Hey everyone. I've been knee-deep in log management and SIEM evaluations for our current startup and the last one. Panther keeps coming up as a modern, code-based alternative to the legacy giants (Splunk, etc.) and cloud-native options (Datadog's security offering, Sentinel).
Everyone talks about the *potential* savings, but I'm trying to move beyond "cheaper than Splunk" vibes. Has anyone actually built a real, quantified ROI model for implementing Panther?
I'm thinking beyond just the monthly license cost. The real calculation seems messy and I'd love to compare notes. For instance:
**Cost Side:**
* Panther's pricing (based on log volume/features).
* Engineering hours to: write and maintain detections as code, manage the infrastructure (if self-hosted), onboard new data sources.
* Associated AWS/Azure/GCP costs for the data lake (S3, Athena, etc.) if using their Data Lake mode.
**Benefit Side (the hard part to quantify):**
* Reduction in mean time to detect/respond (MTTD/MTTR). How do you even baseline this?
* Avoided costs of a potential security incident. Fuzzy, but maybe based on industry averages for a company our size?
* Efficiency gains from unified queries across security and ops data.
* Hard savings from decommissioning a legacy log tool or reducing scope/seat count on a more expensive platform.
For us, the appeal is the "write once, run anywhere" for detections and the control. But engineering time is our biggest expense, so shifting left on security ops has a real cost.
Did you build a spreadsheet? What were the key variables that made or broke the business case for you? Especially interested if you were coming from a more traditional SIEM or a DIY ELK stack.