Whether you're new to Elastic Observability or you're already housing logs and system metrics in Elasticsearch you can seamlessly adopt APM to quickly identify and resolve root cause issues with correlated traces, logs, and metrics. Get deeper visibility into your applications with extensive support for popular languages, OpenTelemetry, and distributed tracing. Use machine learning to quickly correlate infrastructure and application metadata to determine outliers and identify abnormal behavior.

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Capture and analyze distributed transactions spanning microservices and monolithic architectures. Investigate each tier from client to the application services with enriched transaction metadata including deployment markers, for faster analysis to minimize downtime and optimize customer experience. Derive valuable information by tagging each transaction with customer metrics/metadata for easier analysis. Scalable and flexible architecture welcomes full fidelity, 100% transaction sample capture, storage, analytics, and search with the added dials to scale sampling up or down as needed.




Identify performance issues with automated and curated visual representation of all dependencies, including cloud, messaging, data store, and third-party services and their performance data. Drill into anomalies, transaction details, and metrics for deeper analysis.




Support for open standards including OpenTelemetry, W3C trace context, and Jaeger — allowing you to directly ingest application telemetry data collected by OpenTelemetry agents. OpenTelemetry and open standard data sources future-proof your observability investments by providing maximum flexibility and reducing the cost of future integration efforts.