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OpenObserve: Unified Observability for Logs, Metrics, Traces & More
OpenObserve is a high-performance, low-cost, and scalable alternative to Elasticsearch, Splunk, and Datadog, designed for storing and analyzing logs, metrics, traces, RUM, error tracking, and session replay data.
Rust
Added on 2025年6月11日15,486
Stars588
ForksRust
LanguageProject Introduction
Summary
OpenObserve is an open-source, unified observability platform offering a high-performance, cost-effective, and scalable solution for collecting, storing, and analyzing all types of telemetry data, including logs, metrics, traces, RUM, error tracking, and session replay.
Problem Solved
Existing observability solutions are often prohibitively expensive, complex to manage, and struggle with petabyte-scale data while maintaining performance. OpenObserve addresses these challenges by providing a cost-effective, high-performance, and scalable alternative.
Core Features
Unified Observability
Unified platform for logs, metrics, traces, RUM, and session replay.
Low Storage Cost
Achieves significantly lower storage costs compared to traditional solutions.
Petabyte Scale
Built for handling petabyte-scale data volumes.
High Performance
Provides fast ingestion and query performance for real-time analysis.
Tech Stack
Rust
Go
ClickHouse
Apache Kafka
S3 Compatible Storage
使用场景
OpenObserve can be used in various scenarios where collecting, storing, and analyzing large volumes of telemetry data is critical.
Scenario 1: Cloud-Native Application Monitoring
Details
Collect logs, metrics, and traces from microservices running in Kubernetes or other container orchestration platforms for centralized monitoring and debugging.
User Value
Provides a single pane of glass for complex distributed systems, improving visibility and reducing MTTR (Mean Time To Recovery).
Scenario 2: Real User Monitoring and Session Replay
Details
Store and analyze website usage data, frontend errors, and session recordings to understand user behavior and identify frontend performance bottlenecks.
User Value
Enhance user experience by proactively identifying and fixing frontend issues and understanding user journeys.
Scenario 3: Cost-Effective Data Archival and Analysis
Details
Replace expensive legacy logging or metrics systems with a cost-effective and scalable solution capable of handling petabytes of historical data for compliance and analysis.
User Value
Significantly reduce infrastructure costs while retaining long-term data for auditing, compliance, and historical trend analysis.
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