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.
The ingestion bill is visible. The storage bill is the one that compounds.
KubeCon EU 2026 made one thing clear: AI infrastructure is generating telemetry volumes that most observability budgets were never built to handle.
Healthcheck logs generate millions of identical lines per day and silently inflate your observability bill, but filtering them at the right layer can cut total log volume by 15 to 40 percent.
New Relic Pipeline Control bills you on data volume before any filtering happens, requires manual YAML config for every pipeline, and needs a separate Kubernetes install per environment.
Your Datadog bill keeps climbing because teams store more data to solve a retrieval problem, and that has never actually worked.
Application logs capture developer-written context about business logic and internal state; APM traces automatically record request flow and performance across services, and understanding the difference explains why both inflate your observability bill.
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