Harbor vs Langfuse

Langfuse offers observability for LLM apps, not the orchestration of services

Side by side

What it is: Harbor:Harbor is a CLI tool that orchestrates containerized LLM backends, frontends and services with a single command.; Langfuse:Langfuse is an open-source platform for tracing, evaluating and monitoring LLM applications and AI agents.
Best for: Harbor:One-command local LLM stack orchestration; Langfuse:LLM observability & analytics
Who it’s for: Harbor:Developers who want to run local LLM stacks quickly without manual Docker setup; Langfuse:Developers building, debugging and scaling LLM-based apps and agents.
Pricing: Harbor:Open source; Langfuse:Freemium
Plans: Harbor:—; Langfuse:Hobby Free · Core $29 per month · Pro $199 per month · Enterprise $2499 per month
Open source: Harbor:Yes, 3,231 GitHub stars; Langfuse:Yes, 35,097 GitHub stars
Works with: Harbor:Ollama, llama.cpp, vLLM, Open WebUI, SearXNG, Speaches, ComfyUI; Langfuse:Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift
DevHunt upvotes: Harbor:1; Langfuse:89
Launched on DevHunt: Harbor:May 2025; Langfuse:Jan 2023

Single-command stack launch. Run multiple LLM backends, frontends and services together with `harbor up`.
Containerized LLM toolkit. Provides Docker-based backends like Ollama, llama.cpp, vLLM.
Convenience utilities. CLI helpers for model management, config, debugging, URLs and tunnels.
Optimizing proxy & benchmarking. Built-in proxy for performance tuning and tools to benchmark models.
Service CLIs via Docker. Run service CLIs without installing them locally, using Docker containers.
Shared caches & profiles. Caches models across services and supports config profiles and history.

Hierarchical Traces. Capture every LLM call, tool invocation and retrieval step with filters for user, session, cost and latency.
Prompt Management. Version, fetch, release and cache prompts separately from code with one-click deployments.
Evaluation Engine. Run LLM-as-judge, heuristic or human-review evaluations on production data or experiments.
Experiments & Datasets. Define test cases, run experiments and create golden datasets for continuous improvement.
Dashboards & Alerts. Monitor cost, latency and quality via custom dashboards and automated alerts.
Human Annotation. Collaborative human-in-the-loop workflows with annotation queues.
Extensive Integrations. Supports Python, TypeScript, Go, Java, .NET, Ruby, PHP, Swift and 100+ agent frameworks and model providers.
Self-hosted & Cloud Options. Available as hosted SaaS or self-hosted under MIT license.

Based on each tool's website and DevHunt data. Details may change; check the official sites.