Hey folks, I've been deep in the weeds configuring Cribl Stream to manage some pretty hefty S3 log archives, specifically around implementing automated data retention and deletion. It's a powerful feature, but getting the orchestration right between Cribl's Pipelines, S3 Destinations, and AWS lifecycle policies felt like a bit of a puzzle at first.
The core idea is to use Cribl not just to route data, but to *tag* it on the way out, so S3's native lifecycle rules can handle the actual deletion. This keeps the logic clean and leverages AWS's battle-tested cleanup processes. Here's the workflow I settled on:
1. **Pipeline for Tagging:** Create a Pipeline after your S3 Destination. Use a **Filter** Processing Function to isolate the data streams you want to apply retention to. Then, the key is the **AWS S3 Metadata** function.
2. **Configure the AWS S3 Metadata Function:** This is where you attach the S3 object tag that a lifecycle rule will key off of. For example, you might add a tag like `Retention=30days`.
```javascript
// Example within the AWS S3 Metadata function config
// Setting Object Tags
Object Tags: {
'Retention': '30days',
'Project': '${Cribl.getField("project")}'
}
```
You can make this dynamic based on event fields! The function can also set the storage class, which is handy for tiering before deletion.
3. **S3 Lifecycle Policy:** Over in your AWS S3 bucket, you create a lifecycle rule that targets objects with the specific tag (e.g., `Retention=30days`) and defines an expiration action after the desired number of days.
The beauty here is separation of concerns. Cribl becomes the "classifier" at ingestion time, and S3 is the "executor" based on time elapsed. This is far more reliable and scalable than trying to run a separate cleanup job.
A few nuances I discovered:
* The S3 Destination in Cribl needs the `s3:PutObjectTagging` permission for its IAM role, which is sometimes overlooked in basic setups.
* Tag-based lifecycle rules can take up to 48 hours to actually run after the object becomes eligible, so build in a grace period.
* For more complex, non-time-based retention (like "delete after 5 successful pipeline runs"), you'd likely need a different approach, perhaps using Cribl to write to a queue that triggers a Lambda function.
Has anyone else set this up? I'm curious if you used a different method, like having Cribl emit events to an SQS queue for a custom deleter, or if you've played with the **S3 Object Expiration** feature within Pipelines for other use cases. Also, how do you handle validation to ensure tags are being applied correctly? I built a small monitoring Pipeline that samples and logs the metadata being sent.
editor is my home