What is OpenObserve?
OpenObserve (O2) was created to solve the cost and complexity of running Elasticsearch or the full Prometheus/Loki/Tempo/Grafana stack. A single deployment ingests logs via OpenTelemetry, Fluentd, or direct API; metrics via Prometheus remote write or OTLP; traces via Jaeger or OTLP; and real-user monitoring via a JavaScript snippet - all stored in object storage (S3, GCS, MinIO, or local disk).
Read the full overview
The Rust implementation keeps memory usage dramatically lower than JVM-based alternatives. Benchmarks show storage costs 140x below Elasticsearch at equivalent query performance. The embedded SQL query engine supports complex aggregations without separate query infrastructure.
Key capabilities
- Log ingestion and search - full-text and structured log search with saved views and alerts.
- Metrics - Prometheus-compatible metrics ingestion, storage, and dashboarding.
- Distributed tracing - Jaeger-compatible trace ingestion with service dependency maps.
- Real-user monitoring - frontend performance, errors, and session data from a single JS snippet.
- Dashboards and alerts - built-in dashboard editor and alert rules with webhook, email, and PagerDuty targets.
- LLM observability - native tracing for AI pipelines including prompt management and cost tracking.
- Infrastructure monitoring - servers, Kubernetes, cloud services with unified metrics and logs.
- Application performance - distributed traces linking requests across microservices.
- Log management - centralised, searchable log aggregation replacing Elasticsearch or Loki.
- LLM pipeline monitoring - trace token usage, latency, and cost across AI workloads.
OpenObserve targets teams paying for Datadog, New Relic, or a Grafana Cloud plan who want to reclaim cost control without fragmenting their observability into four separately managed tools. It is less mature than the Prometheus ecosystem for pure metrics use cases, but significantly simpler for teams that need logs and traces alongside metrics. Compare SQL-based querying versus PromQL/LogQL before committing.
The Grafana stack solves every observability use case but requires four separate systems, four separate retention policies, and four separate maintenance windows. Teams consistently underestimate the operational overhead. OpenObserve trades some ecosystem depth for radical simplicity: one binary, one storage backend, one query surface. For teams under 50 engineers or those moving fast, that simplicity compounds over time.
Technical details
- Access
- Self-hosted
- Source model
- Open source
- Founded
- 2023
- Headquarters
- San Francisco, CA, USA
- Pricing model
- Open source
- API
- Available
- Published release
- Stable — single binary, HA cluster, and embedded mode 0.14.5 ↗ (checked )
- Website
- openobserve.ai ↗
Official resources
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