# Observability

Open-source observability platform for metrics, logs, and traces visualization.

Grafana is the leading open-source platform for monitoring and observability visualization. It connects to virtually any data source — Prometheus, Elasticsearch, InfluxDB, PostgreSQL, CloudWatch, Datadog, and 150+ others — to create beautiful, interactive dashboards. Used by millions of users at companies like Bloomberg, JPMorgan, eBay, and PayPal. Grafana Cloud offers a fully managed experience with generous free tier. The CNCF ecosystem standard for metrics visualization.

Cloud-scale monitoring, security, and analytics platform for modern infrastructure.

Datadog is a cloud observability and security platform that unifies metrics, traces, logs, RUM, synthetics, APM, and security signals. Current pricing pages list 1,000+ integrations for Infrastructure Monitoring, with Pro from $15/host/month and Enterprise from $23/host/month when billed annually.

Open-source product analytics, session replay, and feature flags

PostHog is an open-source product and data tools platform for analytics, session replay, feature flags, experiments, surveys, error tracking, web analytics, data warehouse, CDP and LLM observability workflows. It suits developer-led teams that want one integrated product OS instead of many separate tools.

Open-source LLM observability and evaluation

Phoenix by Arize is an open-source AI observability platform for tracing, evaluating, and debugging LLM applications. It captures prompt-response pairs, retrieval context, agent tool calls, and latency data through OpenTelemetry-based instrumentation. Provides experiment tracking, dataset management, and evaluation frameworks for systematically improving AI application quality. 10K+ GitHub stars.

Open-source LLM engineering platform for observability

Langfuse is an open-source LLM engineering platform with 29K+ GitHub stars for tracing, evaluating, and monitoring AI applications. Acquired by ClickHouse, it provides detailed traces of LLM calls, prompt management with versioning, dataset-based evaluation, user feedback collection, and cost tracking. Framework-agnostic with native integrations for LangChain, LlamaIndex, OpenAI SDK, and Vercel AI SDK. Offers both self-hosted deployment and a managed cloud service.

LLM evaluation and prompt engineering platform

Braintrust is an AI observability and evaluation platform for tracing LLM applications, building datasets, running prompt/model experiments, scoring outputs and turning production feedback into regression tests. It fits teams that need repeatable quality gates for AI releases rather than one-off prompt demos.

LSP-powered semantic coding agent via MCP

Serena is a free, open-source coding agent toolkit that provides IDE-like semantic code retrieval and editing capabilities to any LLM via the Model Context Protocol (MCP). Built on Language Server Protocol (LSP) integration, it enables symbol-level navigation, cross-file refactoring, and relational code understanding across Python, TypeScript, Go, Rust, Java, PHP, and more — without requiring file-level reads or text-based search.

AI-powered Kubernetes diagnostics in plain English

K8sGPT is a CNCF Sandbox project that scans Kubernetes clusters, diagnoses issues, and explains problems in plain English with actionable remediation steps. It codifies SRE expertise into built-in analyzers for Pods, Services, Deployments, Ingress, PVCs, CronJobs, and more. K8sGPT connects to AI backends including OpenAI, Azure OpenAI, Google Gemini, Amazon Bedrock, Cohere, and local models via Ollama, with data anonymization to protect sensitive cluster information.

AI gateway with observability, routing, and guardrails

Portkey is an AI gateway and observability platform providing a unified API for 200+ LLM providers with intelligent routing, caching, rate limiting, and guardrails. Route requests across OpenAI, Anthropic, Google, and more with automatic failover, load balancing, and cost optimization. Features request logging, prompt management, evaluation tools, and real-time monitoring. The open-source gateway can be self-hosted; Portkey Cloud adds managed observability and team features.

SigNoz is an OpenTelemetry-native observability platform for collecting and correlating logs, metrics, and traces. Teams can self-host it or use SigNoz Cloud, with dashboards, alerting, query workflows, and enterprise controls for cloud-native and AI application telemetry.

ML experiment tracking and model monitoring

Weights & Biases is an AI developer platform for experiment tracking, artifact and model lineage, model monitoring, and Weave-based LLM evaluation. It helps teams log runs, compare metrics, manage datasets and model artifacts, and collaborate through dashboards, reports, alerts, SSO/RBAC controls, and hosted or self-managed deployment options.

Distributed search and analytics engine for all types of data.

Elasticsearch is the world's most popular open-source search and analytics engine, powering search experiences for companies like Wikipedia, GitHub, Netflix, and Uber. Built on Apache Lucene, it provides near-real-time search, structured and unstructured data analysis, and machine learning capabilities. Part of the Elastic Stack (ELK), it handles log analytics, application search, security analytics, and observability at scale. Supports vector search for AI/RAG applications.

