Overview

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Why you need LLM observability?

LLM observability is the comprehensive process of monitoring, evaluating, and gaining insights into the performance and activities of Large Language Models in real-time. LLM observability is crucial for several reasons:

1. Ensuring Accuracy and Relevance: LLMs can produce hallucinations, so observability helps detect and fix these issues.
2. Maintaining Performance: Tracking response times, throughput, and error rates ensures optimal LLM performance.
3. Enhancing Reliability: Monitoring helps prevent and quickly resolve downtime from provider outages, rate limits, or delayed alerts.
4. Optimizing Costs: Monitoring identifies cost-effective models and leverages caching to reduce expenses.

Keywords AI provides an Async Logging API that allows you to log your LLM requests and responses asynchronously, which offers complete observability of your LLM applications and won’t disrupt your application’s performance.

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Benefits of async logging:

• Monitor your LLM performance with 0 latency impact.
• Operates outside the critical path of your application, ensuring no disruptions.
• Gain comprehensive observability of your LLM applications.