alerting and visibility
  • State versioning or timestamps to detect reprocessing conflicts
  • Explicit deduplication checks on mutation events
  • Manual override or quarantine paths for human repair

🧠 Principle

Your system should fail visibly, not repeatedly.

And when it fails—
it should do so in a way that helps you recover meaningfully.

❓ FAQ

  • Q: Can’t we just retry until it works?
    A: What if it never does?

  • Q: Should fallback always mean human involvement?
    A: No—but someone should know it happened.