prometheus/client_java
Client Java
This library provides a framework for instrumenting Java applications to track performance and system-level statistics. It enables the definition and collection of metrics such as counters, gauges, and histograms, while automatically capturing runtime health indicators like memory usage, thread activity, and garbage collection performance.
The project distinguishes itself through a registry-based aggregation model that decouples metric recording from data exposition. It supports thread-safe atomic instrumentation for high-frequency data collection and offers flexible export mechanisms, including HTTP-based scraping, push-gateway support for ephemeral processes, and translation bridges for modern observability standards like OpenTelemetry.
The toolkit includes capabilities for linking metric data points to distributed traces to provide context for performance anomalies. It also facilitates the migration of legacy instrumentation and allows for dynamic configuration of collection and export behaviors without requiring application restarts.
Features
- Application Metrics Exporters - Provides HTTP endpoints and push-based mechanisms to make application performance data available for scraping.
- JVM Application Monitoring - Instruments applications to track performance and system health using standard counters, gauges, and histograms.
- Pull-Based Metric Scraping - Exposes internal state through an HTTP endpoint for periodic collection by external monitoring systems.
- Metric Collection - Tracks application state and performance using counters, gauges, and histograms to provide visibility into system behavior.
- Prometheus-Formatted HTTP Endpoints - Exposes application performance data over HTTP endpoints to allow monitoring systems to scrape metrics.
- JVM Resource Monitoring - Tracks system-level statistics like memory usage and thread counts alongside custom application metrics.
- Prometheus Client Libraries - Provides tools for recording and exposing application metrics from JVM-based languages to monitoring systems.
- Metric Registries - Centralizes metric storage in a thread-safe registry that decouples recording from data exposition.
- Custom Telemetry Definitions - Enables the creation of counters, gauges, and histograms to track application state and performance distributions.
- System Statistics Collection - Automatically collects system-level health indicators including garbage collection, memory usage, and thread activity.
- Metric Push Gateways - Buffers metrics from short-lived or batch processes into a persistent intermediary service for reliable collection.
- Atomic Thread Synchronization - Uses low-overhead atomic primitives to record high-frequency performance data across concurrent threads.
- Legacy Metric Ingestion - Provides compatibility layers to translate and ingest legacy metric definitions into the modern registry system.
- Metric Gateways - Buffers metrics from short-lived or batch processes into an intermediary service to allow for reliable collection.
- Metrics Exporters - Transmits instrumented performance data to external monitoring platforms using specialized bridge collectors.
- Distributed Tracing - Links specific metric data points to distributed traces to provide context for performance spikes.
- OpenTelemetry Standard Integrations - Translates internal application metrics into standard formats for compatibility with modern observability platforms.
- Trace Linking - Attaches specific trace identifiers to metric data points to provide direct context for performance anomalies.
- OpenTelemetry Exporters - Translates internal application metrics into standard formats for integration with modern observability platforms.