Open-source LLM observability through a single-line proxy

Helicone is an open-source LLM observability and AI gateway platform with proxy-based request logging, cost tracking, latency monitoring, caching, rate limits, user analytics, prompt tools, and HQL. It supports OpenAI, Anthropic, Azure, LiteLLM, Anyscale, Together AI, and OpenRouter integrations, and now presents itself as part of Mintlify while continuing managed and self-hosted gateway/observability workflows.

AI-powered API testing with traffic recording

Keploy is an open-source AI-powered testing platform that generates API, integration, and unit tests by recording real network traffic via eBPF. It captures API calls, database queries, and streaming events, then replays them as deterministic tests with auto-generated mocks — no code changes needed. Works across any language or framework with CI/CD pipeline integration and popular testing framework support including JUnit, PyTest, Jest, and Go-Test.

Open-source platform for the complete machine learning lifecycle.

MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. Covers experiment tracking, model packaging, model registry, and deployment. Created by Databricks and now a Linux Foundation project. Integrates with TensorFlow, PyTorch, scikit-learn, Hugging Face, and all major ML frameworks.

OpenTelemetry-native observability with AI tracing, logs, traces, metrics, and session replay — self-hosted in 90 seconds.

Traceway is an open-source, OpenTelemetry-native observability platform that combines logs, traces, metrics, exceptions, session replay, and AI tracing in a single self-hosted system. MIT licensed with no open-core restrictions, it deploys in 90 seconds via Docker Compose and accepts OTLP/HTTP from any OTel SDK without a Collector or per-language vendor SDK.

Git-native AI agent session capture and reasoning traceability

Checkpoints by Entire captures the full reasoning context behind AI-generated code directly in Git. Entire records transcripts, prompts, files touched, token usage, and tool calls alongside every commit. Session metadata lives on a separate branch keeping your history clean, with rewind capabilities to restore any previous agent checkpoint when things go sideways.

HyperDX is the ClickStack UI for ClickHouse-backed observability. It provides a frontend for exploring logs, traces, metrics, session replay, dashboards, and alerts, with an OpenTelemetry-centered deployment path for teams that want a self-hosted or ClickHouse-aligned observability stack.

Full-stack observability with AI-powered monitoring

New Relic is a full-stack observability platform combining APM, infrastructure monitoring, logs, traces, browser/mobile monitoring, synthetics, and AIOps. Current public copy highlights 50+ capabilities, 100 GB/month free data ingest, one free full platform user, unlimited basic users, and 800+ pre-built integrations.

LLM evaluation and tracking with RAG triad metrics

TruLens is an open-source framework for evaluating and tracking LLM experiments with feedback functions, RAG triad metrics (answer relevance, context relevance, groundedness), and Honest/Harmless/Helpful evaluations. Features a unified Metric API for systematic evaluation of RAG pipelines and AI agents. 3,200+ GitHub stars, MIT licensed. Snowflake partnership adds enterprise integration. Supports LangChain, LlamaIndex, and custom LLM applications.

Better Stack is a hosted observability and incident-management platform that combines uptime monitoring, on-call workflows, status pages, logs, traces, metrics, error tracking, session replay, and an AI SRE interface. It is aimed at teams that want one SaaS control plane for telemetry and incident response.

Evaluation-first LLM and agent observability

Confident AI is an evaluation-first observability platform that scores every trace and span with 50+ metrics, alerting on quality drops in LLM and agent applications. It goes beyond traditional APM by treating evaluation as core observability, providing actionable insights that help teams understand not just whether their AI applications are running but whether they are producing correct and useful outputs.

Open-source ML and LLM monitoring with 100+ metrics

Evidently AI is an open-source platform with 100+ pre-built metrics for monitoring data quality, model performance, and data drift in AI/ML pipelines. Available under Apache 2.0 with a cloud version, it helps teams detect when production data shifts away from training distributions, LLM output quality degrades, or feature pipelines introduce anomalies that silently degrade model accuracy.

Full-stack observability platform with OpenTelemetry-friendly telemetry, LLM observability, and AI SRE workflows.

Middleware is a full-stack observability platform for infrastructure, APM, logs, metrics, traces, RUM, synthetics, browser testing, LLM observability, and AI SRE workflows. It targets teams that want OpenTelemetry-friendly telemetry, faster incident correlation, and a 14-day free trial before Pay As You Go or Enterprise observability commitments and rollout planning.

CNCF Sandbox Kubernetes alert enrichment and automation platform

Robusta is a CNCF Sandbox project that enriches Kubernetes alerts with diagnostic context and automates remediation workflows. It intercepts Prometheus alerts, attaches relevant logs, pod status, resource metrics, and troubleshooting suggestions before delivering them to Slack, Teams, or PagerDuty. Supports custom playbooks for automated incident response and AI-powered root cause analysis.

