From ab844171d0601d432552f3676ab48af481c3959b Mon Sep 17 00:00:00 2001 From: Oseer Williams Date: Fri, 17 May 2024 15:02:30 -0400 Subject: [PATCH] fix(pr): preview url --- ...d-lake-demo-jupyter-google-cloud-vertex-ai.md | 16 ++++++++-------- .../vantagecloud-lake-demo-jupyter-sagemaker.md | 2 +- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-google-cloud-vertex-ai.md b/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-google-cloud-vertex-ai.md index d101a7c095..2ab6220e75 100644 --- a/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-google-cloud-vertex-ai.md +++ b/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-google-cloud-vertex-ai.md @@ -30,7 +30,7 @@ When you create a new notebook instance, you can specify a startup script. This - Create a bucket with a name relevant to the project (e.g., teradata_jupyter). - Ensure that the bucket name is globally unique. For instance, if the name teradata_jupyter has already been used, it will not be available for subsequent users. -![New bucket](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/bucket.PNG) +![New bucket](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/bucket.png) * Upload the unizzped Jupyter extension package to your Google Cloud Storage bucket as a file. @@ -74,7 +74,7 @@ su - jupyter -c "git clone https://github.com/Teradata/lake-demos.git" ``` * Upload this script to your Google Cloud storage bucket as a file -![files uploaded to bucket](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/upload.PNG) +![files uploaded to bucket](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/upload.png) ### Initiating a user managed notebook instance @@ -85,15 +85,15 @@ su - jupyter -c "git clone https://github.com/Teradata/lake-demos.git" * Under Details, name your notebook, select your region and select continue. -![notebook env details](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/detailsenv.PNG) +![notebook env details](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/detailsenv.png) * Under Environment select **Browse** to select your startup.sh script from your Google Cloud Bucket. -![select startup script](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/startupscript.PNG) +![select startup script](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/startupscript.png) * Select Create to initiate the notebook. It may take a few minutes for the notebook creation process to complete. When it is done, click on OPEN JUPYTERLAB. -![active notebook](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/activenotebook.PNG) +![active notebook](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/activenotebook.png) :::info You will have to whitelist this IP in your VantageCloud Lake environment to allow the connection. This solution is appropriate in a trial environment. For production environments, a configuration of VPCs, Subnets, and Security Groups might need to be configured and whitelisted. @@ -101,7 +101,7 @@ You will have to whitelist this IP in your VantageCloud Lake environment to allo * On JupyterLab open a notebook with a Python kernel and run the following command for finding your notebook instance IP address. -![python3 kernel](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/python3.PNG) +![python3 kernel](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/python3.png) ``` python , role="content-editable" import requests @@ -123,11 +123,11 @@ print("My Public IP is:", my_public_ip) ## Edit vars.json Navigate into the `lake-demos` directory in your notebook. -![notebook launcher](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/notebooklauncher.PNG) +![notebook launcher](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/notebooklauncher.png) Right click on vars.json to open the file with editor. -![vars.json](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/openvars.PNG) +![vars.json](./images/vantage-lake-demo-jupyter-google-cloud-vertex-ai/openvars.png) Edit the *[vars.json file](https://github.com/Teradata/lake-demos/blob/main/vars.json)* file to include the required credentials to run the demos + diff --git a/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-sagemaker.md b/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-sagemaker.md index b9ad0b72f2..abd30a3e9f 100644 --- a/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-sagemaker.md +++ b/quickstarts/vantagecloud-lake/vantagecloud-lake-demo-jupyter-sagemaker.md @@ -31,7 +31,7 @@ In this section we will cover in detail each of the steps below: * Default options are appropiate for this bucket * In the created bucket upload the Teradata modules for Jupyter -![Load modules in S3 bucket](./images/vantagecloud-lake-demo-jupyter-sagemaker/sagemaker-bucket-upload.PNG) +![Load modules in S3 bucket](./images/vantagecloud-lake-demo-jupyter-sagemaker/sagemaker-bucket-upload.png) ### Create an IAM role for your Jupyter Notebooks instance * On SageMaker navigate to the role manager