LogTrim: Reduce your Datadog costs

Hey Product Hunt - I’m Reece, the solo founder of LogTrim. I built LogTrim after seeing how quickly observability costs can grow when teams are sending huge volumes of logs to platforms like Datadog - including duplicated, noisy, or low-value data. The key idea is simple: reduce the logs before the ingestion cost is incurred. LogTrim sits in front of your observability platform and can filter, sample, deduplicate, mask PII, and turn logs into metrics before forwarding the remaining data. A lot of observability platforms already let you filter logs, but by that point you may have already paid to ingest them. I wanted to move that decision upstream. I’ve spent a lot of time keeping the data plane lightweight and fast, while making setup as painless as possible. I’d especially love feedback from people dealing with high Datadog/logging bills: what are you currently doing to control log volume, and what’s the biggest pain point?