> For the complete documentation index, see [llms.txt](https://mlstacks.zenml.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://mlstacks.zenml.io/stacks/gcp.md).

# GCP

The GCP Modular recipe is available in the `mlstacks` repository and you can [view the raw Terraform files here](https://github.com/zenml-io/mlstacks/tree/main/src/mlstacks/terraform/gcp-modular).

A full list of supported components and flavors can be found in the [Supported Components and Flavors](#supported-components-and-flavors) section, as can a list of components that are coming soon.

## Important Notes for GCP Deployments

All GCP deployments require the inclusion of a GCP Project ID in the metadata's config for each component. This is because GCP resources are tied to a project and cannot be created without one.

## Supported components and flavors

| Component          | Flavor(s)                                      |
| ------------------ | ---------------------------------------------- |
| Artifact Store     | gcp                                            |
| Container Registry | gcp                                            |
| Experiment Tracker | mlflow                                         |
| Orchestrator       | kubeflow, kubernetes, skypilot, tekton, vertex |
| MLOps Platform     | zenml                                          |
| Model Deployer     | seldon                                         |
| Step Operator      | vertex                                         |

## Coming Soon!

* Airflow Orchestrator on GCP
* Feast Feature Store on GCP
* Label Studio Annotator on GCP
* Model Registry components on GCP
* Image Builder components on GCP


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://mlstacks.zenml.io/stacks/gcp.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.