For सेल्फ-होस्टेड APM प्लेटफॉर्म, the strongest matches are apache/incubator-skywalking (Apache SkyWalking is a comprehensive, open-source APM platform that), apache/skywalking (Apache SkyWalking is a full-featured, self-hostable APM platform that) and highlight/highlight (Highlight is a self-hosted, open-source observability platform that combines). getsentry/sentry and signoz/signoz round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
अपने खुद के इंफ्रास्ट्रक्चर के भीतर एप्लिकेशन परफॉरमेंस मेट्रिक्स को ट्रैक, एनालाइज और विज़ुअलाइज़ करने के लिए ओपन-सोर्स टूल्स।
SkyWalking is a comprehensive observability stack and application performance monitoring platform. It functions as a distributed tracing system and an AI application monitor, providing a centralized suite for collecting and analyzing logs, metrics, and traces to maintain the health of containerized architectures. The platform distinguishes itself through a service topology visualizer that renders interactive maps of infrastructure dependencies and communication patterns. It also includes specialized capabilities for generative AI workflow observation to track the execution flow and performanc
Apache SkyWalking is a comprehensive, open-source APM platform that provides distributed tracing, metrics collection, log aggregation, service topology maps, and built-in alerting and anomaly detection, making it a strong fit for a self-hostable, full-stack performance monitoring solution.
SkyWalking is an application performance monitoring system and observability platform designed to collect and analyze metrics, traces, and logs from distributed microservices. It functions as a distributed tracing platform and a telemetry data pipeline that ingests and aggregates observability data from various language agents. The project features an AI-powered anomaly detector that uses machine learning to calculate metric baselines and identify irregular URI patterns. It includes an eBPF performance profiler for diagnosing CPU and network bottlenecks at the kernel level and generates inter
Apache SkyWalking is a full-featured, self-hostable APM platform that collects metrics, traces, and logs from distributed systems, includes AI-powered anomaly detection and eBPF profiling, and supports multi-language instrumentation—exactly the observability stack you’re looking for.
Highlight is a full-stack observability platform and monitoring system that aggregates logs, errors, and distributed traces to provide a unified view of application health. It functions as a distributed tracing system, an error monitoring service, and a session replay tool. The platform is available as a dockerized monitoring stack for self-hosted deployments on Linux. It distinguishes itself by combining backend observability with a visual recording system that captures document object model changes and network requests to replay user interactions. The system covers several core capability
Highlight is a self-hosted, open-source observability platform that combines distributed tracing, log aggregation, error monitoring, and session replay, directly matching the full-stack APM monitoring stack this visitor is looking for.
This project is a comprehensive software observability suite and application performance monitoring platform designed to track runtime errors, performance bottlenecks, and system health. It functions as a centralized diagnostic service that aggregates and categorizes exceptions, providing the infrastructure necessary to visualize complex execution paths across distributed systems and microservices. The platform distinguishes itself through a high-throughput distributed event ingestion pipeline and a columnar storage analytics engine that enables rapid aggregation of large-scale performance me
Sentry is a self-hostable observability and APM platform that provides distributed tracing, code-level instrumentation, service maps, alerting, real-time dashboards, and logs integration across many languages, making it a comprehensive fit for diagnosing application performance issues.
SigNoz is a full-stack observability platform designed to collect, store, and visualize metrics, logs, and distributed traces in a unified environment. It leverages OpenTelemetry-based data collection to ingest telemetry from diverse sources using vendor-neutral protocols, ensuring interoperability across complex microservices architectures. The platform utilizes a high-performance columnar storage engine to enable rapid aggregation and filtering, providing a centralized backend for monitoring application health and performance. What distinguishes the platform is its focus on automated instru
SigNoz is a full-stack observability platform that natively unifies metrics, traces, and logs with OpenTelemetry-based instrumentation, service dependency mapping, and alerting — exactly the self-hosted APM stack you're looking for, covering every requested feature from distributed tracing to multi-language support.
