Developer-first error tracking and performance monitoring
- crash-reporting
- crash-reports
- error-monitoring
- monitoring
47,133 repositories indexed
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Developer-first error tracking and performance monitoring
Open-source cron job and background task monitoring service, written in Python & Django
🍦 Never use print() to debug again.
Easy & Flexible Alerting With ElasticSearch
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Investigate malicious Windows logon by visualizing and analyzing Windows event log
StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define.
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
A collection of scripts to set up MongoDB test environments and parse and visualize MongoDB log files.
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
Tool that extracts and provides metrics on your PostgreSQL database
Get a detailed, real-time view of your PostgreSQL database and system metrics
💽 Doku - Docker disk usage dashboard
Lightweight Claude Code statusLine: 5h/7d rate-limit usage, reset countdowns, model + context window, prompt-cache age — one line, 3 styles × 9 themes, daemon fast-mode
Raspberry Pi MQTT Monitor gathers system information and sends it to a MQTT server.
Performance visualisation tools
Open Source SIEM (Security Information and Event Management system).
OpenType vertical metrics reporting and font line spacing adjustment tool
PostgreSQL replication monitoring and failover daemon
Distributed tracing instrumentation for asyncio with zipkin
Produce watertight polygonal vector maps by tracing raster images
Graphite InfluxDB backend. InfluxDB storage finder / plugin for Graphite API.
System monitoring program for Raspberry pi single board computers written in Python 3.
Friendly Environment for Neural Networks (fenn) is a simple Python framework for building ML/DL workflows and LLM agents faster, with prebuilt trainers, agent templates, logging, configuration management, and much more.