Elastic Observability, built on open source

Observability should be open. Elastic is standardized on OpenTelemetry. With Elastic Distributions of OpenTelemetry (EDOT), you get a production-ready, OTel-native ecosystem with no proprietary extensions, allowing monitoring of everything from Kubernetes to apps.

SREs can investigate and draw insights (and even build custom charts) from logs, metrics, traces, and other data through Elastic’s Discover, prebuilt dashboards, and ES|QL-based ad hoc analysis.

Elastic's AI Assistant, powered by an LLM, delivers root cause insights and context through natural language. Combined with zero-config AIOps that automatically surfaces issues, SREs can resolve problems faster without swivel chair analysis.

Refined over a decade, SREs can choose zero-config out-of-the-box capabilities or customize their own analysis using built-in or imported ML models to detect anomalies, forecast trends, and uncover patterns across logs, metrics, and traces.

Elastic's Search AI Lake supports petabytes of structured and unstructured data, enabling fast, scalable, and relevant analytics through search across large and long-term datasets.

Retain more data cost efficiently with tiered storage — without sacrificing performance. Snapshots stay searchable, so historical data never goes dark. Further reduce data footprint by up to 70% using Elasticsearch logsdb index mode and TSDB.