Am I the only one who finds the license calculation overly complex?

Having recently completed a comparative performance analysis of several EDR platforms, I was compelled to examine the administrative and operational overhead of each solution. While evaluating Cybereason, I encountered a significant and unexpected friction point: the methodology for calculating and forecasting license consumption appears to be needlessly intricate, introducing considerable uncertainty into capacity planning and cost forecasting.

My primary concern stems from the apparent conflation of multiple, variable factors into a single consumption metric. From my documentation review and discussions with sales engineering, the calculation seems to incorporate:
* A base allocation per protected endpoint, which is standard.
* Additional consumption tiers based on data ingestion volumes, which is also understandable.
* However, the specific weighting of forensic data (e.g., process trees, network connections) versus telemetry data, and how they map to the licensed "unit," lacks transparent, deterministic formulas.

This complexity prevents the creation of a reliable predictive model. For a proper benchmarking mindset, one must be able to define a controlled workload and accurately predict its resource consumption. For instance, if I simulate an attack chain involving 100 processes across 50 endpoints, I should be able to calculate the resultant license impact with a known margin of error. The current opaque calculation turns this into a stochastic exercise.

To illustrate, I attempted to reverse-engineer the consumption from a test deployment's daily activity. The observed license usage, as reported in the management console, did not correlate linearly with any single measurable variable I could isolate (endpoint count, alert volume, stored data size). The variance was significant enough to invalidate simple linear regression models.

```sql
-- Example of the type of analysis I attempted
SELECT
date,
reported_license_units,
active_endpoint_count,
total_alert_volume,
forensic_data_mb
FROM deployment_daily_metrics
WHERE date >= '2024-05-01';
```
The correlation coefficients between `reported_license_units` and each independent variable were all below 0.7, indicating a poor fit for any single-factor model.

This opacity creates tangible issues for reproducible budgeting and scaling. In performance testing, we value metrics that are directly tied to workload. If the licensing model behaves like a black-box algorithm with undocumented coefficients, it becomes a risk variable rather than a predictable cost of operations.

I am inquiring if other community members have undertaken similar analyses or have developed internal models to project Cybereason license consumption with any degree of confidence. Furthermore, has anyone successfully obtained a fully specified, mathematical formula from Cybereason support that details the exact contribution of each data type and action to the license counter? Without this, it feels akin to running a benchmark where the scoring algorithm is proprietary and undisclosed.

-- bb42