Tags: #observability

An open-source LLM engineering platform for developing, monitoring, evaluating, and debugging AI applications.

An open-source platform for debugging, evaluating, and monitoring LLM applications, RAG systems, and agentic workflows from prototype to production.

Hive is a production-grade runtime harness for multi-AI agents, providing state management, fault recovery, observability, and human oversight for reliable business process automation.

Netdata provides real-time, AI-powered full-stack observability for infrastructure, offering instant insights with zero configuration.

A Python agent framework built by the Pydantic team to quickly and confidently develop production-grade Generative AI applications with a focus on type safety and observability.

An open-source LLMOps platform unifying LLM gateway, observability, evaluation, optimization, and experimentation for robust AI application development.

An open-source AI gateway enabling seamless integration with 100+ LLMs using any SDK, offering failover, load balancing, cost control, and end-to-end tracing to prevent vendor lock-in.

An AI-powered open-source real-time observability system for unified metrics, logs, alerting, and notification.

A high-performance, end-to-end observability data pipeline that empowers users to collect, transform, and route all their logs and metrics with significant cost reduction and enhanced control.

A Python framework for building reliable, observable, and production-ready Generative AI solutions and agents with minimal overhead.

Coze Loop is an open-source, full-lifecycle management platform for AI agent development, debugging, evaluation, and monitoring.

An open-source AI engineering platform for managing the complete lifecycle of AI applications, including agents, LLMs, and ML models, from debugging and evaluation to monitoring and optimization.

iii unifies diverse backend tools like API frameworks, task queues, and schedulers into a single engine with Function, Trigger, and Worker primitives, simplifying distributed backend development.

Trigger.dev is an open-source platform for building and deploying durable, long-running AI agents and workflows in TypeScript, offering features like retries, queues, and elastic scaling without serverless timeouts.

A distributed operating system for cloud-native application management, built on Kubernetes, offering full-stack IT operations and streamlined DevOps workflows across multi-cloud, datacenter, and edge environments.

An open-source platform for comprehensive AI/ML model observability, evaluation, and debugging.

A Python SDK and platform for comprehensive observability, monitoring, and cost management of AI agents and LLM applications.

An open-source Python library for evaluating, testing, and monitoring ML and LLM systems across experiments and production environments.

Accelerates the development and deployment of production-ready AI agents on Google Cloud with pre-built templates, CI/CD, evaluation, and observability.

A cloud-native data pipeline orchestrator designed for the development, production, and observation of data assets, featuring integrated lineage, observability, and a declarative programming model.

An open-source, developer-first LLMOps platform for streamlining prompt design, version management, observability, and collaboration in AI operations.

An open-source playbook offering end-to-end, code-first tutorials for building and deploying production-grade GenAI agents from prototype to enterprise scale.

Connects AI agents, IDEs, and applications to enterprise databases via an open-source Model Context Protocol (MCP) server, offering prebuilt tools and a framework for custom, secure data interaction.

An end-to-end AI Agent Engineering Platform providing an open-source TypeScript framework for building intelligent agents and a console for operations and observability.

A unified AI gateway and proxy for federating MCP, A2A, and REST/gRPC APIs, offering centralized discovery, governance, and observability for AI agents and tools.

A public repository of leaked and extracted system prompts from major AI models and agents, promoting transparency and observability into their hidden behaviors and biases.

A comprehensive platform for end-to-end testing, simulation, evaluation, and monitoring of LLM-powered agents.

Prefect is a Python-based workflow orchestration framework designed to build resilient and dynamic data pipelines, automating complex data processes with features like scheduling, caching, and retries.

An open-source AI agent for investigating production incidents and finding root causes across any stack.

SigNoz is an open-source, OpenTelemetry-native observability platform that unifies logs, traces, and metrics to monitor applications and troubleshoot issues efficiently.

Quickwit is a cloud-native, open-source search engine designed for high-performance observability data (logs, traces, metrics) with sub-second queries on cloud storage.

An open-source, cost-effective observability platform for logs, metrics, traces, and RUM, offering significant storage cost savings and high performance.