Elastic Stack Observability

Elastic Stack Observability puts logs, metrics, application traces, and user-experience data into one Elasticsearch cluster, viewed and queried through Kibana. Elastic Observability combines these signals into a single, integrated platform for cross-referenced analysis, so a team that already runs Elasticsearch for search does not need a second data platform to answer "why is this service slow, erroring, or down."

The mental model:

system and application activity
        ↓
Elastic Agent, Beats, or an OpenTelemetry SDK
        ↓
ingestion (Fleet-managed integrations, Logstash, or the EDOT Collector)
        ↓
Elasticsearch index — logs, metrics, traces, normalized to common field names
        ↓
Kibana — search, dashboards, SLOs, alerts, AI-assisted investigation

Every signal lands in the same search engine, tagged with the same field names. That is what lets you pivot from a spike in a metric to the logs and traces recorded at the same moment, without switching tools or re-mapping field names by hand.

Why it exists