OpenObserve (O2) is a cloud-native observability platform for logs, metrics, and traces at petabyte scale.
What You Get for Free
- Logs — ingest, search, and analyze at scale (200TB+/day in production)
- Metrics — Prometheus-compatible ingestion and querying
- Traces — OpenTelemetry-compatible distributed tracing
- Dashboards — built-in visualization, no Grafana needed
- Alerts — threshold and anomaly-based alerting
- SQL queries — familiar SQL for log analysis
- S3 storage — store logs on S3/MinIO at 140x lower cost
- Embedded UI — single binary includes the dashboard
- Cloud free tier — 200GB ingestion/month
Quick Start
# Single binary — download and run
curl -L https://raw.githubusercontent.com/openobserve/openobserve/main/download.sh | sh
./openobserve
# Or Docker
docker run -d -p 5080:5080 -e ZO_ROOT_USER_EMAIL=admin@example.com \
-e ZO_ROOT_USER_PASSWORD=ComplexPass#123 openobserve/openobserve:latest
# Send logs (Elasticsearch-compatible API)
curl -u admin@example.com:ComplexPass#123 \
-d '[{"level":"info","message":"hello"}]' \
http://localhost:5080/api/default/logs/_json
Why Teams Are Switching from Elasticsearch
Elasticsearch needs massive RAM and expensive SSDs:
- 140x lower storage — columnar storage + S3 backend
- Single binary — vs Elasticsearch's Java cluster
- No JVM tuning — written in Rust, predictable performance
- Built-in dashboards — no separate Kibana needed
A startup was spending $1,200/mo on Elastic Cloud for 50GB/day of logs. They switched to OpenObserve with S3 storage — same search speed, same dashboards, cost dropped to $45/mo.
Need Custom Data Solutions?
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