A Pulumi package for creating and managing DataRobot resources.
Project description
DataRobot Resource Provider
The DataRobot Resource Provider lets you manage DataRobot resources. The provider is built on terraform-provider-datarobot. To use this package, please install the Pulumi CLI first.
Installing
This package is available for several languages/platforms:
- Python:
pulumi-datarobot - JavaScript/TypeScript:
@datarobot/pulumi-datarobot - Go:
github.com/datarobot-community/pulumi-datarobot/sdk - .NET:
DataRobotPulumi.Datarobot
Python
To use from Python, install using pip:
pip install pulumi_datarobot
Javascript/Typescript
To use from JavaScript or TypeScript in Node.js, install using either npm:
npm install @datarobot/pulumi-datarobot
or yarn:
yarn add @datarobot/pulumi-datarobot
Go
go get github.com/datarobot-community/pulumi-datarobot/sdk/go/...
.NET
To use from .NET, install using dotnet add package:
dotnet add package DataRobotPulumi.Datarobot
YAML
No install necessary, just run pulumi up.
Configuration
The following configuration points are available for the DataRobot provider:
datarobot:apikey(environment:DATAROBOT_API_TOKEN) - the API key for DataRobotdatarobot:endpoint(environment:DATAROBOT_ENDPOINT) - the endpoint for DataRobot
Examples
Air-Gapped Environments
Keep the following items in mind if running in an air-gapped environment:
-
Run
pulumi login --localto store state files on your local filesystem, instead of the default Pulumi Cloud. Pulumi binaries are available here. -
Set
DATAROBOT_ENDPOINT: https://{datarobot.example.com}/api/v2 (replacing {datarobot.example.com} with your specific deployment endpoint) -
For Python, the pulumi and pulumi-datarobot packages must be installed in the air-gapped system.
Example using
pip wheel:- create a directory where you want to store package wheels.
mkdir folder_containing_wheel- Now install wheels of the python library you want to install
pip wheel pulumi-datarobot -w folder_containing_wheel
This will store all your required dependent wheels of the
pulumi-datarobotpackage in the folder. you can check it with doing ls -ltr`.- Now, you can make a tar file of this folder.
tar cf folder_containing_wheel.tar folder_containing_wheel/
and you can transfer it to your air-gapped system.
Now untar the folder.
tar xf folder_containing_wheel.tar cd folder_containing_wheel/
now install wheels from the folder.
pip install * -f ./ --no-index
You will also need to download the binary plugin from this repository. Click on the version that matches the Python package
version from our Releases page, download the tar.gz
for the correct architecture of your computer. For Codespaces, that is *-linux-amd64.tar.gz. After you've extracted it
install it with:
pulumi plugin install resource datarobot <version> -f <path-to-extracted-folder>
Rate limited by GitHub?
[!IMPORTANT] GitHub has hard limits on API calls that cannot be changed. If you are running into this when running deployment tasks you have a couple of options. You can wait until the rate limit expires or you can do a direct download from the releases page which will not use the API and hit the limit.
To directly download the plugin and bypass the GitHub API run:
pulumi plugin install resource datarobot <version> --server https://github.com/datarobot-community/pulumi-datarobot/releases/download/<version>/
For example, to download version 0.10.14, you can run:
pulumi plugin install resource datarobot v0.10.14 --server https://github.com/datarobot-community/pulumi-datarobot/releases/download/v0.10.14/
prior to running the deploy to directly install the plugin.
After you have it downloaded, it will still attempt to query for
updates via the GitHub API that can trigger rate limits. To bypass
that, set the environment variable: PULUMI_SKIP_UPDATE_CHECK
export PULUMI_SKIP_UPDATE_CHECK=1
# OR
export PULUMI_SKIP_UPDATE_CHECK=true
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