The Complete SQS Troubleshooting Guide (The Most Common SQS Failure Traps)
.jpeg)
SQS is a powerful tool, but it requires you to respect its boundaries.
Amazon SQS (Simple Queue Service) is deceptively simple.
You send a message, you receive a message, you delete a message.
But "Simple" does not mean "Foolproof."
Most teams run into the same invisible walls: messages that vanish, queues that won't drain, bills that spike, and retries that loop forever.
This Fix-It Hub collects the most common SQS failure modes—and exactly how to fix them.
Part 1: Why Your DLQ Is Ignoring You
The Symptom: You configured a Dead-Letter Queue (DLQ), but failed messages never show up. They just disappear silently.
The Trap: It isn’t a bug; it’s usually a permission or logic error.
- Silent Drops: If your Source Queue cannot write to the DLQ (IAM permissions) or encrypt with the DLQ's key (KMS), SQS drops the message.
- Premature Deletion: If your code catches an exception and still calls
deleteMessage, SQS thinks it succeeded.
The Fix:
- Validate the Redrive Policy link.
- Check KMS/IAM permissions on the DLQ.
- Stop "swallowing" exceptions in your consumer.
👉 Read the full Fix-It
Part 2: Why Messages "Disappear"
The Symptom: Messages enter the queue but vanish later without being processed or deleted by a consumer.
The Trap: Confusing Retention Period with Visibility Timeout.
- Retention is a death clock. Once it expires (default 4 days), the message dies.
- The DLQ Trap: If your DLQ has the same retention period as your source queue, a message might age out while it is retrying, leaving you nothing to debug.
The Fix:
- Treat Retention as the absolute lifespan.
- Golden Rule: Always set DLQ Retention to 14 Days (Maximum) to guarantee you have time to debug old failures.
Part 3: Why Your Queue Looks Empty (But Costs a Fortune)
The Symptom: Your queue is empty, but your AWS bill shows millions of ReceiveMessage API calls. Or, your application feels sluggish picking up new work.
The Trap: Short Polling (the default).
- Short polling checks a subset of SQS servers and may return empty even when messages exist elsewhere.
- This forces your consumer to spin in a tight loop, racking up API costs for zero data.
The Fix:
- Enable Long Polling by setting
ReceiveMessageWaitTimeSecondsto 20. - Critical Safety Check: Ensure your Client HTTP Timeout is longer than the SQS wait time (e.g., 30s client vs 20s SQS) to prevent crash loops.
Part 4: Why Redrive Creates Infinite Loops
The Symptom: You fix a bug, redrive your DLQ, and watch the queue drain... only to fill up again instantly with the same errors.
The Trap: "Reload vs. Retry."
- Redriving moves messages back to the source, but it exposes them to consumers immediately.
- If you haven't fixed the root cause (bad code) or the payload (poison data), the message will fail, increment its
ReceiveCount, and re-DLQ in seconds.
The Fix:
- Fix the Consumer First: Verify the fix with a single message locally.
- Check for Poison: Scan the DLQ for malformed JSON before redriving.
- Velocity Control: Don't dump 100k messages at once if your DB is fragile.
Summary
SQS is a powerful tool, but it requires you to respect its boundaries.
- DLQs need permissions.
- Retention needs a buffer (14 days).
- Polling needs patience (Long Polling).
- Redrive needs a strategy (Reload, don't just Retry).
Master these four, and your queues will be boring, predictable, and cheap—exactly how infrastructure should be.
Aaron Rose is a software engineer and technology writer at tech-reader.blog and the author of Think Like a Genius.
Comments
Post a Comment