refactor: update file statistics cache configuration and metrics (#11950)
ENVs
Replace
ZO_DATAFUSION_FILE_STAT_CACHE_MAX_ENTRIEStoZO_DATAFUSION_FILE_STAT_CACHE_MAX_SIZEfixed https://github.com/openobserve/openobserve/issues/11835
- Changed
datafusion_file_stat_cache_max_entriestodatafusion_file_stat_cache_max_sizein configuration, allowing for memory size limits instead of entry counts.- Implemented logic to set default cache size to 5% of total memory if not specified.
- Added new metrics for cache hits, misses, eviction counts, and eviction time to monitor cache performance.
- Updated cache eviction logic to track current memory usage and log warnings when limits are exceeded.
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Open source Datadog alternative for logs, metrics, traces, and frontend monitoring. Modern observability platform: 10x easier, 140x lower storage cost, high performance, petabyte scale.
OpenObserve (O2) is a cloud-native observability tool built for logs, metrics, traces, analytics, and Real User Monitoring (RUM). It’s designed as a cost-effective alternative to Datadog, Splunk, and Elasticsearch for teams that need full observability without the complexity or cost.
Why OpenObserve?
OpenObserve is a single observability tool for all your monitoring needs. Here’s why teams choose OpenObserve:
Cost Comparison: OpenObserve Vs Elasticsearch
🎥 Introduction Video
🏗️ Architecture
OpenObserve achieves 140x lower storage costs and high performance through its modern architecture:
This architecture delivers 140x cost savings while providing better performance than Elasticsearch.
Scale & Deployment
High Availability & Disaster Recovery
Deploy in High Availability mode with clustering for mission-critical workloads requiring maximum uptime and performance.
Low RPO/RTO: OpenObserve’s stateless architecture with S3-backed storage enables very low Recovery Point Objective (RPO) and Recovery Time Objective (RTO). Stateless nodes can be rapidly restarted, and data durability is guaranteed by S3’s 99.999999999% (11 nines) durability. That’s a lot of nines.
Read detailed architecture documentation →
Read enterprise deployment guide →
Features
For a full list of features, check the documentation.
Logs Management
OpenObserve provides a centralized log management solution with full-text search, SQL queries, and powerful filtering. Built on Parquet columnar storage for 140x lower storage costs than Elasticsearch. Instantly search through all your logs using quick filters and a powerful query builder. Create dashboards from log data and set up alerts. Read more →
Distributed Tracing
Distributed tracing is essential to troubleshoot issues in microservices applications. Powered by OpenTelemetry, tracing in OpenObserve helps you track user requests across services to identify performance bottlenecks. See user requests in a detailed breakdown with Flamegraphs and Gantt Charts. Click on any span to see the entire trace and understand where issues occurred. Read more →
Metrics & Dashboards
Ingest metrics from your infrastructure or applications and create customized dashboards. 19+ built-in chart types plus custom charts for 200+ visualization variations. Query metrics with SQL or PromQL. Add multiple queries and combine them with formulae. Read more →
Frontend Monitoring (RUM)
Real User Monitoring with performance tracking, error logging, and session replay. Understand exactly what your users experience. Read more →
Alerts
Get notified when anything unusual happens in your application. Set alerts on any telemetry signal (logs, metrics, traces), create thresholds, and configure notification channels. Advanced features like alert history and anomaly detection help you identify issues before they reach your customers. Read more →
Pipelines
Enrich, redact, reduce, or normalize data on ingest. Stream processing for logs-to-metrics conversion and more. No external tools required. Read more →
Getting Started
OpenObserve Cloud (Fastest Way)
Get started in minutes without managing infrastructure. Free tier includes up to 200 GB/day ingestion. Get Started Free →
🐳 Docker:
For other ways to quickly install OpenObserve or use OpenObserve cloud, check quickstart documentation.
For installing OpenObserve in High Availability mode, check High Availability deployment documentation.
Production Ready
OpenObserve is battle-tested in production environments worldwide:
Customer Stories →
Comparisons to Familiar Tools
OpenObserve vs Datadog
OpenObserve is a Datadog alternative that gives you full control over your data and costs.
