140x more storage efficient vs Elastic

Open-Source High-Performance Unified Observability

For the AI Era

Talk to a Human

Why OpenObserve

Four reasons teams switch

Built for scale, priced for reality

Columnar Parquet storage delivers roughly 40x compression and up to 140x lower storage costs than Elasticsearch. Written in Rust on the DataFusion query engine, OpenObserve queries a petabyte of data in about 2 seconds.

140xlower storage cost vs. Elasticsearch
100xmore performant, up to
2.5 PB/daylargest customer ingestion

One platform, every signal

Logs, metrics, traces, real user monitoring, and session replay live in a single tool with one query language. No stitching together five separate systems, no per-tool learning curve.

4signal types in a single tool
1binary, one query layer
0proprietary query languages

Explore the Platform

Nothing hidden, nothing locked in

The full codebase is open source under AGPL-3.0: audit it, extend it, self-host it. Built on open standards like OpenTelemetry so your data is never trapped in a proprietary format.

AGPL-3.0fully open source license
20.6k+GitHub stars
100%commits public

Your infrastructure, your rules

Run OpenObserve as a single binary, a Helm chart in Kubernetes, or fully managed on OpenObserve Cloud. Bring your own storage: local disk, S3, GCS, MinIO, or Azure Blob.

3ways to deploy: binary, Helm, or Cloud
5storage backends supported
0vendor lock-in

See Deployment Options

Built for scale, priced for reality

Columnar Parquet storage delivers roughly 40x compression and up to 140x lower storage costs than Elasticsearch. Written in Rust on the DataFusion query engine, OpenObserve queries a petabyte of data in about 2 seconds.

140xlower storage cost vs. Elasticsearch
100xmore performant, up to
2.5 PB/daylargest customer ingestion

How It Works

Complete systemic context, auto-correlated

Observability Layers

Frontend

AI & LLM

API

Application

Database

Network

Infrastructure

Complete systemic context

Auto-correlate

Solutions

Cloud Observability

Cloud Observability

Kubernetes Observability

Kubernetes Observability

LLM Observability

LLM Observability

SRE agent

SRE agent

AI assistant

AI assistant

Frontend

Frontend

Metrics

Metrics

Logs

Logs

Traces

Traces

Collect your data

Pipelines

Pipelines

Control your data

Visualizations

Visualizations

Incident

Incident

Alerts

Alerts

Act on your data

Deployment

Outcomes

Lower Operational Overhead

Decreased MTTx

Improved Productivity

De-risk Operational Continuity

Product Tour

Every signal, one platform

Real user monitoring

See exactly how real users experience your app: session traces, Core Web Vitals, and errors, correlated with backend traces.

AI and LLM monitoring in OpenObserve

0×

more cost-effective vs.Datadog

8x cost reduction means you can unify your observability into a single platform.

Datadog

OpenObserve

See how much you'd save switching today.

Calculate Your Savings

One platform, every workload

Correlate between the environments and signals across various sources with OpenObserve built-in correlation engine.

Full-stack visibility across every cluster

Collect logs, metrics, and traces from pods, nodes, and control planes without managing a separate stack per cluster.

Auto-discovery via OpenTelemetry Collector
Pre-built Kubernetes dashboards
Correlate pod logs with traces instantly
Scales with ephemeral, high-cardinality workloads

Explore Kubernetes Observability

Plug into your stack

All Integrations

Real User Monitoring (RUM)

OpenTelemetry

Curl

ElasticSearch

Prometheus

Vector

Fluent Bit

Fluentd

Filebeat

Telegraf

Kinesis Firehose

Syslog

OpenAI (Python)

Anthropic (Python)

Google Gemini

Amazon Bedrock

Mistral

Ollama

DeepSeek

OpenAI (JS/TS)

OpenAI Assistants

Anthropic (JS/TS)

Cohere

Groq

Hugging Face

vLLM

Together AI

Fireworks AI

xAI Grok

Cerebras

Novita

CometAPI

BytePlus

LangChain

LlamaIndex

CrewAI

AutoGen

Semantic Kernel

Haystack

Pydantic AI

Vercel AI SDK

Spring AI

DSPy

Smolagents

Instructor

OpenAI Agents

LangGraph

Mastra

Temporal

Agno

Voltagent

Strands Agents

Google ADK

Amazon Bedrock AgentCore

Amazon Bedrock Agents

BeeAI

Claude Agent SDK

DeepAgents

LangServe

LiteLLM

LiveKit

LlamaIndex Workflows

Microsoft Agent Framework

Mirascope

Pipecat

Quarkus LangChain4j

Ragas

Restate

Swiftide

Koog

LiteLLM Proxy

Portkey

OpenRouter

Kong Gateway

Vercel AI Gateway

Anannas

n8n

Flowise

Langflow

Vapi

LobeChat

Codename Goose

Open WebUI

Promptfoo

Real User Monitoring (RUM)

