Metrics
OpenObserve provides comprehensive metrics collection, storage, and visualization capabilities for monitoring your applications and infrastructure performance in real-time.
Overview
Metrics in OpenObserve enable you to track key performance indicators, monitor system health, and gain insights into your application's behavior over time. Designed for high-throughput environments, OpenObserve efficiently handles metrics ingestion, storage, and querying at scale while maintaining cost-effectiveness.
Metrics Page view
Key Features
Metrics Ingestion
- Multiple Formats: Support for multiple formats including Prometheus remote-write and structured JSON metrics via HTTP ingestion.
- Push & Pull Models: Supports push-based ingestion and integration with systems like Prometheus for pull-based scraping.
- High Throughput: Handle millions of metrics per second with minimal latency
- Optimized Processing: Optimized ingestion pipelines for high-throughput environments.
Data Types & Structure
- Time Series Data: Native support for time-series metrics with timestamp precision
- Multi-dimensional: Handle metrics with multiple labels and dimensions for detailed analysis
- Aggregation Functions: Built-in support for common aggregation functions (sum, avg, min, max, count)
- Custom Metrics: Flexible schema for application-specific metrics and KPIs
Query & Analysis
- PromQL Support: Full compatibility with Prometheus Query Language for familiar querying
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SQL Interface: Use SQL syntax for complex metrics analysis and reporting
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Time Range Selection: Flexible time range queries with support for relative and absolute time periods
- Mathematical Operations: Perform calculations and transformations on metrics data
Visualization & Dashboards
- Real-time Charts: Interactive time-series visualizations with multiple chart types
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Custom Dashboards: Create comprehensive dashboards with multiple metrics panels
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Alerting Integration: Set up alerts based on metrics thresholds and conditions
Storage & Performance
- Optimized Compression: Advanced compression algorithms reduce storage costs.
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Efficient Indexing: High-performance indexing for fast query execution across large datasets
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Downsampling: Automatic data downsampling for long-term storage optimization
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Retention Policies: Configurable retention settings to balance storage costs and data availability
Integration & Compatibility
- Prometheus Compatible: Full compatibility with Prometheus ecosystem and exporters
- OpenTelemetry Ecosystem: Full compatibility with OpenTelemetry collectors and instrumentation libraries
- API Access: RESTful APIs for programmatic access to metrics data
- Standard Exporters: Support for popular metrics exporters (Node Exporter, cAdvisor, etc.)