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dropwizard/metrics

0
View on GitHub↗
7,845 stars·1,794 forks·Java·Apache-2.0·27 viewsmetrics.dropwizard.io↗

Metrics

This project is an application performance monitoring tool and JVM metrics library designed to measure workload behavior and export performance data to external monitoring databases. It serves as an instrumentation toolkit for tracking resource usage and internal runtime behavior within a Java execution environment.

The system focuses on application performance measurement and JVM application monitoring, specifically tracking system health and runtime resource analysis to identify bottlenecks and stability issues. It provides a mechanism for external metrics export, sending captured data to third-party tools for long-term analysis and visualization.

Features

  • Application Performance Monitoring - Provides a comprehensive system for tracking runtime performance bottlenecks and operational health of applications.
  • JVM Instrumentation Toolkits - Provides a toolkit for tracking resource usage and internal runtime behavior within a Java execution environment.
  • Global Metric Registries - Maintains a central registry to store and organize active measurement objects for coordinated reporting and lifecycle management.
  • JVM Application Monitoring - Monitors the internal health and resource utilization of the Java Virtual Machine runtime.
  • Metrics Exporters - Exposes captured performance metrics to external monitoring tools and databases for long-term storage and analysis.
  • Performance Measurement - Captures real-time execution data and high-resolution resource tracking to optimize software efficiency.
  • Point-In-Time Snapshots - Captures current metric values as immutable point-in-time snapshots to ensure consistency during reporting cycles.
  • JVM Runtime Analysis - Monitors internal memory and CPU behavior within the JVM to detect leaks and stability issues.
  • Reporting Plugins - Provides pluggable reporter classes that translate internal metric data into specific formats for external monitoring tools.
  • Latency Distribution Histograms - Captures performance data in buckets to approximate the statistical distribution of request latencies and sizes.
  • Hardware Metric Polling - Utilizes a polling mechanism to periodically read real-time metrics and export them to external systems.
  • Thread-Safe Metric Counters - Implements thread-safe counters to track real-time numerical metrics across concurrent operations without data corruption.
  • Monitoring - Library for exposing application metrics.
  • Logging Frameworks - Exposes application metrics via JMX or HTTP.

Star history

Star history chart for dropwizard/metricsStar history chart for dropwizard/metrics

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Metrics

These projects share indexed features with Metrics. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • micrometer-metrics/micrometermicrometer-metrics avatar

    micrometer-metrics/micrometer

    4,850View on GitHub↗

    Micrometer is a dimensional metrics library and application metrics facade that provides a vendor-neutral interface for recording performance data. It decouples application instrumentation from specific observability backends, allowing the recording of counters, gauges, and timers using key-value tags for granular analysis. The project features a system of backend adapters that transform and route instrumented data to various external monitoring tools. This includes name normalization to ensure portability across different monitoring systems and the ability to map dimensional data to hierarch

    Java
    View on GitHub↗4,850
  • metrics-rs/metricsmetrics-rs avatar

    metrics-rs/metrics

    1,422View on GitHub↗

    This project is a unified observability framework for Rust applications, designed to capture, aggregate, and report performance telemetry. It provides a comprehensive toolkit for instrumenting code to track counters, gauges, and histograms, enabling developers to monitor application health and operational performance through a standardized interface. The library distinguishes itself by decoupling instrumentation sites from specific backend implementations through a global registry and trait-based abstractions. This architecture allows developers to swap telemetry exporters at runtime without

    Rustmetricsrust-langtelemetry
    View on GitHub↗1,422
  • naver/pinpointnaver avatar

    naver/pinpoint

    13,833View on GitHub↗

    Pinpoint is a distributed application performance monitoring and tracing system. It functions as an application performance monitor and topology visualizer designed to analyze the execution behavior of large-scale distributed applications. The system uses bytecode instrumentation to monitor applications without requiring changes to the original source code. It captures call stacks and request flows across interconnected services to visualize system dependencies and generate real-time architectural maps of communication patterns. The platform covers a broad range of observability capabilities

    Java
    View on GitHub↗13,833
  • prometheus/client_javaprometheus avatar

    prometheus/client_java

    2,277View on GitHub↗

    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, includ

    Javainstrumentationjavametrics
    View on GitHub↗2,277
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Frequently asked questions

What does dropwizard/metrics do?

This project is an application performance monitoring tool and JVM metrics library designed to measure workload behavior and export performance data to external monitoring databases. It serves as an instrumentation toolkit for tracking resource usage and internal runtime behavior within a Java execution environment.

What are the main features of dropwizard/metrics?

The main features of dropwizard/metrics are: Application Performance Monitoring, JVM Instrumentation Toolkits, Global Metric Registries, JVM Application Monitoring, Metrics Exporters, Performance Measurement, Point-In-Time Snapshots, JVM Runtime Analysis.

Which projects share features with dropwizard/metrics?

Projects with overlapping indexed features include: micrometer-metrics/micrometer — Micrometer is a dimensional metrics library and application metrics facade that provides a vendor-neutral interface… metrics-rs/metrics — This project is a unified observability framework for Rust applications, designed to capture, aggregate, and report… naver/pinpoint — Pinpoint is a distributed application performance monitoring and tracing system. It functions as an application… prometheus/client_java — This library provides a framework for instrumenting Java applications to track performance and system-level… openzipkin/zipkin — Zipkin is an open-source distributed tracing system designed to collect, store, and visualize timing data across… google/mtail — mtail is a log-based metrics extractor and time-series monitoring agent. It functions as a log pattern parser that…