Production Monitoring
Showing 20 of 20 projects
An open-source platform for debugging, evaluating, and monitoring LLM applications, RAG systems, and agentic workflows with tracing and automated evaluations.
An open-source platform for debugging, evaluating, and monitoring LLM applications, RAG systems, and agentic workflows.
A low-overhead sampling profiler for Python programs that works without restarting or modifying code, written in Rust.
Open-source framework for building full-stack AI-powered applications with unified APIs across JavaScript, Go, and Python.
Middleware that displays a speed badge for every HTML page in Ruby Rack apps, with optional flamegraphs and memory profiling.
A single-command tool for generating interactive flamegraphs to profile and visualize performance bottlenecks in Node.js applications.
Monitoring solution for Java and Java EE applications in QA and production environments.
A Ruby gem for collecting and reporting production code coverage, tracking line-of-code execution frequency.
A Rails plugin that sends email notifications when exceptions occur in your application.
A MySQL 5.5 fork maintained by Twitter with performance optimizations for NUMA, SSDs, and production monitoring.
A .NET library for safely refactoring critical code paths by comparing old and new implementations in production.
Embed dependency information into Rust binaries for vulnerability auditing in production.
Replaces the Rails default logger with Semantic Logger for structured, JSON-formatted logging in production.
An Elixir client for Prometheus.io, enabling metrics collection and monitoring in Elixir applications.
A Ruby agent that instruments applications to send performance data to Skylight for monitoring and profiling.
A lightweight binary that monitors application logs and uses GPT to automatically diagnose errors in real-time.
A Symfony bundle for monitoring production applications by sending metrics to StatsD with ready-to-use collectors.
Ruby agent for sending custom application metrics to the Instrumental monitoring platform with high reliability and non-blocking operation.
A high-performance AI agent runtime engine that transforms terminal AI tools into production services with persistent sessions.
Track runtime, wait time, and memory allocations per Fiber, method, or block in Crystal applications.
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