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Monitoring Your AI Application

Effective monitoring is crucial for maintaining and optimizing your AI application. This guide will walk you through the key aspects of monitoring, including using the dashboard, understanding important metrics, and accessing logs.

Monitoring is closely related to evaluation and continuous improvement.

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Dashboard Overview

The dashboard provides a comprehensive view of your AI application’s performance and usage.

Each card can be filtered.

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Volume Metrics

Track the usage and activity of your AI application over time:

• Number of conversation threads
• Agent runs
• Text generations
• Token usage
• User feedback submissions

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Latency Metrics

Monitor the speed and responsiveness of your AI:

• Time to first token: How quickly your AI starts generating a response
• Token throughput: The rate at which tokens are generated

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AI Performance Evaluations

Evaluate the quality and effectiveness of your AI:

• Set up AI evaluations in production to continuously monitor performance
• For detailed information on setting up evaluations, refer to our evaluation guide

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LLM Cost Metrics

Track the cost of your LLM Provider APIs over time.

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Accessing Logs

Detailed logs provide valuable insights for troubleshooting and optimization:

1. In the sidebar, navigate to the “Logs” section
2. Use filters to narrow down logs by date, conversation ID, or AI eval results
3. Review log entries for specific conversations or errors to identify root causes