## Observability in Spice

Observability in Spice enables task tracking and performance monitoring through a built-in distributed tracing system that can [export to Zipkin](https://docs.spice.ai/features/observability/zipkin) or be viewed via the [`runtime.task_history`](https://docs.spice.ai/features/observability/task-history) SQL table.

Spice records detailed information about runtime operations through trace IDs, timings, and labels - from SQL queries to AI completions. This task history system helps operators monitor performance, debug issues, and understand system behavior across individual requests and overall patterns.

### Use-Cases

#### Debugging and Troubleshooting

- Trace AI chat completion steps and tool interactions to identify why a request isn't responding as expected

- Investigate failed queries and other task errors

#### Performance Analysis

- Track SQL query/tool use execution times

- Identify slow-running tasks

#### Usage Analytics

- Track usage patterns by protocol and dataset

- Understand how AI models are using tools to retrieve data from the datasets available to them

### Portal Interface

The Spice platform provides a built-in UI for visualizing the observability traces that Spice OSS generates.

An observability trace for an AI chat completion in the Spice portal.

Last updated 3 months ago.