OpenTelemetry

Curl

ElasticSearch

Prometheus

Vector

Fluent Bit

Fluentd

Filebeat

Telegraf

Kinesis Firehose

Syslog

OpenAI (Python)

Anthropic (Python)

Google Gemini

Amazon Bedrock

Mistral

Ollama

DeepSeek

OpenAI (JS/TS)

OpenAI Assistants

Anthropic (JS/TS)

Cohere

Groq

Hugging Face

vLLM

Together AI

Fireworks AI

xAI Grok

Cerebras

Novita

CometAPI

BytePlus

LangChain

LlamaIndex

CrewAI

AutoGen

Semantic Kernel

Haystack

Pydantic AI

Vercel AI SDK

Spring AI

DSPy

Smolagents

Instructor

OpenAI Agents

LangGraph

Mastra

Temporal

Agno

Voltagent

Strands Agents

Google ADK

Amazon Bedrock AgentCore

Amazon Bedrock Agents

BeeAI

Claude Agent SDK

DeepAgents

LangServe

LiteLLM

LiveKit

LlamaIndex Workflows

Microsoft Agent Framework

Mirascope

Pipecat

Quarkus LangChain4j

Ragas

Restate

Swiftide

Koog

LiteLLM Proxy

Portkey

OpenRouter

Kong Gateway

Vercel AI Gateway

Anannas

n8n

Flowise

Langflow

Vapi

LobeChat

Codename Goose

Open WebUI

Promptfoo

Milvus

PostHog

Zapier

Claude Code

Cognee

Exa

Firecrawl

Gradio

LibreChat

MCP Use

Mixpanel

Parallel

Trubrics

Cursor

Opencode

OpenAI Codex

MCP Server

MCP Claude

LLM Applications

AWS

Amazon EC2

Application Load Balancer

Amazon VPC Flow Logs

Amazon Cognito

AWS Network Firewall

AWS CloudWatch Logs

AWS CloudWatch Metrics

Amazon RDS

AWS Lambda

Amazon ECS

AWS Route 53

AWS WAF

AWS API Gateway

Amazon CloudFront

Amazon EventBridge

GCP Logs

Google Cloud Run

Microsoft Azure

Azure Activity Logs

Cloudflare

Vercel

Heroku

Kubernetes

Linux

Windows

NGINX

IIS

Oracle WebLogic

PostgreSQL

MySQL

Oracle Database

SQL Server

MongoDB

Amazon DynamoDB

Cassandra

Aerospike

Redis

Snowflake

Apache ZooKeeper

Databricks

GitHub Actions

Jenkins

Ansible

Terraform

Apache Kafka

RabbitMQ

NATS

Apache Airflow

Cribl

MuleSoft

Microsoft 365

Okta

Jumpcloud

OpenVPN

Google Workspace

Falco

OSQuery

Netflow

SNPM

Python

.NET Tracing

Node.js

.NET Logs

Milvus

PostHog

Zapier

Claude Code

Cognee

Exa

Firecrawl

Gradio

LibreChat

MCP Use

Mixpanel

Parallel

Trubrics

Cursor

Opencode

OpenAI Codex

MCP Server

MCP Claude

LLM Applications

AWS

Amazon EC2

Application Load Balancer

Amazon VPC Flow Logs

Amazon Cognito

AWS Network Firewall

AWS CloudWatch Logs

AWS CloudWatch Metrics

Amazon RDS

AWS Lambda

Amazon ECS

AWS Route 53

AWS WAF

AWS API Gateway

Amazon CloudFront

Amazon EventBridge

GCP Logs

Google Cloud Run

Microsoft Azure

Azure Activity Logs

Cloudflare

Vercel

Heroku

Kubernetes

Linux

Windows

NGINX

IIS

Oracle WebLogic

PostgreSQL

MySQL

Oracle Database

SQL Server

MongoDB

Amazon DynamoDB

Cassandra

Aerospike

Redis

Snowflake

Apache ZooKeeper

Databricks

GitHub Actions

Jenkins

Ansible

Terraform

Apache Kafka

RabbitMQ

NATS

Apache Airflow

Cribl

MuleSoft

Microsoft 365

Okta

Jumpcloud

OpenVPN

Google Workspace

Falco

OSQuery

Netflow

SNPM

Python

.NET Tracing

Node.js

.NET Logs

Testimonials

What teams say running OpenObserve

Correlate between the environments and signals across various sources with OpenObserve built-in correlation engine.

Ajith Natarajan

“[OpenObserve is] super fast, definitely very lightweight, and you can get started with an initial POC in two to three minutes to be honest.”

2–3 min

To first POC

Lightweight

Minimal footprint

AI vision

Retail analytics platform