In the second part of this two-part series, Hamish Watson shows us how to use infrastructure as code to deploy an Azure Kubernetes systems cluster.

To learn about the many ways to deploy an Azure SQL database, watch part one: https://youtu.be/T05C-ro1_W0?WT.mc_id=dataexposed-c9-niner

Video Content:

  • 0:00 Introduction
  • 0:55 Demo: Deploying Azure Kubernetes systems cluster
  • 7:50 Get started on Azure

In the first part of this two-part series with Hamish Watson, we will look at the various methods available to deploy an Azure SQL database including PowerShell, Azure CLI and Terraform. Creating resources has never been easier or more standard than what we have now.

Related Links:

  • 0:00 Introduction
  • 1:55 A Match Made in the Cloud Overview
  • 4:42 Demo
  • 7:10 Other ways to deploy into Azure
  • 8:22 Continuation of demo
  • 8:56 CI CD Pipeline

Sascha Dittmann has created a series of videos I’m showing how to get started with DevOps for Machine Learning (MLOps) on Microsoft Azure.

In the second video of this 5-part series, you’ll discover how to connect Azure DevOps to your Azure Subscription, as well as create and configure Azure Machine Learning Services from your DevOps pipeline.

If you haven’t yet seen the first video in this series, it’s here on Frank’s World and on YouTube.  

Subscribe for more free data analytics videos: https://www.youtube.com/saschadittmann?sub_confirmation=1And don’t forget to click the bell so you don’t miss anything. Share this video with a YouTuber friend: https://youtu.be/mZUdYu345dg

If you enjoyed this video help others enjoy it by adding captions in your native language:https://www.youtube.com/timedtext_video?v=mZUdYu345dg

Watch my most recent upload: http://bit.ly/2OihAlj

Recommended links to learn more about DevOps for Machine Learning (MLOps):

The GitHub repo with the example code I used: https://github.com/SaschaDittmann/MLOps-Lab

Azure DevOps: https://azure.microsoft.com/en-us/services/devops/

Azure Machine Learning Service: https://azure.microsoft.com/en-us/services/machine-learning-service/

Azure Machine Learning CLI Extension: https://docs.microsoft.com/en-us/azure/machine-learning/service/reference-azure-machine-learning-cli

✅ For business inquiries contact me at CloudBlog@gmx.de

✅ Let’s connect:Twitter: https://twitter.com/SaschaDittmannFacebook: https://www.facebook.com/DataDrivenDevInstagram: https://www.instagram.com/saschadittmann/LinkedIn: https://www.linkedin.com/in/saschadittmannGitHub: https://github.com/SaschaDittmann

DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This helps support my channel and allows me to continue making awesome videos like this. Thank you for the support!

#MLOps #DevOpsForMachineLearning #AzureMLIn this series of videos I’m showing how to get started with DevOps for Machine Learning (MLOps) on Microsoft Azure.

In the second video of this 5-part series, you’ll discover how to connect Azure DevOps to your Azure Subscription, as well as create and configure Azure Machine Learning Services from your DevOps pipeline.

If you haven’t yet seen the first video in this series, I strongly recommend that you do so:

Subscribe for more free data analytics videos:
https://www.youtube.com/saschadittmann?sub_confirmation=1
And don’t forget to click the bell so you don’t miss anything.

Share this video with a YouTuber friend:

If you enjoyed this video help others enjoy it by adding captions in your native language:
https://www.youtube.com/timedtext_video?v=mZUdYu345dg

Watch my most recent upload: http://bit.ly/2OihAlj

Recommended links to learn more about DevOps for Machine Learning (MLOps):

The GitHub repo with the example code I used:
https://github.com/SaschaDittmann/MLOps-Lab

Azure DevOps:
https://azure.microsoft.com/en-us/services/devops/

Azure Machine Learning Service:
https://azure.microsoft.com/en-us/services/machine-learning-service/

Azure Machine Learning CLI Extension:
https://docs.microsoft.com/en-us/azure/machine-learning/service/reference-azure-machine-learning-cli

✅ For business inquiries contact me at CloudBlog@gmx.de

✅ Let’s connect:
Twitter: https://twitter.com/SaschaDittmann
Facebook: https://www.facebook.com/DataDrivenDev
Instagram: https://www.instagram.com/saschadittmann/
LinkedIn: https://www.linkedin.com/in/saschadittmann
GitHub: https://github.com/SaschaDittmann

DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This helps support my channel and allows me to continue making awesome videos like this. Thank you for the support!

#MLOps #DevOpsForMachineLearning #AzureML

Sascha Dittmann shows us how to get started with DevOps for Machine Learning (MLOps) on Microsoft Azure in this first in a series of videos.

In the first video of this 5-part series, you’ll discover how to create an Azure DevOps project, import sample machine learning code and create a DevOps pipeline to process simple Data Quality Checks.I use services like Azure DevOps and Azure Machine Learning Services for this challenge.

In this video, Anna Hoffman and Jeroen ter Heerdt discuss and show how you can get started with Azure CLI and the Azure Cloud Shell with respect to Azure SQL.      

Time Index:

  • [00:00] Intro
  • [00:38] Intro to the Azure Cloud Shell (ACS)
  • [01:06] Switch between Bash and PowerShell in ACS
  • [01:20] Azure CLI is cross-platform
  • [01:48] Set Azure subscription
  • [02:05] Set default resource group and logical server
  • [02:28] Demo of Azure CLI SQL commands
  • [03:37] All Azure CLI commands available
  • [04:28] Azure CLI in PowerShell notebooks in Azure Data Studio

For more info, see https://docs.microsoft.com/en-us/cli/azure/sql/db?view=azure-cli-latest&WT.mc_id=dataexposed-c9-niner.

In this video, Damian Brady speaks to George Verghese from the Azure DevOps team about the new Azure DevOps CLI. There are several ways to work with Azure DevOps, and if your goal is automation, the CLI should definitely be in your toolbelt.

George explains why you may want to use the CLI over the other options, and walks through its capabilities, how to use it, and some of the scenarios it can help with.

Links Related to Azure DevOps & Azure DevOps CLI

Follow George on Twitter: @gvvarkey
Follow Damian on Twitter: @damovisa

Resources: