Elastic Observability unifies logs, metrics, traces and uptime on the Elastic Stack with AI-assisted root cause analysis.
Elastic Observability builds on the ELK heritage — Elasticsearch, Kibana and the Beats and Agent ecosystem — to give teams full visibility across applications and infrastructure. Logs, metrics, APM traces and synthetic monitoring live in one platform where AIOps features correlate alerts, detect anomalies and surface root causes. Deployments run as a managed cloud or self-hosted, and OpenTelemetry support keeps instrumentation portable. It is one of the most deployed observability stacks in the world.
Elastic Observability is available through Elastic Cloud subscriptions with usage-based tiers, or self-hosted under the project’s licensing; free trials are available.
Engineering and SRE teams that want one platform for all observability data with strong search analytics under the hood.
SRE teams investigate incidents by pivoting from alerts to traces to logs in one platform, and security teams reuse the same data for threat hunting. DevOps groups standardize on OpenTelemetry ingestion across services.
Start an Elastic Cloud trial or deploy the stack yourself, ingest logs with an agent and build your first service dashboard.
Self-hosted options exist at low cost and trials are available; managed cloud is subscription-based.
Yes — Elasticsearch and Kibana APIs cover ingestion, search and configuration comprehensively.
Versus Datadog, Elastic offers superior log search and flexible deployment; versus Splunk it is generally more cost-effective at scale.
Machine learning detects anomalies, correlates related alerts into incidents and suggests probable root causes during outages.
Yes, self-managed deployment remains an option for teams with data residency or cost-control requirements.
Elasticsearch for storage and search, Kibana for visualization and the Beats and Agent ecosystem for ingestion — battle-tested components used at massive scale.
Native OTLP ingestion keeps instrumentation portable, so adopting Elastic does not require rewriting your telemetry collection strategy.
Managed cloud pricing scales with resources and retention you configure; self-managed options exist for teams that prefer infrastructure control over subscription simplicity.
Elasticsearch’s search heritage makes massive log volumes a strength — hot-warm architectures and lifecycle policies keep costs manageable as data grows.