> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlayer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Glossary

> Definitions of terms used in Openlayer

Here, we define some terms used in Openlayer.

## Workspace

When you [create an account](https://app.openlayer.com/), you are given a workspace. A workspace is
your **home in Openlayer**, where all your projects live and where your team collaborates.

## Project

A project lives inside a workspace. It represents **a problem you are tackling with AI/ML**
and houses all the models, data, and tests related to it. You can [create multiple projects](/workspace-and-projects/creating-and-loading-projects)
in your workspace, and your team members have access to all of them.

A project has two modes: **development** and **monitoring**.

### Development mode

The development mode of a project hosts your efforts during **model development**.
It is where you push models and datasets for testing and keep track
of their versions. Refer to the
[Development overview](/development/overview) for a deep dive into the process followed in development.

### Monitoring mode

The monitoring mode of a project allows you to monitor a **model deployed in production**.
It receives production data and evaluates it with the tests you defined.
In the monitoring mode, you can also set up alerts to get notified when tests
start failing. Refer to the
[Monitoring overview](/monitoring/overview) for details.

## Tests

Tests materialize **expectations around models and data** and exist to measure different
aspects of quality and performance.

In development, they ensure you are systematically making progress and avoiding regressions in your quest toward high-quality models.
In monitoring, they help measure the model's health in production and trigger notifications when they fail.
Refer to the [Tests overview](/tests/overview) and to the [Understanding tests](/tests/understanding-tests) guides
to learn more about them.

## Inference pipeline

The inference pipeline is part of a **project's monitoring mode**. It represents a
model that is deployed in production *making inferences*.

A common setup for many teams is to have two inference pipelines: one named `staging`, and the other `production`.
When you publish/stream production data to Openlayer, you need to specify which inference pipeline it belongs to.