LLM observability and evaluation by Weights & Biases

W&B Weave is the LLM observability and evaluation toolkit from Weights & Biases. It provides automatic tracing of LLM calls with full input/output logging, cost and latency tracking, evaluation pipelines with custom scorers, and a trace explorer for debugging multi-step agent workflows. Integrates with OpenAI, Anthropic, LangChain, and CrewAI via simple Python/TypeScript decorators.

Open-source LLMOps platform for prompt management and evaluation

Agenta is an open-source LLMOps platform that combines prompt engineering playgrounds, prompt version management, LLM evaluation, and observability in a unified interface. It supports 50+ LLM models with side-by-side prompt comparison, A/B testing, human evaluation workflows, and OpenTelemetry-native tracing. Self-hostable with 4,000+ GitHub stars.

AI-driven log analysis with zero false positives

Dash0 is an AI-driven observability platform focused on log analysis that auto-structures unstructured logs, provides instant alerting with zero false positives, and delivers full-stack tracing capabilities. It uses AI to transform raw log data into structured, searchable events without requiring manual parsing configuration, making log-based debugging significantly faster for engineering teams.

Open-source Kubernetes security platform for risk analysis and compliance

Kubescape is a CNCF-backed open-source Kubernetes security platform that scans clusters, manifests, and container images for vulnerabilities, misconfigurations, and compliance violations. It checks against NSA-CISA, MITRE ATT&CK, and CIS benchmarks, integrates into CI/CD pipelines, and provides runtime threat detection via eBPF. Supports SBOM generation and vulnerability scanning. Used by ARMO with growing enterprise adoption in cloud-native security.

Open-source observability for AI agents

Laminar is an open-source observability platform for AI agents providing tracing, evaluation, and analytics for LLM applications. It integrates with Vercel AI SDK, LangChain, OpenAI, and Anthropic with a single line of code. Features include OpenTelemetry-native SDKs, an extensible evaluation framework with CI/CD support, SQL access to traces and metrics, and a visual debugging timeline for agent reasoning and actions.

LLM evaluation and tracing by Comet

Opik is an open-source LLM evaluation and tracing platform by Comet ML for debugging, testing, and monitoring AI applications. Provides detailed traces of LLM calls with latency, token usage, and cost tracking. Features automated evaluation with built-in and custom metrics, dataset management for regression testing, and production monitoring dashboards. Integrates with the broader Comet ML experiment tracking ecosystem. Available as both self-hosted open-source and managed cloud service.

Observability platform purpose-built for Python and Pydantic AI apps

Pydantic Logfire is an observability platform built by the Pydantic team specifically for Python AI applications. It provides structured logging, distributed tracing, and metrics with native understanding of Pydantic models, FastAPI, and AI framework data types. Auto-instruments OpenAI, Anthropic, LangChain, and other LLM providers. Built on OpenTelemetry for vendor-neutral data export. Offers a managed cloud dashboard with a generous free tier for development and small-scale production use.

Observability and lifecycle management for AI agents

AgentOps is an observability platform for monitoring, debugging, and managing AI agents. It provides session replay, event timelines, tool-call and LLM tracing, cost tracking, and dashboards for multi-agent workflows. Integrations span OpenAI, CrewAI, AutoGen, LangChain, LangGraph, LlamaIndex, Google ADK, OpenAI Agents, xAI, and 400+ LLMs/frameworks.

AI observability with security posture management

Coralogix uses AI to provide actionable insights across logs and traces with a dedicated AI-SPM dashboard for tracking prompt injections and data leaks in AI applications. Its pay-per-use model with no upfront fees integrates security posture management directly into the observability stack, making it uniquely positioned for teams running both traditional and AI-powered production workloads.

Self-evolution engine for AI agents with auditable updates

Evolver is an open-source self-evolution engine for AI agents that turns run logs into auditable, reviewable updates via its Genome Evolution Protocol. Instead of ad hoc prompt tweaking, teams collect traces and Evolver proposes versioned diffs to prompts, tools and workflows that engineers can approve, reject or roll back like code.

Modern task queue and workflow orchestration built on PostgreSQL

Hatchet is an open-source task queue and workflow orchestration platform designed as a modern alternative to Celery and BullMQ. Built on PostgreSQL for durability, it handles background jobs, AI agent workflows, RAG pipelines, and GPU task scheduling with TypeScript and Python SDKs. YC W24 batch with 7,400+ GitHub stars, MIT licensed. Supports fan-out, rate limiting, retries, and real-time observability through a web dashboard.

LLM application observability and evaluation platform

LangSmith is LangChain's platform for debugging, testing, evaluating, and monitoring LLM applications in production. Provides detailed tracing of every step in LLM chains and agent workflows, dataset management for regression testing, prompt versioning, and automated evaluation with custom metrics. Features an annotation queue for human feedback, online monitoring dashboards, and integration with LangChain, LangGraph, and any LLM framework via the Python/JS SDK. Essential for production LLM ops.

