Elastic Observability

Elastic Observability is the observability product built on Elasticsearch, collecting and analysing logs, metrics and traces alongside Elastic's search and security offerings, deployed as Elastic Cloud Serverless, Elastic Cloud Hosted or self-managed.

Sharing one data store across observability, search and security is the structural argument and it produces a real operational advantage. Investigating an incident routinely means correlating an application error with a security event and a business record, and when those live in three products the correlation is done by a person with three browser tabs. One engine holding all of it makes that a query.

The self-managed option is what distinguishes Elastic commercially from the cloud-only observability vendors, and it matters for two reasons: telemetry volumes make hosted pricing unpredictable at scale, and some organisations cannot send operational data to a third party at all. Being able to run the same product locally, on Kubernetes or under an organisation's own orchestration removes both objections.

Elastic has moved firmly into the AI retrieval space alongside observability, with a vector database, context engineering for grounding agents, an Agent Builder, Jina AI models for embeddings and reranking, and workflows combining scripted automation with reasoning inside Elasticsearch. AutoOps provides cluster management with performance recommendations and cost insights, which addresses the long-standing criticism that operating Elasticsearch well requires real expertise. Kibana handles exploration and dashboards. Rates are published separately on the Elastic pricing pages rather than on the product page.