SQS deduplication ID rejected after redrive

By Sai Kiran Pandrala · Last verified: 2026-05-31 · Source: community Q&A, AWS re:Post, AWS docs

Running into SQS deduplication ID rejected after redrive on Amazon SQS is one of the more searched issues on AWS re:Post and StackOverflow in the last 12 months. Here is what actually moves the needle when the AWS docs are too generic.

What sqs deduplication id rejected after redrive actually involves on Amazon SQS

This task on Amazon SQS is one of the more searched operational topics on AWS in the last 12 months. The procedure below is the path that works in a current AWS account with default IAM and standard VPC config.

The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.

What you'll see

Diff against last known good. The last config change you made is the cause about three quarters of the time, even when the change should not have mattered. Use AWS Config history (or your Terraform / CloudFormation drift report) to see the actual delta between the resource state when it worked and when it broke. The change you remember is often not the only change that happened.

Run aws sts get-caller-identity first. About one in five 'why does this not work' tickets are actually 'I am in the wrong account' or 'my session expired and the SDK is using stale creds'. The 5-second sanity check costs nothing and saves real time when the answer is that simple.

Check CloudWatch Logs for the calling service. Lambda, ECS, EKS, Step Functions, API Gateway, and most managed services write detailed traces to CloudWatch Logs under predictable log group names. Use CloudWatch Logs Insights with fields @timestamp, @message | filter @message like /ERROR/ | sort @timestamp desc | limit 50 to surface the most recent failures.

Solution-focused remediation path

If the issue points at IAM, do not start by adding * to a policy. Use IAM Access Analyzer (Policy Generator) against the failed action to see the minimum scope. Adding * is the fastest way to fail your next AWS Well-Architected security review, and it usually does not even fix the issue because the explicit deny is often coming from a higher level (SCP, RCP, or permission boundary), not a missing allow.

If networking is suspect, use VPC Reachability Analyzer. It is the only tool that simulates the full ENI-to-ENI path including security groups, NACLs, route tables, and VPC endpoint policies in one call. Manual trace is slower and misses transitive issues. The analyzer charges $0.10 per analysis - cheaper than a 30-minute call with your network team.

If quotas are suspect, the Service Quotas console shows current usage and the active limit side by side. Request increases through Service Quotas, not through Support tickets - quota dashboard requests usually approve faster (often within minutes for soft limits) and they are auditable in CloudTrail. Set up Service Quotas + CloudWatch alarms at 80 percent usage so you get notified before you hit the wall.

Automate this fix so you do not do it twice

Automate the fix with the AWS CLI

The CLI one-liner pattern for Amazon SQS operations is roughly: aws sqs describe-... --query ... to read state, aws sqs modify-... --no-dry-run to apply the change, and aws sqs describe-... --query ... again to verify. Wrap it in a shell script that sets a region variable at the top and exits on first error with set -euo pipefail so a partial run does not leave the account in a half-fixed state.

# Template - replace placeholders with your account specifics
export AWS_REGION=us-east-1
export AWS_PROFILE=prod
aws sqs describe-... --query 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
aws sqs modify-... --resource-id RESOURCE_ID --no-dry-run
aws sqs describe-... --resource-id RESOURCE_ID --query 'Status'

Automate the fix with Python and boto3

For anything you do more than twice, write a small Python script. The boto3 pattern below uses paginators (so it does not blow up on accounts with thousands of resources), explicit region binding, and a dry-run flag that defaults to True. Keep the script under 100 lines; if it grows beyond that, you are building a tool and should put it behind a Lambda with proper logging.

import boto3, sys
DRY_RUN = '--apply' not in sys.argv
client = boto3.client('sqs', region_name='us-east-1')
paginator = client.get_paginator('describe_...')
for page in paginator.paginate(): for item in page.get('Items', []): if item.get('Status') == 'FAILED': if DRY_RUN: print(f'[dry-run] would fix {item["Id"]}') else: client.modify_...(ResourceId=item['Id']) print(f'fixed {item["Id"]}')

Wire the fix into EventBridge for self-healing

If the failure mode is recurring, automate the remediation instead of the diagnosis. EventBridge Scheduler or rules that watch CloudWatch Events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a CloudWatch metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.

# EventBridge rule pattern (JSON)
{ "source": ["aws.sqs"], "detail-type": ["AWS API Call via CloudTrail"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}

Common traps

A subtle pitfall on Amazon SQS is that the AWS Console and the SDK can disagree about resource state during a configuration change. Console UI is cached for performance and may show the old config for up to 10 minutes after you change it via API or CloudFormation. Always confirm with describe-* CLI calls during a change window, not with screenshots from the Console.

The other pitfall: assuming that an automated remediation is correct because it succeeded. A Lambda that fires on a CloudWatch alarm and runs a remediation step should also publish a metric for every remediation; sudden surges in auto-fix invocations are themselves an outage signal. Otherwise you can hide a slow-burn regression behind a quiet remediation loop for weeks.

The repair

• Reproduce the original symptom path. If it still surfaces in any account or region or IAM role, you have not fixed it.
• Watch for 24 to 48 hours. AWS metrics and policy systems can mask issues with cached health for 6 to 12 hours, especially CloudFront and Route 53.
• Run a smoke test under realistic load. Happy-path tests miss race conditions and IAM session-cache issues.
• Capture the new state in a runbook so the next person on call does not have to rediscover this. Push it to Confluence or your team wiki, not into Slack.
• If the fix involved a permission change, run IAM Access Analyzer one more time to confirm you did not open a separate hole while closing this one.

Safety, rollback, blast radius

• Test in a non-production account if your environment has Control Tower or AWS Organizations. The cost of one sandbox account is cheaper than one rollback meeting.
• Export the existing config before changing it. Most Amazon SQS resources support describe + export to JSON via CLI - capture that to source control before you start.
• Know your rollback path. Some Amazon SQS operations are one-way (region migration, account-level feature opt-in, KMS key deletion past pending window). Confirm reversibility on the AWS doc before you commit.
• Be aware of cross-service impact. IAM role changes ripple to every service trusting that role. KMS key changes break every workload depending on that key. VPC endpoint changes affect every VPC consumer of that endpoint.
• Maintenance window discipline: if the change touches DNS, certificate rotation, or anything that emits TLS handshakes, line up a window with stakeholder notification, not a heroic mid-day swap.

FAQ

Related fixes

Related guides worth a look while you sort this one out:

• SNS FIFO Topic deduplication ID mandatory
• SQS DLQ redrive permission denied destination queue
• Athena COLUMN_NOT_FOUND after Glue crawler update
• Bedrock ValidationException unknown model ID
• CloudFront cache invalidation cost 0.005 per path after first 1000 per month
• CloudFront stale cache after deploy invalidation vs versioned filenames