OpenObserve

open_source

OpenObserve is a fast, scalable, and cost-effective open source observability platform. Monitor logs, metrics, and traces with 140x lower storage costs than Elasticsearch. Get started in 2 minutes.

Data & Analytics

DevOps Tools

AI Infrastructure Tools

About

OpenObserve is a modern, unified observability platform built for the AI era, offering full visibility into logs, metrics, traces, and frontend monitoring. Written in Rust and powered by the Apache DataFusion query engine, it delivers blazing-fast query performance — capable of querying 1 petabyte of data in just 2 seconds. Its columnar storage with Apache Parquet and ~40x compression ratio results in storage costs that are 140x lower than Elasticsearch, making enterprise-grade observability dramatically more affordable. OpenObserve is fully open source under the AGPL-3.0 license and embraces open standards such as OpenTelemetry, ensuring seamless integration with existing toolchains without vendor lock-in. Its stateless node architecture enables horizontal scaling without data complexity, making it suitable for everything from early-stage startups to Fortune 100 enterprises. Key capabilities include log management, metrics monitoring, distributed tracing, frontend monitoring, alerting, data pipelines, and rich visualization dashboards. The platform supports flexible storage backends including local disk, S3, MinIO, Google Cloud Storage, and Azure Blob Storage — enabling a true Bring Your Own Bucket model. OpenObserve is ideal for DevOps engineers, SREs, and platform teams looking to replace costly tools like Datadog or Elasticsearch with a scalable, cost-effective, and community-driven alternative.

Key Features

140x Lower Storage Costs: Achieves dramatically reduced storage costs compared to Elasticsearch through ~40x compression and columnar Apache Parquet storage format.
Unified Observability: Single platform for logs, metrics, traces, frontend monitoring, alerting, pipelines, and dashboards — eliminating the need for multiple tools.
Petabyte-Scale Performance: Built in Rust with the DataFusion query engine, enabling queries across 1 petabyte of data in approximately 2 seconds.
Flexible Storage Backends: Supports local disk, Amazon S3, MinIO, Google Cloud Storage, and Azure Blob Storage via a Bring Your Own Bucket model.
OpenTelemetry Compatible: Fully compatible with OpenTelemetry standards and vendor-neutral APIs, ensuring smooth integration with existing observability toolchains.

Use Cases

Replacing costly SaaS observability tools like Datadog or New Relic with a self-hosted, open source alternative to reduce infrastructure spend.
Centralizing logs, metrics, and traces from microservices and Kubernetes clusters into a single unified observability platform.
Monitoring cloud infrastructure across AWS, Azure, and GCP with native storage backend support and OpenTelemetry compatibility.
Providing DevOps and SRE teams with real-time alerting and dashboards for rapid incident detection and response.
Storing and querying large volumes of historical observability data at petabyte scale without prohibitive storage costs.

Pros

Massive Cost Savings: 140x lower storage costs make it a compelling alternative to expensive SaaS observability tools like Datadog or Elasticsearch.
Fast Setup: Teams can run an initial proof of concept in as little as 2-3 minutes, lowering the barrier to adoption.
Truly Open Source: AGPL-3.0 license with active community, full code transparency, and no hidden vendor lock-in.
Horizontal Scalability: Stateless architecture allows seamless horizontal scaling from small teams to Fortune 100 enterprise workloads.

Cons

AGPL License Restrictions: The AGPL-3.0 license may require organizations to open-source modifications, which can be a concern for proprietary enterprise deployments.
Self-Hosted Complexity: While quick to start, managing a self-hosted observability stack at scale requires infrastructure expertise and ongoing maintenance.
Smaller Ecosystem than Established Tools: As a newer platform, its plugin and integration ecosystem is less mature than long-established tools like Grafana or Elastic.

Frequently Asked Questions

OpenObserve uses columnar storage with Apache Parquet and achieves approximately 40x compression, dramatically reducing the amount of disk space needed compared to row-based storage systems like Elasticsearch.

Yes, OpenObserve is fully open source under the AGPL-3.0 license. The complete source code is publicly available, allowing community contributions, security audits, and full control over your observability data.

OpenObserve supports local disk, Amazon S3, MinIO, Google Cloud Storage (GCS), and Azure Blob Storage, giving teams full flexibility in where they store their observability data.

Yes, OpenObserve is fully compatible with OpenTelemetry and offers standard API interfaces, making it easy to integrate with existing logging agents, metrics exporters, and tracing libraries.

Absolutely. OpenObserve's stateless node architecture supports horizontal scaling and has been deployed for Fortune 100 enterprises handling production-level petabyte-scale workloads.