How Grepr uses continuous pattern extraction and AI to detect anomalies and build monitoring strategies to prevent failures.
Every AI conversation at the summit dragged a cost conversation behind it, and most teams already knew which one was winning.
Grepr's free tier is live: perpetual, no credit card, 4 TB of logs and 8 TB of traces a month to run on your own data.
Both pipelines claim to cut observability costs with AI, but the rule management, trace handling, and S3 storage models work in completely different ways.
Datadog bills are climbing again, and the teams paying them will be in Minneapolis this month. Grepr will be there too.
Unstructured logs make parsing, searching, and alerting harder while driving up storage costs, so this guide covers the structured logging practices that matter most for production systems in 2026.
Filter rules force you to guess which data matters before you need it. Pattern-based sampling with full retention doesn't.
HIPAA requires six years of telemetry retention, and a two-tier architecture that sends reduced data to your observability platform and raw events to S3 with Parquet and Iceberg satisfies the mandate without the six-figure storage bill.
Kubernetes environments drown observability platforms in redundant log data, and Grepr uses semantic machine learning to reduce that volume by up to 90 percent while preserving every raw event in low-cost S3 storage.
.webp)
.gif)
.webp)
.webp)
.avif)
.gif)
