Logfire

Superlog is an open-core, self-hosted observability workspace for OpenTelemetry data, developed by Superlog Labs. It ingests traces, logs, and metrics, groups noisy signals into incidents, and provides a local-first interface for investigating production systems. The open-source community edition includes a web app and API, an OTLP intake proxy, worker processes for incident grouping and background jobs, a Postgres schema, ClickHouse-backed telemetry queries, and pluggable agent-runner interfaces with a default runner that records a local incident summary. The repository is licensed under Apache License 2.0; a hosted Superlog Cloud edition is also available with a free tier, pay-as-you-go plan, and monthly credit packs.

Langfuse is an open-source LLM engineering platform for developing, monitoring, evaluating, and debugging AI applications. It ingests traces for LLM calls and related operations such as retrieval, embeddings, and agent actions, with integrations including OpenTelemetry, LangChain, the OpenAI SDK, LiteLLM, and other LLM frameworks. Its features include prompt management with version control and collaborative iteration, LLM-as-a-judge and code-based evaluations, user feedback and manual labeling, datasets for test sets and benchmarks, trace replay and debugging, metrics, and a playground for testing prompts and model configurations. Langfuse exposes APIs and typed Python and JavaScript/TypeScript SDKs for custom LLMOps workflows. It is available as a managed cloud service or for self-hosting with Docker Compose, virtual machines, Kubernetes via Helm, or Terraform templates.

Loop is Braintrust’s AI agent for investigating and improving production agents. It queries trace data with SQL, examines representative failures, and turns findings into evaluation datasets for regression testing. Loop can also generate prompts, scorers, and datasets for optimization, as well as task-specific annotation interfaces for reviewing trace data.

LangSmith is an AI-agent observability and evaluation platform from LangChain. It captures agent traces, including tool calls, sub-agent calls, and retrieved context, so teams can inspect agent runs, debug behavior, and use traces as evidence in feedback and memory workflows. The LangChain site describes step-by-step tracing, trace-based dataset creation, evaluation of agent steps, complex-trace querying, online evaluations, dashboards, and alerts for production agent runs.

Langfuse CLI is a command-line tool for accessing Langfuse APIs from agent workflows, scripts, and CI/CD. It exposes Langfuse data and operations including traces, scores, datasets, and experiment runs, enabling coding agents and developers to investigate production behavior and evaluation results from the terminal.