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Azure Resources

General Resources

Main Azue Documentation : https://docs.microsoft.com/en-us/azure/

List of All Azure Services : https://portal.azure.com/#allservices

Azure Tips and Tricks : https://microsoft.github.io/AzureTipsAndTricks/

Azure Portal "How to" series - focused on using the Azure portal to do several different things. This is mostly about the services themselves, not the portal, and many topics do not apply to us (e.g. Azure Arc) but there are some very useful videos : https://youtube.com/playlist?list=PLLasX02E8BPBKgXP4oflOL29TtqTzwhxR

These look like really good intros to Azure, but requires a time investment. The examples are not really research computing examples but may be valuable learning examples. Most of these lessons were taken from other 'learning paths' and are still oriented towards IT professionals

Microsoft Learn: - Azure for Researchers part 1: Introduction to Cloud Computing - Azure for Researchers part 2: Cloud Security and Cost Management

Interface: Azure Portal

Azure Portal Documentation : https://docs.microsoft.com/en-us/azure/azure-portal/

Microsoft Azure Hierarchy: Organize your Azure resources effectively

Re-organize your portal view by creating a new dashboard (optional) : https://docs.microsoft.com/en-us/azure/azure-portal/azure-portal-dashboards

Azure portal productivity Tips : https://microsoft.github.io/AzureTipsAndTricks/blog/tip329.html#azure-portal-productivity-tips

https://microsoft.github.io/AzureTipsAndTricks/blog/tip329.html

Interface: Command Line

Command-line progamming of Cloud Services

Storage

Create a Storage Account:

https://docs.microsoft.com/en-us/azure/storage/common/storage-quickstart-create-account

Azure Storage Explorer: https://azure.microsoft.com/en-us/features/storage-explorer/

Blob Storage Documentation: https://docs.microsoft.com/en-us/azure/storage/blobs/

Create and Manage a Storage Account: https://docs.microsoft.com/en-us/azure/storage/common/storage-quickstart-create-account

Using the CLI with Storage Reference: https://docs.microsoft.com/en-us/cli/azure/storage/account

Using PowerShell Storage Reference: https://docs.microsoft.com/en-us/powershell/module/azure.storage

Create blob storage with CLI:

https://docs.microsoft.com/en-us/azure/storage/common/storage-azure-cli

Create blob storage with PowerShell:

https://docs.microsoft.com/en-us/azure/storage/blobs/storage-quickstart-blobs-powershell

Compute

Overview of Compute Options: https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/compute-overview

Choosing an Azure Compute Service (Decision Tree): https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/compute-decision-tree

Interface: ARM templates

Azure Resource Manager Templates are JSON-formatted configuration files that dictate which resources to create.

Overview of ARM templates: https://docs.microsoft.com/en-us/azure/azure-resource-manager/templates/overview

explore quick start ARM templates (web): https://azure.microsoft.com/en-us/resources/templates/

explore quick start ARM templates (github): https://github.com/Azure/AzureStack-QuickStart-Templates

  • many of these github repositories include a "deploy to Azure" button that will run the template via the portal and create resources.

Programming with SDKs

R and Azure

https://blog.revolutionanalytics.com/2018/12/azurestor.html

https://cloudblogs.microsoft.com/opensource/2019/07/01/azurer-available-create-manage-monitor-azure-services-r/

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/r-developers-guide

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/r-packages-supported-by-azure-machine-learning

https://github.com/Azure/AzureContainers

https://github.com/Azure/AzureR

https://github.com/Azure/AzureRMR

Python and Azure

https://azure.microsoft.com/en-us/develop/python/

https://docs.microsoft.com/en-us/azure/python/

https://github.com/Azure/azure-sdk-for-python

https://github.com/Azure/azure-storage-python

https://azure.github.io/azure-sdk/releases/latest/all/python.html (Note that pypi.org/project/azure/ is deprecated/obsolete if you find that via google)

MATLAB and Azure

https://blogs.msdn.microsoft.com/uk_faculty_connection/2017/06/29/running-matlab-on-azure-provision-a-matlab-distributed-computing-server-using-azure-vms/

https://github.com/mathworks-ref-arch/matlab-on-azure

https://www.itcentralstation.com/products/comparisons/mathworks-matlab_vs_microsoft-azure-machine-learning-studio

https://www.mathworks.com/solutions/cloud.html

Microsoft Azure Cosmos DB

CosmosDB is a very large scale data system that can act like other database systems including SQL, MongoDB (a popular no-sql database), and others.
It's advantage is that it can handle extremely large data sets (65tB) but is easy to get started. Google and AWS have similar offereings ( "BigQuery" and "Aurora" respectively).

If your data is not large, consider using SQL data systems which are also very widely used (and can be used on your own computer)

Intro: https://docs.microsoft.com/en-us/azure/cosmos-db/introduction

It can be free to use, but you have to turn that on when creating the service for your account: https://docs.microsoft.com/en-us/azure/cosmos-db/free-tier

You can run a notebook inside the databaase to queery data with python :

Cloud Architecture

This section has resources for advanced to intermediate cloud users who are interested in much more details that most researchers will ever need, and are really geared for IT staff. However, sometimes to find insight into how to approach your problem (especially for cloud timing ooptimazation projects) these may have useful sections.

Microsoft Azure Infrastructure Services for Architects by John Savill, Oct 2019, available from the MSU Library : http://catalog.lib.msu.edu/record=b13538669~S39

Azure has changed since 2019 but may still be relevant