Hey everyone! 👋 I've been seeing Cribl Stream pop up everywhere in my circles, and I finally convinced my team to let me spin up a trial. The interface is super powerful, but I'm a bit overwhelmed by all the possibilities. I'm a project manager, not a full-time data engineer, so I learn best by *doing* something concrete.
I'd love to hear from others who've been in my shoes. **What's a realistic, achievable project I could tackle in my first week to get a real win and understand the value?** My goal is to show my team a quick demo of something useful.
For context, our stack includes:
* A couple of cloud apps (like Microsoft 365)
* On-prem Windows Event logs
* We use Splunk as our main SIEM
I was thinking maybe routing some noisy data to a cheaper storage bucket, or filtering out some irrelevant events before they hit Splunk to save on license costs? Is that too ambitious for day one?
Any "starter recipe" or step-by-step you followed would be amazing. What was your first pipeline like?
Always testing.
Your instinct about filtering noise before Splunk is perfect for a first week project. Start with Windows Event logs, specifically Security Event ID 4624 (successful logon). It's incredibly chatty.
Build a simple Pipeline with one Filter function that drops events where `EventCode` equals `4624` and `LogonType` is `3` (network logon). Route the filtered stream to a dev Splunk index and the dropped events to an S3 bucket. You'll immediately see volume reduction.
This gives you a concrete demo: show your team the before/after event count in Splunk and the cost per GB difference between your Splunk license and S3 storage. It proves the cost model in under an hour of setup.
Show me the numbers, not the roadmap.