Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that provides a single, web-based interface where you can perform all ML development steps. It allows you to build, train, and deploy ML models at scale, and it provides a range of tools and features to help you streamline your ML workflows. One of the key features of SageMaker Studio is the ability to create lifecycle configurations that automate the setup and configuration of your development environment. In this article, we will explore how to deploy SageMaker Studio lifecycle configurations with AWS CDK on Amazon Web Services (AWS).
What are SageMaker Studio Lifecycle Configurations?
SageMaker Studio lifecycle configurations are scripts that automate the setup and configuration of your development environment. They allow you to customize your environment by installing software packages, configuring settings, and running scripts. You can use lifecycle configurations to set up your environment for specific use cases, such as data preprocessing, model training, or deployment.
Lifecycle configurations are written in Bash or Python and can be stored in Amazon S3 buckets. You can associate a lifecycle configuration with a SageMaker Studio user profile or a domain profile. When a user logs in to SageMaker Studio or creates a new notebook instance, the associated lifecycle configuration is automatically executed.
What is AWS CDK?
AWS Cloud Development Kit (CDK) is an open-source software development framework that allows you to define cloud infrastructure using familiar programming languages such as TypeScript, Python, and Java. With AWS CDK, you can define your infrastructure as code and deploy it using AWS CloudFormation. This approach allows you to automate the deployment of your infrastructure and manage it as code.
How to Deploy SageMaker Studio Lifecycle Configurations with AWS CDK?
To deploy SageMaker Studio lifecycle configurations with AWS CDK, you need to follow these steps:
Step 1: Install AWS CDK
To install AWS CDK, you need to have Node.js and npm installed on your system. You can install them by following the instructions on the Node.js website. Once you have Node.js and npm installed, you can install AWS CDK by running the following command:
“`
npm install -g aws-cdk
“`
Step 2: Create a new AWS CDK project
To create a new AWS CDK project, you can use the following command:
“`
cdk init app –language=typescript
“`
This command creates a new AWS CDK project in TypeScript. You can replace `typescript` with `python` or `java` if you prefer to use a different programming language.
Step 3: Define your SageMaker Studio lifecycle configuration
To define your SageMaker Studio lifecycle configuration, you need to create a new file in your AWS CDK project and write your configuration script in Bash or Python. You can use the following code as an example:
“`bash
#!/bin/bash
# Install required packages
sudo yum install -y git
# Clone your repository
git clone https://github.com/your-repo.git
# Install Python packages
pip install -r requirements.txt
“`
This script installs the `git` package, clones your repository, and installs the required Python packages.
Step 4: Define your AWS CDK stack
To define your AWS CDK stack, you need to create a new file in your AWS CDK project and write your stack definition in TypeScript. You can use the following code as an example:
“`typescript
import * as cdk from ‘aws-cdk-lib’;
import * as sagemaker from ‘aws-cdk-lib/aws-sagemaker’;
import * as s3 from ‘aws-cdk-lib/aws-s3’;
export class SageMakerStudioLifecycleConfigStack extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props?: cdk.StackProps) {
super(scope, id, props);
// Create an S3 bucket to store the lifecycle configuration
const bucket = new s3.Bucket(this, ‘LifecycleConfigBucket’);
// Create the lifecycle configuration
const lifecycleConfig = new sagemaker.CfnLifecycleConfig(this, ‘LifecycleConfig’, {
name: ‘MyLifecycleConfig’,
onCreate: [
{
content: cdk.Fn.base64(‘#!/bin/bashnsudo yum install -y gitn’),
},
{
content: cdk.Fn.base64(`#!/bin/bash
git clone https://github.com/your-repo.git
pip install -r requirements.txt
`),
},
],
rules: [
{
ruleConfiguration: {
instanceTypeRegex: ‘ml.*’,
},
ruleEvaluation: ‘Start’,
},
],
});
// Associate the lifecycle configuration with a user profile
const userProfile = new sagemaker.CfnUserProfile(this, ‘UserProfile’, {
domainId: ‘your-domain-id’,
userProfileName: ‘MyUserProfile’,
single
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