# Quickstart

This introduction assumes you are already using dbt in your company and tables you would like to monitor are managed by dbt. To fully use stealthward you need to install both:

* [Stealthward DBT Package](#stealthward-dbt-package)
* [Stealthward Python Package](#stealthward-python-package)

We'll go over the steps required to do that & explain what possibilities those packages create for you.

## Stealthward DBT Package

Add the stealthward dbt pakcage to your main dbt repo project. You need to update your **`packages.yml`** file with stealthward package like that:

```yaml
packages:
    ***
    - package: stealthward/stealet
      version: [">=0.0.1"]
```

and then install dbt packages dependencies by running:

```bash
dbt deps
```

You can do it locally, in your dbt cloud environment, or Airflow etc. scheduler environment.

{% hint style="info" %}
**INFO**

On production, you most likely are already running **`dbt deps`** as part of dbt models computation. So this step maybe only necessary for your local environment.

At last, maybe [Sheenflow](https://app.gitbook.com/o/Q2YSD89DgzskcRTE4LF3/s/GJ6IIwIuOa144ZdCj1er/) is also a nice choice schedule jobs.
{% endhint %}

### Configuration Tables

...

### DBT Package Functions

...

### Computing First Metrics

...

### Storing Test History

...

## Stealthward Python Package

To generate stealthward reliability UI, send stealthward alerts to Slack and easily backfill stealthward models you will need to install the strealthward python library. Install it executing:

```
pip install stealthward
```

### Python Package Functionality

* Stealthward overview UI - For generating & display stealthward UI
* Stealthward notify - For notifying external services about alerts (Currently Slack)
* Stealthward run - For easily backfilling dbt data

### Generate & Server UI

```
stealthward overview generate
stealthward overview server
```