openobserve/openobserve

Open source observability platform for logs, metrics, traces, RUM, Session replay, pipelines, SLO and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.

What it solves

OpenObserve provides a cost-effective, high-performance alternative to expensive observability platforms like Datadog, Splunk, and Elasticsearch. It eliminates the complexity of managing large clusters and the high cost of storage associated with traditional log and metric management, specifically targeting teams that need to scale to petabytes of data without prohibitive expenses.

How it works

Built in Rust as a single binary, the platform uses an S3-native design and Parquet columnar storage to drastically reduce storage costs (up to 140x) and improve query performance. It is OpenTelemetry native, allowing users to ingest logs, metrics, and traces using standard protocols. Users can query their data using familiar languages like SQL and PromQL rather than proprietary query languages.

Who it’s for

It is designed for DevOps and platform engineers who need a unified observability stack for logs, metrics, traces, and frontend monitoring (RUM) that is easy to deploy and scales from terabytes to petabytes.

Highlights

  • Unified Observability: Combines logs, metrics, traces, RUM, and AI/LLM observability in one tool.
  • Extreme Storage Efficiency: Uses Parquet and S3 to cut costs significantly compared to Elasticsearch.
  • AI-Powered Insights: Includes an AI assistant to write queries and a dedicated module for monitoring GenAI/LLM application costs, tokens, and latency.
  • Low Operational Overhead: Deploys as a single binary with no complex sharding or cluster tuning required.
  • Frontend Monitoring: Includes session replay and Core Web Vitals tracking.

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