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btraceio/btrace

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5,989 Stars·956 Forks·Java·Apache-2.0·10 Aufrufe

Btrace

btrace ist ein JVM-Tool für dynamisches Tracing und Performance-Profiling, das zum Injizieren sicherer Instrumentierungsskripte in eine laufende Java Virtual Machine verwendet wird, ohne dass ein Prozessneustart erforderlich ist. Es fungiert als Java-Agent-Framework und als Model Context Protocol-Server, der JVM-Diagnoseoperationen und Tracing-Tools für Large Language Models und KI-Assistenten bereitstellt.

Das Projekt zeichnet sich durch die Ermöglichung von Echtzeit-Code-Injektion und Bytecode-Level-Instrumentierung über ein sicheres binäres Protokoll aus. Es stellt die Produktionsstabilität durch eine statische Sicherheitsanalyse-Engine sicher, die instabile Codemuster, wie Schleifen und Allokationen, während der Skript-Kompilierungsphase blockiert.

Das System deckt ein breites Spektrum an Observability-Funktionen ab, einschließlich Methoden-Ausführungs-Tracing, Objekt-Allokations-Tracking und Field-Access-Monitoring. Es bietet Performance-Profiling durch Latenzmetriken und Ausführungsdaten-Sampling und kann benutzerdefinierte Java Flight Recorder-Events für native Analysen ausgeben.

Der Agent unterstützt flexible Bereitstellungsstrategien, einschließlich Bootstrapping beim Start oder das Anhängen an Live-Prozesse in containerisierten Umgebungen mittels Fat-JAR-Bundles.

