Every security source speaks a different language.
An AWS CloudTrail log names a behavior `eventName`; a firewall calls it `src_ip`; an application process outputs `client_ip` or `remoteAddress`. In the traditional SIEM pipeline, engineers must convert, map, and translate every single string before it enters indexed hot storage.
This is the **"Format Tax"**—the hidden resource sink where highly trained security analysts spend 70% of their operational hours acting as data janitors, maintaining thousands of fragile Regex parsers instead of actively tracking attackers.
The Normalization Bottleneck
Index-time log parsing is an obsolete architectural pattern. By forcing all standardization onto the ingest pipeline, you block the deployment of new visibility streams because building custom parsers takes days or weeks.
Furthermore, human effort becomes the primary scaling bottleneck. If your environment generates petabytes of disparate cloud, network, and endpoint logs, maintaining consistency becomes mathematical chaos.
Schema-On-Read & Open Telemetry
Rover avoids the format tax by loading original evidence raw. Instead of choking ingestion pipelines with heavy mapping steps, Rover utilizes a **schema-on-read** structure. Data from various cloud sources lands instantly as raw JSON within S3-backed arrays.
At query run time, Rover overlays standard open mapping formats (like OCSF or ECS) over raw telemetry dynamically. Analysts hunt across disparate sources seamlessly, while raw, unmodified logs remain perfectly preserved for forensic audits.
To eliminate your data parsing backlog, get in touch at contactus@roverhq.ai.