I recently discovered what I consider a serious design flaw in AWS DynamoDB Triggers that I believe deserves more attention from the community.<p>Here's the issue: DynamoDB Triggers can only point to the `$LATEST` version of a Lambda function. Yes, you read that right - there's no built-in way to target a specific version or alias through the console. This means any changes to your Lambda function's `$LATEST` version immediately affect your production triggers, whether you intended to or not.<p>Consider this scenario:
1. You have a critical DynamoDB table with a Lambda trigger handling important business logic
2. A developer pushes changes to the Lambda's `$LATEST` version for testing
3. Surprise! Those changes are now processing your production data<p>The workarounds are all suboptimal:
- Create triggers through CloudFormation/CDK (requires delete and recreate)
- Maintain separate tables for different environments
- Add environment checks in your Lambda code
- Use the Lambda console to configure triggers (unintuitive and error-prone)<p>This design choice seems to violate several fundamental principles:
- Separation of concerns
- Safe deployment practices
- The principle of least surprise
- AWS's own best practices for production workloads<p>What's particularly puzzling is that other AWS services (API Gateway, EventBridge, etc.) handle versioning and aliases perfectly well. Why is DynamoDB different?<p>Some questions for the community:
1. Has anyone else encountered production issues because of this?
2. What workarounds have you found effective?
3. Is there a technical limitation I'm missing that explains this design choice?
4. Should we push AWS to change this behavior?<p>For now, my team has implemented a multi-layer safety net:
```python
def lambda_handler(event, context):
if not is_production_alias():
log_and_alert("Non-production version processing production data!")
return<p><pre><code> if not validate_deployment_state():
return
# Actual business logic here</code></pre>
```<p>But this feels like we're working around a problem that shouldn't exist in the first place.<p>Curious to hear others' experiences and thoughts on this. Have you encountered similar "gotchas" in AWS services that seem to go against cloud deployment best practices?
I don’t know as I’ve ever seen Lambda versioning being used for anything in the wild. Folks just spin up different dev and staging environments for testing.
> Consider this scenario: 1. You have a critical DynamoDB table with a Lambda trigger handling important business logic 2. A developer pushes changes to the Lambda's `$LATEST` version for testing 3. Surprise! Those changes are now processing your production data<p>...why would a DynamoDB trigger for prod data be pointing to a Lambda where people push things that are still being tested?<p>> The workarounds are all suboptimal...- Maintain separate tables for different environments<p>This is not "suboptimal" or a "workaround"; it's the proper way to do things lol<p>Just as one would have separate RDS instances for QA/staging/test versus production.<p>Test Lambda --> Test DynamoDB table<p>Prod Lambda --> Prod DynamoDB table
I mean the solution would be to have a different test table an also a test lambda. You can deploy to test lambda and test it by changes to the test table.