Get real-time visibility into your Kubernetes ecosystem

Bring logs, metrics, and traces from your Kubernetes cluster — and the workloads running on it — into a single, unified solution. Dynamic service discovery, central agent management, and enriched telemetry data from your clusters allow you to quickly identify issues with your applications, services, and environment.

Use a centrally managed Elastic Agent to gain visibility into your Kubernetes deployments on EKS, AKS, GKE or self-managed clusters.
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Manage and monitor your Kubernetes environment with Elastic Observability.
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Use observability and security for an OpenTelemetry application on your Kubernetes cluster.
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Automatic discovery of dynamic workloads with out-of-the-box dashboards

Dynamic workloads need dynamic monitoring, and when you run applications in containers they become ephemeral. Elastic auto discovers these changes and lets you keep an eye on your Kubernetes services and components, wherever they are running, while metadata enrichment on ingest allows you to filter, track, and identify common attributes of the system. View these changes and related metrics, logs, and analysis in comprehensive out-of-the-box dashboards.

Leverage open standards

Elastic integrations natively support open standards like OpenTelemetry, Prometheus, and Istio for metrics and much more. Use PromQL to collect, transform, and visualize your existing Prometheus metrics.

In addition to Elastic Agent, native tools to ingest logs, metrics, and traces, with support for open standards, including OpenTelemetry for metrics and traces, Prometheus metrics, and Istio metrics are supported through integrations, including support for PromQL queries for metrics collection.


End-to-end visibility from the application, Kubernetes, to the cloud

Elastic APM not only provides visibility into your application services, but also correlates them to the related Kubernetes and cloud components. Elastic machine learning provides additional insights into interrelated issues between the layers.

In-depth analytics of your entire ecosystem

Get deep insights into your Kubernetes cluster and the services running on it, including the Kubernetes nodes, control plane components, and your workloads. Quickly navigate to related logs, metrics, or traces, in context, for faster and more efficient troubleshooting.


Operate your Kubernetes architectures with confidence

A correlated and contextualized experience for ad hoc analysis reduces complexity related to distributed microservice architectures and surfaces problems easier. Use Elastic’s machine learning capabilities to improve management of your Kubernetes clusters.

  • Actionable insights

    Threshold-based alerting enables you to easily track the performance and availability relative to your Kubernetes SLOs/SLAs. Use error budgets to determine when to deploy new features and updates in your ecosystem.

  • Discover unknown unknowns

    Detect outliers in response times or error rates with machine learning-based anomaly detection. Identify problematic services or geographies to uncover the unknown unknowns in your Kubernetes logs with log categorization.

  • Automated correlation

    Analyze problematic transactions and automatically identify contributing factors to find the root cause of problems, whether they are related to an application, the environment, or a specific pod.