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  • Prerequisites
  • Defining our stack
  • Deploying our stack
  • Get stack outputs
  • Destroying our stack
  • What next?

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  1. Getting Started
  2. Quickstart

K3D Quickstart

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Last updated 1 year ago

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This quickstart will guide you through deploying a simple stack using K3D to simulate a cloud provider using mlstacks. We'll be deploying a simple minio bucket. This is as simple and quick an example of how mlstacks works as it gets.

Prerequisites

First, install the mlstacks CLI:

pip install mlstacks

You will need to have K3D installed. Please visit the for installation instructions.

If you don't have or installed, you should also install them.

Defining our stack

Then, create a file called quickstart_stack.yaml wherever you have access to the mlstacks tool. In this file, add the following:

spec_version: 1
spec_type: stack
name: "quickstart_stack"
provider: k3d
default_region: "local"
default_tags:
  deployed-by: "mlstacks"
components:
  - simple_component_minio.yaml

This defines our stack using the mlstacks specification. We'll now define the component that we want to deploy in a separate file called simple_component_minio.yaml:

spec_version: 1
spec_type: component
component_type: "artifact_store"
component_flavor: "minio"
name: "quickstart_minio_bucket"
provider: k3d
metadata:
  config:
    bucket_name: "quickstart_minio_bucket"
  tags:
    deployed-by: "mlstacks"
  region: "local"

Deploying our stack

Now, we can deploy our stack using the mlstacks CLI:

mlstacks deploy -f quickstart_stack.yaml

This will deploy our stack to a local K3D cluster. You can now check your K3D console to see that the stack and the minio bucket has been deployed.

Get stack outputs

You can get the outputs of your stack using the mlstacks CLI:

mlstacks output -f quickstart_stack.yaml

This will print out the outputs of your stack, which you can use in your pipelines.

Destroying our stack

Finally, we can destroy our stack using the mlstacks CLI:

mlstacks destroy -f quickstart_stack.yaml

What next?

You can now try adding more components and deploying them to this K3D provider. You can also try deploying your stack to an actual cloud provider instead of this local environment.

Good luck! And if you have any questions, feel free to

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