Sessions enable tracking and organizing related traces across multi-turn conversations with your AI application. When building conversational AI, maintaining context between interactions is critical - Sessions make this possible from an observability perspective.
With Sessions in Phoenix, you can:
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Track the entire history of a conversation in a single thread
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View conversations in a chatbot-like UI showing inputs and outputs of each turn
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Search through sessions to find specific interactions
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Track token usage and latency per conversation
This feature is particularly valuable for applications where context builds over time, like chatbots, virtual assistants, or any other multi-turn interaction. By tagging spans with a consistent session ID, you create a connected view that reveals how your application performs across an entire user journey.