# Creating a Notebook Instance

We'll start by creating an Amazon S3 bucket that will be used throughout the workshop.  We'll then create a SageMaker notebook instance, which we will use for the other workshop modules.

## 1. Create a S3 Bucket

SageMaker typically uses S3 as storage for data and model artifacts.  In this step you'll create a S3 bucket for this purpose. To begin, sign into the AWS Management Console, https://console.aws.amazon.com/.

### High-Level Instructions

Use the console or AWS CLI to create an Amazon S3 bucket (see step-by-step instructions below if you are unfamiliar with this process). Keep in mind that your bucket's name must be globally unique across all regions and customers. We recommend using a name like `smworkshop-firstname-lastname`. If you get an error that your bucket name already exists, try adding additional numbers or characters until you find an unused name.

<details>
<summary><strong>Step-by-step instructions (expand for details)</strong></summary><p>

1. In the AWS Management Console, choose **Services** then select **S3** under Storage.

1. Choose **+Create Bucket**

1. Provide a globally unique name for your bucket such as `smworkshop-firstname-lastname`.

1. Select the Region you've chosen to use for this workshop from the dropdown.

1. Choose **Create** in the lower left of the dialog without selecting a bucket to copy settings from.

</p></details>

## 2. Launching the Notebook Instance

1. Make sure you are on the AWS Management Console home page.  In the **Find Services** search box, type **SageMaker**.  The search result list will populate with Amazon SageMaker, which you should now click.  This will bring you to the Amazon SageMaker console homepage.

![Services in Console](./images/console-services.png)

2. In the upper-right corner of the AWS Management Console, confirm you are in the desired AWS region. Select N. Virginia, Oregon, Ohio, or Ireland.

3. To create a new notebook instance, click the **Notebook instances** link on the left side, and click the **Create notebook instance** button in the upper right corner of the browser window.

![Notebook Instances](./images/notebook-instances.png)

4. Type smworkshop-[First Name]-[Last Name] into the **Notebook instance name** text box, and select ml.m5.xlarge for the **Notebook instance type**.

![Notebook Settings](./images/notebook-settings.png)

5. In the **Permissions and encryption** section, choose **Create a new role** in the **IAM role** drop down menu.  In the resulting pop-up modal, select **Specific S3 buckets** under **S3 Buckets you specify – optional**. In the text field, paste the name of the S3 bucket you created above, AND the following bucket name separated from the first by a comma:  `gdelt-open-data`.  The combined field entry should look similar to ```smworkshop-john-smith, gdelt-open-data```. Click **Create role**.

![Create IAM role](./images/role-popup.png)

6. You will be taken back to the Create Notebook instance page.  Now you should see a message saying "Success! You created an IAM role."

![Create Notebook Instance](./images/permissions-settings.png)

7. Click **Create notebook instance** at the bottom.

### 3. Accessing the Notebook Instance

1. Wait for the server status to change to **InService**. This will take several minutes, possibly up to ten but likely much less.

![Access Notebook](./images/open-notebook.png)

2. Click **Open Jupyter**. You will now see the Jupyter homepage for your notebook instance.