# Observability

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.

<figure><img src="https://692214342-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-Mc71sWdWMqp1e_rsTZE-129938315%2Fuploads%2Fgit-blob-59450a2cad62520b114fab2b9b31721f3c00fd86%2Fobservability_ai_chat_trace.png?alt=media" alt=""><figcaption><p>An observability trace for an AI chat completion in the Spice portal.</p></figcaption></figure>