info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#designated-technical-writers
Snowplow is an enterprise-grade marketing and product analytics platform which helps track the way users engage with our website and application.
From [Snowplow's documentation](https://github.com/snowplow/snowplow), Snowplow consists of six loosely-coupled sub-systems:
- **Trackers** fire Snowplow events. Currently Snowplow has 12 trackers, covering web, mobile, desktop, server and IoT
- **Collectors** receive Snowplow events from trackers. Currently we have three different event collectors, sinking events either to Amazon S3, Apache Kafka or Amazon Kinesis
- **Enrich** cleans up the raw Snowplow events, enriches them and puts them into storage. Currently we have a Hadoop-based enrichment process, and a Kinesis- or Kafka-based process
- **Storage** is where the Snowplow events live. Currently we store the Snowplow events in a flat file structure on S3, and in the Redshift and PostgreSQL databases
- **Data modeling** is where event-level data is joined with other data sets and aggregated into smaller data sets, and business logic is applied. This produces a clean set of tables which make it easier to perform analysis on the data. We have data models for Redshift and Looker
- **Analytics** are performed on the Snowplow events or on the aggregate tables.
We currently have many definitions of Snowplow's schema. We have an active issue to [standardize this schema](https://gitlab.com/gitlab-org/gitlab/-/issues/207930) including the following definitions:
- The instance level, which will enable tracking on both the frontend and backend layers.
- User level, though user tracking can be disabled on a per-user basis. GitLab tracking respects the [Do Not Track](https://www.eff.org/issues/do-not-track) standard, so any user who has enabled the Do Not Track option in their browser will also not be tracked from a user level.
We utilize Snowplow for the majority of our tracking strategy and it is enabled on GitLab.com. On a self-managed instance, Snowplow can be enabled by navigating to:
- **Admin Area > Settings > Integrations** in the UI.
-`admin/application_settings/integrations` in your browser.
The following configuration is required:
| Name | Value |
| ------------- | ------------------------- |
| Collector | `snowplow.trx.gitlab.net` |
| Site ID | `gitlab` |
| Cookie domain | `.gitlab.com` |
## Snowplow request flow
The following example shows a basic request/response flow between a Snowplow JS / Ruby Trackers on GitLab.com, [the GitLab.com Snowplow Collector](https://about.gitlab.com/handbook/engineering/infrastructure/library/snowplow/), GitLab's S3 Bucket, GitLab's Snowflake Data Warehouse, and Sisense.:
```mermaid
sequenceDiagram
participant Snowplow JS (Frontend)
participant Snowplow Ruby (Backend)
participant GitLab.com Snowplow Collector
participant S3 Bucket
participant Snowflake DW
participant Sisense Dashboards
Snowplow JS (Frontend) ->> GitLab.com Snowplow Collector: FE Tracking event
Snowplow Ruby (Backend) ->> GitLab.com Snowplow Collector: BE Tracking event
loop Process using Kinesis Stream
GitLab.com Snowplow Collector ->> GitLab.com Snowplow Collector: Log raw events
Snowflake DW->>Snowflake DW: Transform data using dbt
Snowflake DW->>Sisense Dashboards: Data available for querying
```
## Implementing Snowplow JS (Frontend) tracking
GitLab provides `Tracking`, an interface that wraps the [Snowplow JavaScript Tracker](https://github.com/snowplow/snowplow/wiki/javascript-tracker) for tracking custom events. There are a few ways to utilize tracking, but each generally requires at minimum, a `category` and an `action`. Additional data can be provided that adheres to our [Feature instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy).
| `category` | string | document.body.dataset.page | Page or subsection of a page that events are being captured within. |
| `action` | string | 'generic' | Action the user is taking. Clicks should be `click` and activations should be `activate`, so for example, focusing a form field would be `activate_form_input`, and clicking a button would be `click_button`. |
| `data` | object | {} | Additional data such as `label`, `property`, `value`, and `context` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). |
### Tracking in HAML (or Vue Templates)
When working within HAML (or Vue templates) we can add `data-track-*` attributes to elements of interest. All elements that have a `data-track-event` attribute will automatically have event tracking bound on clicks.