Features

  • Java Instrumentation Frameworks - Provides a complete framework for building and deploying Java agents that perform bytecode-level instrumentation.
  • JVM Instrumentation Toolkits - Provides a toolkit for injecting and executing custom logic into a running Java Virtual Machine without requiring a restart.
  • Runtime Agent Attachment - Provides the ability to attach an instrumentation agent to a live Java Virtual Machine process without restart.
  • Method Execution Tracking - Captures method entry, exit, and return values to analyze timings and track execution flow.
  • AI Agent Integrations - Connects external AI agents and language models to live JVM runtimes using the Model Context Protocol.
  • Model Context Protocol Integrations - Connects Java virtual machines to AI assistants using the standardized Model Context Protocol for automated diagnostics.
  • MCP Protocol Integrations - Implements the Model Context Protocol to expose JVM diagnostic operations and tracing tools to AI assistants.
  • Model Context Protocol Servers - Implements a Model Context Protocol server to expose JVM diagnostic tools to AI assistants.
  • Runtime Process Attachers - Enables attaching to and modifying live JVM processes via instrumentation APIs for real-time monitoring.
  • JVM Profiling Tools - Profiles JVM performance by measuring method latency and tracking object allocations.
  • Method Execution Trackers - Monitors the duration and output of specific Java methods at runtime using class and method patterns.
  • Runtime Code Injection - Enables the insertion of tracing logic into a live process without requiring a restart.
  • JVM Agent Communication - Establishes a high-performance binary communication link between a local client and a remote JVM agent.
  • Instrumentation Safety Analysis - Analyzes instrumentation scripts at compile time to block unstable patterns like infinite loops or excessive allocations.
  • Bytecode Instrumentation Agents - Modifies compiled bytecode at runtime to inject monitoring logic at method entry, return, and exception points.
  • Dynamic Instrumentation Injections - Injects tracing scripts into running JVM processes to modify and monitor behavior without restarts.
  • Method Interception Proxies - Implements dynamic method interception to inject custom behavior into function calls without altering source code.
  • Dynamic Tracing Tools - Acts as a dynamic tracing tool for injecting safe instrumentation scripts into running JVMs.
  • Live Process Code Injection - Injects and executes compiled scripts into an active JVM process to extract internal state without termination.
  • Application Performance Profiling - Measures method execution durations and analyzes call stacks to identify bottlenecks in live Java applications.
  • LLM Interfaces - Exposes runtime diagnostic operations to language models through a common protocol for simplified troubleshooting.
  • Method Performance Profiling - Measures execution time for specific methods and filters results to identify performance bottlenecks.
  • Agent Packaging - Packages tracing extensions into self-contained JAR files for deployment across distributed environments like Kubernetes.
  • Ad-hoc Trace Executions - Runs short command-line scripts to print, count, or time events for rapid debugging.
  • Runtime Call-Stack Capturers - Captures active execution frames to identify the sequence of method calls leading to an event.
  • Runtime Value Capture - Captures function arguments, return values, and execution durations during runtime instrumentation.
  • Isolated Service Interfaces - Enables development of injectable service interfaces that maintain classloader isolation.
  • Instrumentation Extension Packaging - Bundles tracing logic into artifacts while automatically inferring the system permissions required for execution.
  • Classloader Isolation - Uses isolated Java class loaders to prevent dependency conflicts between tracing extensions and the target application.
  • Agent Functionality Extensions - Supports extending the agent's capabilities via a stable API and isolated implementation modules.
  • Agent JAR Bundling - Packages instrumentation extensions into a single, self-contained JAR file for simplified deployment in distributed environments.
  • Binary Communication Protocols - Uses a high-performance binary serialization and transport protocol for communication between client and agent.
  • Custom Event Production - Creates custom recording events to leverage high-performance native Java Flight Recorder recording engines.
  • Event Aggregators - Summarizes multiple execution events into totals and averages to identify performance patterns.
  • Startup Instrumentation - Allows agents to be pre-loaded at startup to capture events from the earliest stages of the application lifecycle.
  • Startup Agent Bootstrapping - Starts applications with a pre-loaded agent to ensure instrumentation is active from the earliest launch stages.
  • Thread-Local State Management - Stores independent data copies for each thread to track state across different instrumentation handlers.
  • Execution Trace Streams - Routes execution data and structured spans from the instrumented process back to a client for real-time display.
  • Exception Traceback Capture - Captures full stack traces automatically when exceptions occur during JVM execution.
  • Plugin Installation and Management - Provides a system for installing and managing plugins that expand the agent's functionality.
  • Memory Usage Analysis - Calculates the size of specific objects and monitors heap and non-heap consumption at runtime.
  • Latency Histograms - Records duration distributions and statistics using histograms to track method execution timing.
  • Thread-Local Storage - Maintains ephemeral data associated with specific threads to share state across multiple instrumentation handlers.
  • Data Access Tracing - Intercepts and monitors reads and writes to specific object fields and arrays during JVM runtime.
  • Lifecycle Startup Tracing - Instruments the application before its main code executes to capture early lifecycle events.
  • Execution Event Sampling - Captures a representative subset of runtime events to minimize the performance overhead of tracing.
  • Execution Sampling Filters - Reduces instrumentation overhead by capturing only a fraction of method invocations based on sampling rates.
  • Ad-hoc Diagnostic One-liners - Allows executing concise command-line scripts to perform quick debugging tasks like counting invocations or filtering slow methods.
  • Field Access Tracking - Intercepts reads and writes to specific object fields to monitor state changes in real-time.
  • JFR Event Producers - Creates and emits custom Java Flight Recorder events from dynamic instrumentation probes for native performance analysis.
  • Dynamic Probe Toggles - Allows toggling sets of instrumentation probe handlers at runtime to adjust diagnostic detail.
  • Probe Lifecycle Management - Allows users to list, trigger events for, and remove active instrumentation probes at runtime.
  • Trace Exporters - Exports recorded execution event streams into standard formats for external visualization and performance analysis.
  • Stack Trace Capturers - Records the sequence of method calls to diagnose execution paths via active thread stacks.
  • Object Allocation Profilers - Samples object allocations and aggregates thread stacks to identify hot paths in the target environment.
  • Performance Distribution Analyzers - Computes and prints statistical distributions of numeric values to analyze method execution latencies.
  • Safe Tracing Constraints - Enforces safety constraints on runtime scripts to prevent loops and allocations that could crash production applications.
  • Trace Event Filters - Provides conditional logic to filter trace events and reduce noise in the output.

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Häufig gestellte Fragen

Was macht btraceio/btrace?

btrace ist ein JVM-Tool für dynamisches Tracing und Performance-Profiling, das zum Injizieren sicherer Instrumentierungsskripte in eine laufende Java Virtual Machine verwendet wird, ohne dass ein Prozessneustart erforderlich ist. Es fungiert als Java-Agent-Framework und als Model Context Protocol-Server, der JVM-Diagnoseoperationen und Tracing-Tools für Large Language Models und KI-Assistenten bereitstellt.

Was sind die Hauptfunktionen von btraceio/btrace?

Die Hauptfunktionen von btraceio/btrace sind: Java Instrumentation Frameworks, JVM Instrumentation Toolkits, Runtime Agent Attachment, Method Execution Tracking, AI Agent Integrations, Model Context Protocol Integrations, MCP Protocol Integrations, Model Context Protocol Servers.

Welche Open-Source-Alternativen gibt es zu btraceio/btrace?

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