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Introducing Brokle: Open-Source LLM Observability

Today we're excited to announce Brokle, the open-source platform for LLM observability. Learn why we built it and how it can help your team ship better AI applications.

HHashir
November 15, 20253 min read

Why We Built Brokle

As AI applications become increasingly complex, teams need better tools to understand what's happening inside their LLM pipelines. Traditional monitoring falls short — you can't debug a hallucinating model with HTTP status codes alone.

Brokle was born from our own frustration building production AI systems. We needed a way to trace every interaction, evaluate output quality, manage prompt iterations, and understand costs — all in one place.

What Brokle Offers

End-to-End Tracing

Built on OpenTelemetry, Brokle captures every step of your LLM pipeline. From the initial user query through retrieval, augmentation, and generation — every operation is traced with full context.

from brokle import Brokle

brokle = Brokle()

# Automatic instrumentation
with brokle.trace("chat-completion"):
    response = openai.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": "Hello!"}]
    )

Quality Evaluation

Automated evaluation pipelines help you catch quality issues before your users do. Use LLM-as-judge, custom evaluators, or human feedback to score every response.

Prompt Management

Version, test, and deploy prompts with confidence. Brokle tracks which prompt versions are in production and how they perform over time.

Cost Analytics

Understand exactly where your AI budget goes. Brokle breaks down costs by model, provider, feature, and user — helping you optimize spend without sacrificing quality.

Open Source First

Brokle is fully open source under the MIT license. You can self-host it on your own infrastructure, contributing to and benefiting from a growing community of AI engineers.

We believe observability tooling should be transparent, extensible, and owned by the teams that use it.

Getting Started

Getting started with Brokle takes just a few minutes:

  1. Self-host with Docker Compose or deploy to your Kubernetes cluster
  2. Install the SDK for Python or JavaScript
  3. Instrument your app with a few lines of code
  4. Explore your traces in the Brokle dashboard

Check out our quickstart guide to get up and running.

What's Next

This is just the beginning. We're working on expanded SDK support, deeper integrations with popular frameworks, and advanced analytics features. Follow our progress on GitHub and join the community.

We can't wait to see what you build with Brokle.