Self-Hosted Session Replay and Heatmaps

Umami is a self-hosted, privacy-focused web analytics platform designed to provide full control over infrastructure and user data. It captures website traffic and visitor behavior through anonymous tracking methods that avoid cookies, browser fingerprinting, and the storage of personally identifiable information. The platform distinguishes itself through a comprehensive suite of behavioral analysis tools, including session replays, heatmaps, and cohort-based retention reporting. It features a multi-tenant architecture that allows teams to manage multiple websites within a single, collaborative dashboard, supported by granular role-based access controls and the ability to share specific insights via public links. Beyond core traffic monitoring, the system includes a robust event tracking framework for capturing custom user interactions, conversion funnels, and marketing campaign attribution. It also provides diagnostic capabilities for web performance, allowing users to track core web vitals and troubleshoot data collection through detailed session logs and visitor activity searches. The software supports flexible deployment strategies, including containerized installations and source-code-based setups, and can be integrated into various environments via a standard API or pre-built plugins.

OpenReplay is a session replay platform and frontend debugging suite designed to record and play back user browser sessions. It functions as a user behavior monitoring system that captures interaction patterns and technical metadata to identify conversion issues and revenue loss. The platform is distinguished by its self-hosted infrastructure model, allowing the recording and analytics pipeline to be deployed on private servers for full control over data residency. It also includes a browser co-browsing tool for real-time screen sharing and direct communication to provide immediate technical support. The system provides comprehensive observability by correlating session recordings with network requests, console logs, and application state changes. It features tools for automated bug report capture, backend log synchronization, and data privacy management to obscure sensitive information before it reaches the server. The software allows for the upload of JavaScript sourcemaps to resolve minified code during the debugging process.

Rybbit is an open-source, self-hosted web analytics platform designed for comprehensive user behavior tracking and product engagement analysis. It provides a complete suite for monitoring visitor interactions, conversion funnels, and site performance, allowing organizations to maintain full ownership of their data and infrastructure. The platform distinguishes itself through a strong emphasis on privacy-compliant data collection and visual session replay capabilities. It supports advanced traffic routing through custom domains to bypass ad blockers and includes configurable masking tools to protect sensitive user information during session recordings. By linking anonymous activity to persistent user profiles, it enables accurate cross-device analysis and detailed cohort segmentation. Beyond core tracking, the system offers extensive tools for event-driven data pipelines, including custom event logging, e-commerce transaction monitoring, and automated error tracking. It features robust administrative controls, such as role-based access management, team collaboration workflows, and granular data retention policies. The platform is built for flexible deployment, utilizing containerized orchestration to simplify maintenance and updates in private server environments.

OpenPanel is a self-hosted product analytics platform designed for tracking user behavior and visualizing product metrics on private infrastructure. It provides a comprehensive system for collecting events across web, mobile, and server environments while ensuring complete ownership of data. The platform distinguishes itself through a privacy-first approach, utilizing cookieless event tracking and regional data residency to simplify regulatory compliance. It integrates large language models via the Model Context Protocol, enabling users to query behavioral data and analyze trends using natural language. The system covers a broad range of analytical capabilities, including behavioral analysis with conversion funnels, retention cohorts, and session replays. It also features financial monitoring for recurring revenue and lifetime value, alongside visual report builders for creating custom dashboards without SQL. The entire stack is Dockerized for streamlined deployment on private servers, including support for automated system updates and reverse proxy integration.

PostHog is a comprehensive product analytics and feature management platform designed to capture, process, and visualize user behavior data. It provides a unified suite for tracking application events, managing feature rollouts, and monitoring system health through session recordings and error tracking. By leveraging a columnar-storage-optimized architecture, the platform enables high-performance aggregation and filtering across massive event datasets. What distinguishes PostHog is its integrated approach to data pipelines and application control. It features a robust event ingestion system that supports custom transformation logic through sandboxed scripting, allowing for real-time data manipulation before storage. The platform also includes a sophisticated feature flagging service that supports multivariate testing and dynamic configuration across web and mobile environments, alongside automated anomaly detection and alerting engines that monitor data streams for performance shifts. The platform covers a broad observability surface, including application performance monitoring, qualitative user feedback collection via targeted surveys, and detailed activity auditing. It provides extensive administrative controls, such as granular access management and secure proxy infrastructure, to ensure reliable data collection and compliance. Developers can interact with the platform through a documented API that supports authenticated access, rate limiting, and efficient result pagination.

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 stack traces back to original code. Its broader capabilities include full-stack instrumentation for various languages and serverless environments, automated event pattern clustering, and end-to-end request tracking. The system also features SQL-based telemetry querying, multi-channel alerting, and unified visualization dashboards. The software can be deployed as a self-hosted instance using Docker.

This project is a JavaScript error tracking SDK and application performance monitoring tool. It captures runtime exceptions and crashes across web browsers, server-side environments, and edge computing contexts. The SDK includes a session replay tool that records visual user interactions to reproduce bugs. To ensure telemetry delivery, it provides a tunneling proxy that routes monitoring data through custom endpoints to bypass browser-level ad blockers. The toolkit also features a source map processor that translates minified stack traces back into original source code. Additionally, it covers structured application log capture and performance tracing to identify system bottlenecks via execution spans.