Below is an example of `data-track-*` attributes assigned to a button:
Event listeners are bound at the document level to handle click events on or within elements with these data attributes. This allows for them to be properly handled on re-rendering and changes to the DOM, but it's important to know that because of the way these events are bound, click events shouldn't be stopped from propagating up the DOM tree. If for any reason click events are being stopped from propagating, you'll need to implement your own listeners and follow the instructions in [Tracking in raw JavaScript](#tracking-in-raw-javascript).
| `data-track-event` | true | Action the user is taking. Clicks must be prepended with `click` and activations must be prepended with `activate`. For example, focusing a form field would be `activate_form_input` and clicking a button would be `click_button`. |
| `data-track-label` | false | The `label` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). |
| `data-track-property` | false | The `property` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). |
| `data-track-value` | false | The `value` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). If omitted, this will be the element's `value` property or an empty string. For checkboxes, the default value will be the element's checked attribute or `false` when unchecked. |
| `data-track-context` | false | The `context` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). |
### Tracking within Vue components
There's a tracking Vue mixin that can be used in components if more complex tracking is required. To use it, first import the `Tracking` library and request a mixin.
You can provide default options that will be passed along whenever an event is tracked from within your component. For instance, if all events within a component should be tracked with a given `label`, you can provide one at this time. Available defaults are `category`, `label`, `property`, and `value`. If no category is specified, `document.body.dataset.page` is used as the default.
You can then use the mixin normally in your component with the `mixin`, Vue declaration. The mixin also provides the ability to specify tracking options in `data` or `computed`. These will override any defaults and allows the values to be dynamic from props, or based on state.
```javascript
export default {
mixins: [trackingMixin],
// ...[component implementation]...
data() {
return {
expanded: false,
tracking: {
label: 'left_sidebar'
}
};
},
}
```
The mixin provides a `track` method that can be called within the template, or from component methods. An example of the whole implementation might look like the following.
<a@click.prevent="track('click_action')">Track an event</a>
</div>
</div>
</template>
```
### Tracking in raw JavaScript
Custom event tracking and instrumentation can be added by directly calling the `Tracking.event` static function. The following example demonstrates tracking a click on a button by calling `Tracking.event` manually.
GitLab provides `Gitlab::Tracking`, an interface that wraps the [Snowplow Ruby Tracker](https://github.com/snowplow/snowplow/wiki/ruby-tracker) for tracking custom events.
Custom event tracking and instrumentation can be added by directly calling the `GitLab::Tracking.event` class method, which accepts the following arguments:
| `category` | string | 'application' | Area or aspect of the application. This could be `HealthCheckController` or `Lfs::FileTransformer` for instance. |
| `action` | string | 'generic' | The action being taken, which can be anything from a controller action like `create` to something like an Active Record callback. |
| `data` | object | {} | Additional data such as `label`, `property`, `value`, and `context` as described [in our Feature Instrumentation taxonomy](https://about.gitlab.com/handbook/product/feature-instrumentation/#taxonomy). These will be set as empty strings if you don't provide them. |
Tracking can be viewed as either tracking user behavior, or can be utilized for instrumentation to monitor and visual performance over time in an area or aspect of code.
We use the [AsyncEmitter](https://github.com/snowplow/snowplow/wiki/Ruby-Tracker#52-the-asyncemitter-class) when tracking events, which allows for instrumentation calls to be run in a background thread. This is still an active area of development.
## Developing and testing Snowplow
There are several tools for developing and testing Snowplow Event
| Testing Tool | Frontend Tracking | Backend Tracking | Local Development Environment | Production Environment |
1. Open Chrome DevTools to the Snowplow Analytics Debugger tab
1. Learn more at [Igloo Analytics](https://www.iglooanalytics.com/blog/snowplow-analytics-debugger-chrome-extension.html)
### Snowplow Inspector Chrome Extension
Snowplow Inspector Chrome Extension is a browser extension for testing frontend events. This works on production, staging and local development environments.
1. Open the chrome extension by pressing the Snowplow Inspector icon beside the address bar
1. Click around on a webpage with Snowplow and you should see JavaScript events firing in the inspector window.
### Snowplow Micro
Snowplow Micro is a very small version of a full Snowplow data collection pipeline: small enough that it can be launched by a test suite. Events can be recorded into Snowplow Micro just as they can a full Snowplow pipeline. Micro then exposes an API that can be queried.
Snowplow Micro is a Docker-based solution for testing frontend and backend events in a local development environment. You need to modify GDK using the instructions below to set this up.
