4 best LLM gateways for observability: tracing, cost attribution, and debuggability

Braintrust Gateway offers a comprehensive solution for managing and observing large language model (LLM) requests by unifying access to multiple providers such as OpenAI, Anthropic, Google, and AWS, while integrating advanced observability features. It provides a unique capability to capture detailed trace data, including token usage, latency, and costs, without the need for additional instrumentation, facilitating easier debugging and cost analysis. The platform enables developers to use captured traces for evaluation, leveraging features like a playground for testing prompt changes and an AI assistant called Loop to identify quality patterns and cost anomalies. Braintrust also supports integration with OpenTelemetry, allowing seamless incorporation into existing monitoring setups, and offers features like GitHub Actions to prevent regressions by blocking merges that fail quality evaluations. This makes it particularly useful for teams aiming to trace production LLM behavior, debug efficiently, and ensure high-quality deployments, while providing custom cost attribution and the ability to test modifications against real production data directly within the platform.

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