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
Pinpoint is a distributed APM and tracing system that uses bytecode instrumentation to collect metrics, trace request flows, and visualize service topologies—directly matching the core observability needs—though its multi-language support is primarily Java-focused, which may limit the "multi-language" requirement.
OpenObserve is a unified observability data platform designed to ingest, store, and analyze logs, metrics, and traces. It functions as a cloud-native monitoring tool that centralizes telemetry from diverse sources, including standard collectors and cloud service providers, into a single, scalable system. By utilizing a columnar storage engine backed by object storage, the platform enables efficient long-term data retention and high-performance analytical querying. The platform distinguishes itself through deep integration with artificial intelligence, allowing users to query data using natura
OpenObserve is a unified observability data platform that ingests and analyzes logs, metrics, and traces with AI-driven querying, making it a comprehensive self-hosted APM stack supporting distributed tracing, metrics collection, service maps, alerting, and multi-source telemetry — exactly what this search requires.
HyperDX is an OpenTelemetry observability platform that provides centralized log management, distributed tracing, and a self-hosted monitoring stack. It functions as a unified system for collecting, indexing, and visualizing logs, metrics, and traces from cloud and container environments. The platform distinguishes itself with specialized tooling for large language model monitoring and session replay, allowing user interactions in the browser to be linked to backend telemetry. It employs schema-less JSON parsing to index structured logs dynamically and uses source maps to resolve minified sta
HyperDX is a self-hosted OpenTelemetry observability platform that centralizes logs, metrics, and traces with built-in distributed tracing, alerting, and real-time dashboards—exactly what this APM stack search is after.
Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r
Uptrace is a full-featured, self-hosted observability platform built on OpenTelemetry that collects distributed traces, metrics, and logs; it provides real-time dashboards, AI-powered alerting and anomaly detection, and multi-language support through OpenTelemetry instrumentation, making it an excellent fit for your APM requirements.
Pinpoint is a distributed application performance management tool designed to trace requests and monitor metrics across large-scale distributed architectures. It functions as a request tracer, topology mapper, and JVM application monitor, providing a backend capable of collecting and visualizing trace data from OpenTelemetry compatible sources. The system distinguishes itself through a combination of bytecode-based instrumentation via a Java agent and topology-based visualization that renders live maps of service interconnections. It captures execution flow across asynchronous boundaries, suc
Pinpoint is a self-hostable open-source APM tool that provides distributed tracing via bytecode instrumentation, service topology maps, and metrics monitoring—directly matching the visitor's need to collect traces, metrics, and logs for troubleshooting application performance across multiple services and languages.
Anteon is a distributed load testing platform and automated performance testing suite designed to simulate high-traffic user scenarios and measure system performance across multiple global locations. It functions as an infrastructure anomaly detector and a service dependency mapper, providing a performance monitoring dashboard to track real-time resource usage across cluster instances. The project distinguishes itself by combining distributed traffic generation with service dependency mapping to identify system bottlenecks through network-level tracing. It incorporates an automated validation
Anteon is a distributed load-testing platform that also provides service-dependency mapping and anomaly detection, so it fits the APM category with metrics and topology features, though its primary focus on load generation rather than code-level instrumentation means it's a narrower match for a comprehensive APM stack.
The server acts as a centralized ingestion engine designed to collect, normalize, and index distributed telemetry data. It functions as a backend processor that receives performance metrics, traces, and error logs from application agents, transforming them into structured documents for storage and analysis within search and analytics platforms. The system distinguishes itself through a high-throughput ingestion pipeline that utilizes asynchronous event processing and backpressure-aware flow control to maintain stability during traffic spikes. It employs modular, plugin-based transformation st
Elastic APM Server is a dedicated server component of the Elastic APM stack that ingests traces, metrics, and logs from agents into Elasticsearch, giving you distributed tracing, service maps, and real-time dashboards — aligning directly with the visitor’s self-hosted, full-featured APM requirements.
VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct
VictoriaMetrics is a time series database and observability platform that can ingest metrics, logs, and traces via OpenTelemetry and Prometheus protocols, making it a valid APM backend—but its focus as a storage and query engine means it lacks built-in code-level instrumentation, service maps, and application-specific alerting that a full APM stack typically provides.
Cat is a distributed application performance monitoring tool and tracing framework designed to track transactions, latency, and health across distributed services. It functions as a Kubernetes-native monitoring stack that utilizes multi-language monitoring clients and a real-time alerting system to maintain system visibility. The system provides monitoring clients for Java, Go, Python, Node.js, and C++ to collect performance metrics and trace data. It distinguishes itself by sampling request flows to record call chains and identify bottlenecks, while using a monitoring engine to trigger immed
Cat is a self-hosted distributed APM tool with multi-language instrumentation, distributed tracing, metrics collection, and real-time alerting, covering the core monitoring need though without explicit service maps or full logs integration.
Pixie is an open-source observability platform for Kubernetes that uses eBPF to automatically capture telemetry data from clusters without requiring any manual instrumentation or code changes. It functions as an eBPF telemetry collector, a continuous application profiler, a network traffic analyzer, and a scriptable telemetry query engine, all within a single Kubernetes-native tool. The platform distinguishes itself through several integrated capabilities. It continuously samples stack traces from compiled-language code to identify CPU performance bottlenecks, visualizing the results as inter
Pixie is a self-hosted Kubernetes-native observability platform that automatically captures metrics, traces, and profiles via eBPF, which aligns with the core APM needs—though it relies on the cluster for deployment and lacks built-in alerting, it is still an operational application performance monitoring tool.
Kibana is a browser-based data exploration and visualization platform designed for interacting with information stored in distributed search engines. It serves as a centralized interface for analyzing structured and unstructured data, enabling users to build custom dashboards, generate interactive charts, and map complex datasets to uncover trends and actionable insights. Beyond visualization, the platform functions as a comprehensive management console for infrastructure operations. It provides tools for configuring security policies, managing data indices, and monitoring system health. The
Kibana is a visualization and management platform for Elasticsearch, but on its own it does not collect metrics, traces, or logs—it requires a separate Elastic APM stack (Elasticsearch and APM agents) to function as a complete APM solution, making it a component rather than a self-contained monitoring stack.
This project is a self-hosted application performance monitoring tool designed for Ruby on Rails environments. It functions as a diagnostic platform that tracks request response times, database query efficiency, and background job performance to help identify bottlenecks within web application infrastructure. The tool distinguishes itself by integrating directly into the framework to provide real-time performance insights and developer-focused utilities, such as direct navigation from error reports to the corresponding lines in a code editor. It supports complex analysis by correlating perfor
A self-hosted performance monitor for Rails applications, this tool fits the APM category but is limited to Ruby on Rails and may lack the broader multi-language tracing, logs integration, and service maps you specified.
| रिपॉजिटरी | स्टार्स | भाषा | लाइसेंस | अंतिम पुश |
|---|---|---|---|---|
| apache/incubator-skywalking | 24.8K | Java | Apache-2.0 | |
| apache/skywalking | 24.8K | Java | Apache-2.0 | |
| highlight/highlight | 9.3K | TypeScript | NOASSERTION | |
| getsentry/sentry | 44.1K | Python | NOASSERTION | |
| signoz/signoz | 27.4K | TypeScript | NOASSERTION | |
| naver/pinpoint | 13.8K | Java | Apache-2.0 | |
| openobserve/openobserve | 17.9K | TypeScript | agpl-3.0 | |
| hyperdxio/hyperdx | 9.3K | TypeScript | mit | |
| uptrace/uptrace | 4.1K | Go | agpl-3.0 | |
| pinpoint-apm/pinpoint | 13.8K | Java | Apache-2.0 |