Goodbye log swamp, hello Streams
Streams brings AI-assisted parsing, intelligent logs organization, and proactive event detection into a simple, intuitive workflow, so you can focus on solving problems, not wrangling pipelines.
CORE CAPABILITIES
Chaos → Clarity
SREs are drowning in alerts and brittle pipelines because the "why" behind most incidents is buried in chaotic, context-rich logs. Streams turns that chaos into clarity in minutes, giving you the answers you need to make logs your first stop for investigations.
Powered by agentic AI
In Elastic, agentic workflows organize logs, surface significant events, and guide investigations. Combined with organizational context grounded in your knowledgebases and runbooks, fast ES|QL queries, and machine learning, agentic AI turns raw logs into a ready-to-use source of truth.GUIDED DEMO
From raw logs to real answers
From ingest to investigation, Streams simplifies and automates the work of building custom pipelines and manually extracting fields, giving you clean, structured, high-fidelity data and helping you find the needle in the haystack.
Bring your data. We'll do the rest.
No pipelines to maintain — just send your logs.
No dropped data — retain full context with Elastic's high-performance data store.
No manual sifting — AI highlights the signals to watch, so you can focus on resolution.
Log management made easy
Forget grepping through petabytes of logs. Streams detects patterns humans can't see, parsing, partitioning, and structuring logs, and surfacing significant events with AI.
Elastic ElasticFrequently asked questions
Logs are the most ubiquitous, context-rich signal in your stack. Every system produces logs. Logs provide the raw, detailed information needed to understand exactly why an issue occurred and how to fix it. For that reason, they are the primary source of truth for troubleshooting and investigation.
As applications became more complex, the volume and variety of logs exploded. Logs became too expensive to store and too hard to extract value from. The industry responded by treating detailed log data as a burden, discarding crucial context, and throwing away the signal with the noise. Now teams are drowning in dashboards and alerts that don't give them the "why" — the answers they need — or else are spending their time maintaining fragile pipelines, instead of solving problems
Unlike traditional observability solutions that treat logs as secondary to metrics and traces, Streams makes logs a primary signal for both detection and investigation, helping you get to resolution faster. AI-driven workflows make logs usable and actionable, highlighting the "why" that's missing from traditional observability tools so SREs can resolve incidents faster, without having to spend weeks on data engineering and building complex pipelines.
Significant Events automatically detects critical anomalies and patterns in your logs, such as out-of-memory errors, server crashes, startup/shutdown events, and other operational changes, giving SREs an early warning and a clear starting point for investigation. Events are specific to the system (e.g., Apache Spark) and are automatically flagged based on context. You can filter, group, or explore them directly in the UI.
Streams uses AI to simplify parsing, enrichment, partitioning, and schema updates, removing the need to maintain complex Grok patterns or custom pipelines. SREs can begin investigating issues within minutes, rather than spending weeks on pipeline setup and data engineering.
By surfacing the most critical logs and automatically structuring data for efficient storage, Streams allows SREs to retain high-value data without discarding important information, reducing overall storage costs.
No. Streams works with your existing data sources and ingestion points. It can augment or replace pipelines over time without breaking your current workflows.
Yes. Streams eliminates the need for complex pipelines, high-cost ingestion, and manual log correlation. It provides immediate insights, AI-driven event detection, and cost-effective storage, making it a modern alternative to legacy solutions.
