AI-native Postgres observability: 45+ automated health checks, query and config tuning, agent-ready JSON and MCP output. Open source.
Results for “observability”
109 tools found
AI eval and observability platform: tracing, LLM and human scoring, quality gates. Used by Vercel, Notion and Replit.
Open-source observability database unifying metrics, logs and traces: SQL and PromQL, written in Rust, object-storage native.
Open-source AI gateway and LLM observability: one API for 100+ models, cost and latency tracking, prompt management.
Open-source fullstack monitoring: session replay, error tracking, logging and tracing in one self-hostable platform.
Observability platform for debugging production systems with distributed tracing, BubbleUp anomaly analysis, and AI-assisted querying.
Collaboration platform for AI teams to manage, test and monitor the prompts that power their LLM applications.
Open-source observability platform that unifies traces, metrics and logs in one OpenTelemetry-native tool, self-hosted or cloud.
AI-native observability platform that lets engineers debug production issues by asking questions in plain language instead of digging through logs.
A dashboard that tells you whether your AI feature is actually getting worse or better over time, built on top of a popular open-source testing library instead of asking you to guess from user complaints.
A dashboard that shows you exactly what your AI agent did, step by step, when it fails — every tool call, every sub-agent, every LLM response — instead of leaving you to guess from a wall of logs.
A control panel for getting AI models and agents from a developer's laptop into real production use — deployment, scaling, and governance — built to run on whichever cloud a company already uses instead of locking them into one.
A free, self-hosted dashboard that shows you exactly what your AI agents did, why they cost what they cost, and where they broke.
A quality-control inspector for AI agents — before your AI assistant goes live and starts talking to real customers, AgentX tests it, points out exactly where it messes up, and suggests a fix, instead of you finding out from an angry customer.
A dashcam for your AI coding assistant — after Claude Code or Codex finishes a session, Spotlight shows you exactly what it touched, what commands it ran, and flags anything risky, instead of you having to trust a summary or dig through logs yourself.
A self-installing mechanic for your app's bugs — instead of you wiring up monitoring tools and then manually digging through logs when something breaks, Superlog instruments your code itself, groups the mess into one clear incident, and shows up with a re
An AI assistant for the 3am "something's broken" moment — it automatically digs through your logs, metrics, and past incidents to figure out what's actually wrong, instead of an engineer manually piecing it together across a dozen tools.
A debugging tool for AI agents that lets you rewind a failed run to the exact step that broke, change one thing, and replay it — so you can actually prove a fix worked instead of just hoping it did.
A free, open-source tool that watches your Kubernetes cluster and tells you what broke and why, without adding any code to your apps.
An observability platform built entirely around the open OpenTelemetry standard, so your monitoring data isn't locked into one vendor.