OpenObserve vs Elasticsearch
OpenObserve achieves 140x lower storage costs through Parquet columnar format and S3-native architecture.
OpenObserve vs Splunk
OpenObserve is an open-source Splunk alternative without the licensing complexity.
OpenObserve vs Grafana/Loki/Prometheus Stack
OpenObserve consolidates logs, metrics, and traces in one platform instead of stitching together multiple tools.
📷 Screenshots
OpenObserve includes a powerful web UI for logs, traces, dashboards, alerts, and more.
Logs Search
Distributed Tracing
Trace details page with full request flow visualization:
Dashboards
Frontend Monitoring
Real user monitoring with session replay:
See more screenshots
Home
Golden Metrics from Traces
More Dashboard Examples
Performance Analytics
Error Tracking
Alerts
Streams
Ingestion
Pipeline
Functions
🔐 Security & Compliance
Security Features
Compliance Certifications
OpenObserve meets the stringent security and compliance requirements of regulated industries including finance, healthcare, and government.
⚖️ License
Open Source Edition: Licensed under AGPL-3.0. We chose AGPL to ensure that improvements to OpenObserve remain open source and benefit the entire community. This license protects the commons while still allowing free commercial use.
Enterprise Edition: Licensed under a commercial Enterprise License Agreement, not AGPL. This provides additional flexibility for enterprise deployments and eliminates any concerns about AGPL requirements.
For more details:
💼 Enterprise Support
OpenObserve is built as a true open source project, and we’re committed to the community. The open source version is feature-complete and production-ready - it includes logs, metrics, traces, dashboards, alerts, pipelines, and everything you need to run observability at scale. It will always remain actively maintained and free to use without restrictions.
Enterprise Edition
For organizations requiring enterprise-grade features and support, we offer an Enterprise edition with:
Enterprise Features:
Enterprise Support & SLAs:
Pricing:
For enterprise inquiries and custom deployments, contact our sales team.
🤝 Contributing
We welcome contributions from the community! Whether you’re fixing bugs, adding features, improving documentation, or sharing feedback, your help makes OpenObserve better for everyone.
To get started, please read our Contributing Guide which covers:
🌍 Community
The best way to get help, share ideas, and connect with other OpenObserve users is through our community channels. We’re a friendly group of developers, operators, and observability enthusiasts.
🔗 Join us on Slack
Our Slack community is the most active place for:
Join the conversation →
📱 Join OpenObserve community on WeChat
Other ways to connect
❓ FAQ
How does OpenObserve achieve 140x lower storage costs?
Through a combination of Parquet columnar storage format (efficient compression), S3-native architecture (leveraging inexpensive object storage). See the detailed comparison chart in the “Why OpenObserve?” section above.
What are the limitations?
All data in OpenObserve is immutable - once ingested, it cannot be modified or deleted (only entire retention periods can be dropped). This is by design and is actually a feature for logs and compliance requirements, ensuring data integrity and audit trails.
Is this production-ready?
Yes. OpenObserve is running in production with thousands of deployments worldwide, including environments processing in excess of 2 PB/day. See our customer stories for real-world examples.
How does query performance compare to Elasticsearch?
OpenObserve delivers better performance than Elasticsearch for most workloads. Users report faster search performance and significantly faster analytics queries, all while using 1/4th the hardware resources. The columnar storage format (Parquet) is particularly effective for complex aggregations and analytics workloads.
Is there a steep learning curve?
No. OpenObserve is designed to be intuitive from day one:
Most users are productive within hours, not weeks. Some even claim minutes, but we’ll let you be the judge.
🔐 SBOM
Software Bill of Materials for OpenObserve
Rust
SBOM can be found here. You can analyze it using dependency track.
In order to generate the SBOM, you can use the following commands:
Install cargo-cyclonedx:
Generate the SBOM:
JavaScript
SBOM can be found here. You can analyze it using dependency track.
In order to generate the SBOM, you can use the following commands:
Install cyclonedx-npm:
Generate the SBOM: