pinpoint-apm/pinpoint

Features

• Application Performance Monitoring - Analyzes call stacks and transaction response times to pinpoint the exact line of code causing performance degradation.
• Database Performance Monitoring - Monitors query execution times and connection pool utilization across various JDBC drivers to resolve data access bottlenecks.
• Distributed Tracing Backends - Provides a backend for storing and analyzing distributed trace data from compatible sources.
• Topology Visualizers - Aggregates trace dependencies to render a live map of service interconnections and system health statuses.
• Distributed Trace Propagation - Maintains trace context across service boundaries using headers to map upstream callers.
• Trace Data Ingestion - Implements endpoints for receiving distributed trace spans via gRPC or HTTP protocols.
• Tracing Context Propagation - Injects unique identifiers into request headers to link spans across multiple microservices and reconstruct call chains.
• Runtime Bytecode Instrumentation - Injects monitoring logic into application binaries at runtime via a Java agent to capture execution metrics.
• Asynchronous Tracing - Captures execution flow across reactive streams and coroutines to maintain trace continuity in non-blocking applications.
• Coroutine State Inspection - Analyzes the execution state and stack traces of active Kotlin coroutines to maintain trace continuity.
• Distributed APM Tools - Provides a performance management system that traces requests and monitors metrics across large-scale distributed architectures.
• JVM Application Monitoring - Tracks thread activity, garbage collection, and resource utilization specifically for Java applications.
• Metric Data Ingestion - Collects and imports large volumes of performance metrics and agent data into a centralized store.
• Distributed Tracing - Tracks requests across distributed systems using unique identifiers to analyze execution flow and bottlenecks.
• Distributed Request Tracers - Tracks request flows and visualizes dependencies across multiple interconnected services to identify bottlenecks.
• JVM Resource Monitoring - Tracks real-time CPU usage, memory consumption, and garbage collection patterns to optimize Java application health.
• System Health Monitors - Tracks real-time system metrics including CPU usage, memory, and transaction throughput to assess overall health.
• Connection Pool Observability - Tracks the performance and usage of database connection pools to identify data access bottlenecks.
• MongoDB Driver Monitoring - Tracks the execution of database operations performed via the MongoDB Java driver.
• Instrumentation Filters - Applies include and exclude rules to determine which specific packages or classes should be instrumented.
• Response Time Trend Analysis - Analyzes request counts and response time distributions over time to detect performance anomalies.
• MySQL Driver Monitoring - Tracks the execution of database queries via the MySQL JDBC driver to analyze latency.
• Query Performance Monitors - Analyzes MyBatis database logs and execution statistics to identify query bottlenecks.
• Asynchronous Request Tracing - Tracks execution and latency of asynchronous HTTP client requests to visualize network call patterns.
• Distributed Tracing - Collects and visualizes trace data from OpenTelemetry compatible sources via gRPC or HTTP.
• Performance Monitoring - Tracks performance and traces requests flowing through gRPC services to identify bottlenecks.
• RPC Execution Tracing - Provides tracing and monitoring of the active lifecycle of remote procedure calls implemented using the Apache Thrift framework.
• Database Performance Monitors - Tracks real-time metrics and execution times for database queries made via the JTDS driver.
• End-to-End Message Tracing - Tracks the full lifecycle of MQTT publications and subscriptions to identify performance bottlenecks.
• Function Monitoring - Aggregates metrics, logs, and traces from serverless functions running within OpenWhisk.
• Trace-to-Log Mappers - Maps Log4j2 logging events to trace span attributes to correlate logs with transaction data.
• Messaging Performance Diagnostics - Analyzes the performance and latency of message producers and consumers across Kafka, RabbitMQ, and RocketMQ.
• HTTP Client Monitoring - Monitors and records the execution time and details of HTTP requests made via the OkHttp client.
• Database Monitoring - Provides performance tracking and metric collection specifically for IBM DB2 database systems.
• Thread Activity Monitors - Provides real-time tracking of active threads to identify concurrency issues and application hangs.
• Server Status Monitors - Tracks request and response metrics for the Jetty web server to identify performance bottlenecks.
• Observability Tracing - Captures and records logging activity from the Log4j framework to provide observability traces.
• Instrumentation Path Filtering - Defines include and exclude patterns to control which specific packages or classes are tracked.
• Query Performance Monitoring - Tracks and visualizes the performance of data processing queries sent via the Informix JDBC driver.
• Reactive Stream Monitoring - Tracks the execution flow and performance of asynchronous data streams.
• Root Cause Analysis - Diagnoses the source of application errors and performance degradation by linking them to specific traces.
• Reactive Web Server Monitoring - Monitors the performance and flow of asynchronous requests across Netty, Tomcat, Undertow, and Jetty.
• Web Server Performance Monitoring - Tracks the execution and performance of requests processed by the Apache Tomcat web server.
• Spring Framework Monitoring - The product tracks execution and performance metrics for Spring-based applications.
• Code-Level Transaction Analysis - Provides detailed inspection of transactions at the method and line level to pinpoint performance bottlenecks.
• HTTP Client Monitoring - Tracks and analyzes the performance of requests made via the JDK HttpClient.
• Distributed Tracing - Performance management for large-scale distributed architectures.

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