We didn't want to spend $1M per year on Splunk or other traditional logging tools, so we started deleting logs or moving them into S3. This made investigations painfully difficult. Sometimes the data we wanted to query was missing, and S3 was too slow to search.

We found that, by indexing data in S3 in an intelligent way, we could provide extremely fast search across massive data sets at low cost. Cyber threats often take months to be detected, and most teams don't have access to their historical data because it's exorbitantly expensive to store and access at scale. This forces companies to make a critical trade-off: pay a fortune and make sense of all your data, or selectively retain some of it over a shorter period of time and suffer from blind spots.

That's why we built Scanner: a powerful log indexing tool that gives builders the ability to run fast search, time series, and threat detections on top of the logs they're storing in S3. We believe it should be possible to store logs at massive scale and low cost, for any period of time, without sacrificing speed. Your tools should scale with your data.