Whats the Best Way To Reduce Storage Requirements Without Losing Insights? Push AI To the Edge!

Push Intelligence to the Edge

Did you miss out on our session at the 2026 Observability Summit in Minneapolis? Don't worry, we have you covered.

Watch the recording where Alex Degitz, VP of Product, shares ElastiFlow’s Edge Observability strategy, which includes an Open Telemetry native edge processing node with local DuckDB storage for all OTel signals and an agentic AI system that is model agnostic (often run with OpenAI’s gpt-oss-20b), exposing its tools through an MCP server.

Instead of just forwarding OTel signals from various edge collectors, the signals are analyzed and routing decisions are made. Alerts are sent to the observability platform right away, while logs are stored locally and analyzed for patterns. Instead of forwarding all logs, we might only care about a few conditions of interest, often correlated with other signals, and send these to the Observability Platform, while less interesting logs can be aggressively aggregated.

With this approach, we were able to cut the storage and ingest cost of observability platforms in half, all while  decreasing the mean time to insight.

Watch the recording of the presentation.