Elastic (NYSE: ESTC), the Search AI Company, has introduced Streams, an agentic AI-powered solution that redefines how Site Reliability Engineers (SREs) interact with logs. The platform automatically parses and partitions raw log data, surfaces critical anomalies, and gives teams actionable insights—helping engineers move from symptom to solution in minutes.

For years, SREs have struggled with log overload—massive data volumes, unclear signals, and dashboards that show what’s broken but not why. Elastic’s new Streams solution directly tackles that problem. It uses AI to extract relevant fields, automatically identify significant events like out-of-memory errors or internal server failures, and deliver early warnings that reveal the root cause of system issues.

“Streams makes logs your most valuable asset,” said Ken Exner, Chief Product Officer at Elastic. “It automatically finds the signal in the noise, surfacing critical events from any log source. This gives SREs time back, allowing them to move from symptom to solution in minutes.”

Powered by the Elasticsearch platform, Streams introduces a complete overhaul of traditional log pipelines. It adapts dynamically to new log formats, replacing complex manual data engineering with AI-driven automation. The platform helps teams maintain full observability without incurring the high storage and management costs associated with traditional methods.

Key capabilities include:

• Log everything, effortlessly – AI-driven ingestion supports any log format from any source.

• Get answers, not just data – Automatically surfaces significant events for faster root-cause analysis.

• Cost-effective visibility – Reduces complexity and total ownership costs through intelligent data organization.

With Streams, Elastic is positioning logs not as a noisy byproduct, but as a rich source of operational intelligence—transforming them into a first-line tool for proactive system reliability.

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