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OpenObserve Review

OpenObserve is an open-source observability platform for logs, metrics, and traces, designed to provide full-stack monitoring with significantly reduced storage costs.

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Why it matters

1Offers up to 140x lower storage costs compared to Elasticsearch due to Apache Parquet columnar storage.
2Provides unified observability for logs, metrics, traces, Real User Monitoring (RUM), and session replay.
3Built in Rust for high performance and efficiency, supporting petabyte-scale operations.
4Secured $10 million in Series A funding on April 28, 2026, and launched 'Observability 3.0' with AI-native features.

Stork’s verdict on OpenObserve

OpenObserve delivers petabyte-scale observability at low cost, though its UI/UX and self-hosting documentation are still maturing.

About OpenObserve

Headquarters
paris
Founded
2022

Specs

API Available

Yes, public API

overview

What is OpenObserve?

OpenObserve is an open-source observability platform developed by OpenObserve that enables SRE teams, DevOps engineers, startups, and enterprises to monitor logs, metrics, and traces with high efficiency. It unifies telemetry data, including real user monitoring (RUM) and session replay, into a single system, aiming to reduce operational costs and complexity significantly.

features

Key Features of OpenObserve

OpenObserve provides a comprehensive suite of features designed for modern cloud-native environments, focusing on performance, cost-efficiency, and unified data management. Its architecture supports petabyte-scale operations and offers advanced capabilities for AI observability.

  • Logs monitoring with SQL and PromQL support for querying.
  • Metrics monitoring utilizing high-compression Apache Parquet columnar storage.
  • Traces monitoring with native OpenTelemetry support for distributed systems.
  • Customizable Dashboards and alerts for real-time insights and incident notification.
  • Real User Monitoring (RUM) and Session Replay for comprehensive frontend visibility.
  • AI SRE Agent for automated root cause analysis and natural language querying.
  • Stateless node architecture ensuring scalability and resilience across deployments.
  • API available for programmatic access and integration with existing tools.
  • Support for various object storage backends including S3, MinIO, GCS, and Azure Blob Storage.

use cases

Who Should Use OpenObserve?

OpenObserve is primarily designed for engineering teams seeking a unified, cost-effective, and high-performance observability solution. It addresses the needs of organizations operating in cloud-native and Kubernetes environments, as well as those developing AI-driven applications.

  • Startups and Enterprises: Seeking to drastically reduce infrastructure costs for observability while maintaining enterprise reliability and petabyte-scale operations.
  • SRE Teams and DevOps Engineers: Requiring full-stack observability for logs, metrics, traces, RUM, and session replay to troubleshoot problems and monitor system behavior.
  • Cloud-Native and Kubernetes Environments: Deploying and managing observability for containerized workloads with easy deployment options like Helm charts.
  • AI Observability: Monitoring agentic decisions, logging incorrect results, and capturing training and inference metrics for Gen AI and agentic AI workloads.

how to use

How to Use OpenObserve

OpenObserve can be deployed rapidly in various environments, offering flexibility for both self-hosting and cloud-based operations. Its design prioritizes ease of setup and integration with existing infrastructure.

  • 1Download and run the single binary for quick local deployment on Linux, macOS, or Windows.
  • 2Deploy using a Helm chart for streamlined integration into Kubernetes environments.
  • 3Utilize the Terraform Provider and Kubernetes Module for Infrastructure as Code (IaC) management of resources.
  • 4Configure data ingestion via OpenTelemetry, syslog, or other supported methods to collect telemetry.
  • 5Connect to preferred object storage (S3, MinIO, GCS, Azure Blob Storage) using Bring Your Own Bucket (BYOB) for data residency and compliance.
  • 6Access the API for programmatic interaction and custom integrations with other monitoring or automation tools.

pricing

OpenObserve Pricing & Plans

OpenObserve offers a flexible pricing model that includes a free tier for self-hosted deployments and a usage-based model for its cloud service. The self-hosted Enterprise version provides additional features for larger organizations.

  • Free: Available for self-hosted deployments, providing core observability features under the AGPL-3.0 License.
  • Self Hosted Enterprise: Free up to 50 GB/day of ingestion, including features like SSO, RBAC, and Audit trail for enhanced security and management.
  • OpenObserve Cloud: Transitioned to a fully usage-based pricing model effective June 2, 2025, eliminating minimum fees and discontinuing the free cloud tier.

Pros

  • +Offers up to 140x lower storage costs compared to Elasticsearch due to Apache Parquet and object storage.
  • +Provides a unified platform for logs, metrics, traces, RUM, and session replay, reducing tool sprawl.
  • +Built in Rust for high performance, efficiency, and low resource consumption, supporting petabyte scale.
  • +Supports OpenTelemetry natively, ensuring vendor-neutral instrumentation and data collection.
  • +Offers flexible deployment options including a single binary, Helm charts, and Infrastructure as Code (Terraform).
  • +Includes an AI SRE Agent for automated root cause analysis and natural language querying capabilities.

Cons

  • The UI/UX requires further refinement, with user feedback suggesting improvements for mobile interfaces and trace navigation.
  • Documentation for specific self-hosting configurations, such as syslog ingestion or persistent storage, can be sparse.
  • Advanced security features like Role-Based Access Control (RBAC) and Single Sign-On (SSO) are restricted to paid plans.
  • The free cloud tier was discontinued effective June 2, 2025, transitioning to a fully usage-based model.
  • Requires self-management for the open-source version, which may entail operational overhead for smaller teams without dedicated resources.

Similar Tools

OpenObserve vs Competitors

OpenObserve positions itself as a modern, cost-effective, and high-performance alternative to established observability solutions, particularly for organizations focused on reducing operational expenditures and simplifying their monitoring stack.

1
SigNoz

SigNoz is an open-source, full-stack observability platform that provides logs, metrics, and traces, with an integrated AI Teammate (Noz) for natural language querying and incident investigation.

Similar to OpenObserve, SigNoz offers a self-hosted, open-source solution for comprehensive observability. Its AI features, like Noz, provide an advanced layer of analysis and interaction that OpenObserve's description doesn't explicitly detail, while also focusing on cost-effectiveness through self-hosting.

2
Grafana Labs (Grafana Cloud with AI)

Grafana AI, part of Grafana Cloud, leverages machine learning and large language models for anomaly detection, forecasting, AI-powered investigations (Sift), and an AI Assistant to streamline observability workflows.

While Grafana's core components are open-source, its AI capabilities are primarily offered through Grafana Cloud, which has a free tier. It directly competes by offering AI-driven insights across logs, metrics, and traces, similar to OpenObserve's core functionality but with explicit AI enhancements.

3

Logz.io provides an AI-powered observability platform with AI Agents that automate root cause analysis, alert analysis, and data analysis, focusing on accelerating troubleshooting and optimizing costs.

Logz.io offers a managed service that is compatible with open-source tools like OpenSearch and Grafana, and its AI Agents directly address the need for faster, more cost-effective issue resolution, aligning with OpenObserve's value proposition of lower storage costs and quick setup.

4

New Relic offers a comprehensive, intelligent observability platform with AIOps capabilities that provide full-stack visibility, including AI observability for LLM applications and agentic workflows.

New Relic provides a perpetual free tier with 100 GB of data ingest per month and one full platform user, making it a strong competitor on cost for smaller teams, while offering a broader suite of AI-enhanced observability features than OpenObserve's description.

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