Multi-agent simulation and LLM evaluation platform

Maxim AI is an evaluation and monitoring platform for LLM applications with multi-agent simulation capabilities. Features automated test generation from production traces, custom evaluation metrics, regression detection, and real-time monitoring dashboards. Supports simulating multi-turn conversations for testing chatbots and agents at scale. Provides prompt versioning, A/B testing, and integration with CI/CD pipelines for continuous quality assurance of AI outputs across deployment cycles.

Data and AI observability for enterprise teams

Monte Carlo is the leading data and AI observability platform using ML to monitor pipelines, warehouses, and lakes for quality issues. It detects freshness delays, volume anomalies, schema changes, and distribution shifts before they impact analytics. With 500+ deployments at Nasdaq, Honeywell, and Roche, it provides automated root cause analysis, field-level lineage, and incident management. Available on AWS and Azure Marketplace.

OpenTelemetry-native LLM observability instrumentation

OpenLLMetry by Traceloop is an open-source instrumentation library with 7,000+ GitHub stars that adds OpenTelemetry-native tracing to LLM and AI agent applications. It captures detailed traces of model calls including latency, token usage, costs, and error rates, exporting data to any OpenTelemetry-compatible backend like Grafana, Datadog, or Jaeger for vendor-neutral AI observability.

AI agent testing and LLM evaluation platform

LangWatch is an AI agent testing, LLM evaluation, and observability platform for production AI teams. It combines traces, evaluations, scenario simulations, guardrails, prompt management, and Optimization Studio/DSPy workflows, with cloud and self-managed options for teams that need release-quality feedback loops.

AI-powered SRE agent for Kubernetes troubleshooting

Metoro is an AI SRE platform for Kubernetes that combines observability with autonomous troubleshooting. Its Guardian agent monitors cluster health, correlates metrics, logs, and traces to identify root causes, and suggests remediation actions. Features an MCP server for integration with AI coding agents and natural language querying of infrastructure state.

Framework for evaluating LLM and agent performance

OpenAI Evals is an open-source framework and benchmark registry for evaluating LLM performance on custom tasks. It provides infrastructure for writing evaluation prompts, running them against models, and recording results in a structured format for comparison. The hosted Evals API on the OpenAI platform adds managed run tracking, dataset management, and programmatic access to evaluation pipelines. With 17,700+ GitHub stars, it serves as a foundation for systematic LLM quality measurement.

All-in-one open-source observability — logs, metrics, traces, RUM

OpenObserve is an open-source observability platform that unifies logs, metrics, traces, and real user monitoring in a single binary. It claims 140x lower storage costs than Elasticsearch through columnar storage and compression, with native OpenTelemetry support, a built-in query UI, dashboards, and alerts. Designed for AI and cloud-native workloads at petabyte scale. Over 15,000 GitHub stars.

Prompt registry, observability, and evaluation workflows for LLM applications.

PromptLayer is a prompt management, observability, and evaluation platform for LLM applications. Teams use its Prompt Registry, visual editor, request logs, Tables, evaluations, Tool Registry, and Skill Collections to version prompts, replay requests, compare variants, run datasets, and ship prompt changes without redeploying code. Pricing starts with Free $0 for 5 users and 2.5K requests/month, Pro $49/month, Team $500/month, and Enterprise custom.

See where your AI coding tokens actually go

Open-source TUI dashboard and CLI that shows where your AI coding tokens actually go, broken down by task type, tool, model, MCP server, and project. CodeBurn reads local session data directly from Claude Code, Codex, Cursor, OpenCode, Pi, and GitHub Copilot — no wrapper, proxy, or API keys — and layers on one-shot success rates so you can see whether the AI nails work first try or burns budget on edit/test/fix retries. Ships with a macOS menu bar widget and CSV/JSON export.

Agentic application security from prompt to cloud

Cycode is an AI-native application security platform that converges AST, SSCS, and ASPM into a single solution with the Maestro AI orchestrator managing multi-agent security workflows. It provides native SAST, SCA, secrets detection, IaC scanning, and container security alongside ConnectorX integration with 100+ third-party tools. Cycode's AI Exploitability Agent reduces false positives by 94%, and the Context Intelligence Graph maps risk across code, pipelines, and runtime environments.

Postgres sync engine for local-first and real-time applications

ElectricSQL is a sync engine that keeps local application state synchronized with PostgreSQL in real-time. It enables local-first architectures where apps work offline with instant responsiveness, syncing data bidirectionally when connectivity is available. Supports partial replication with shape-based subscriptions to sync only relevant data subsets to each client.