Deploying Azure Marketplace VMs

The first step is to gather information about the Market Place Virtual Machine (VM) image that we want to deploy. For this example I decided to deploy a Tableau Server image.

Login-AzureRmAccount

$location = 'eastus'
  
Get-AzureRmVMImagePublisher -Location $location `
    | Where-Object -Property PublisherName -Like Tableau*
 
$publisherName = 'tableau'
  
Get-AzureRmVMImageOffer -Location $location `
                        -PublisherName $publisherName
 
$offer = 'tableau-server'
  
Get-AzureRmVMImageSku -Location $location `
                      -PublisherName $publisherName `
                      -Offer $offer `
      | Select-Object -Property 'Skus'

Skus                  
----                  
bring-your-own-license

Now that we have the image information, it’s time to create an Azure Resource Manager (ARM) Template.

Geo-HA Service Fabric Cluster

One of the biggest challenges that we face when we build an Internet-scale solution, is high availability across geographic locations (Geo-HA). Why is this important? Well, there can be a few different reasons. The most common reason, is to be able to survive data center outages. Another reason, is to bring services closer to end users so that we can provide good user experiences.

Geo-HA brings challenges to the table. For example, should we use an Active-Passive or Active-Active strategy for data across regions? Keeping in mind that Active-Active is difficult to get right, we need to take time to analyze and to make the correct choices. We need to consider our Disaster recovery (DR) plan, target RPO and RTO. Azure has a whole bunch of mechanisms for replication, backup and monitoring, so how do we decide what’s the right combination?

Today’s Internet-scale services are built using microservices. Service Fabric is a next-generation middleware platform used for building enterprise-class, Tier-1 services. This microservices platform allows us to build scalable, highly available, reliable, and easy to manage solutions. It addresses the significant challenges in developing and managing stateful services. The Reliable Actors API is one of two high-level frameworks provided by Service Fabric, and it is based on the Actor pattern. This API gives us an asynchronous, single-threaded programming model that simplifies our code while still providing the advantages of scalability and reliability guarantees offered by Service Fabric.

A Service Fabric cluster is HA within its geographic region by default. Thinking about our heritage of on premise data centers, we’ve poured thousands of man-hours to deploy Disaster Recovery sites in secondary physical locations, because we know that everything is possible. Over the past few years, we’ve experienced many interesting scenarios, for example, a cut cable, or a faulty DNS entry broke the Internet. So why should we do anything differently in the cloud? We must treat each region as we treat our own data centers and think about Geo-HA.

The rest of this post is about taking high availably to the next level by deploying a Geo-HA Service Fabric cluster.

Deploying Nano Server to Azure

Based on the current builds, compared to Server, Nano Server has 93 percent lower VHD size, 92 percent fewer critical bulletins and 80 percent fewer reboots!

I’ve been curious about Nano Server for a while now. And I recently noticed that it was available on Microsoft Azure. This post is definitely from a developers point-of-view. It goes through the steps required to create a functional Nano Server Virtual Machines (VM) on Microsoft Azure.

Nano Server is ideal for many scenarios:

• As a “compute” host for Hyper-V virtual machines, either in clusters or not
• As a storage host for Scale-Out File Server.
• As a DNS server
• As a web server running Internet Information Services (IIS)
• As a host for applications that are developed using cloud application patterns and run in a container or virtual machine guest operating system.

The Adventure

Nano Server is a remotely administered server operating system (OS). Wait. Let me repeat this because it’s important… Nano Server is a remotely administered server operating system (OS). Developers, Nano Server is a server OS optimized for clouds and data centers. It’s designed to take up far less disk space, to setup significantly faster, and to require far fewer restarts than Windows Server. So why does this matter? Well it means more resources, more availability and stability for our Apps. And it also means that it’s time to learn new skills, because there is no local logon capability at all, nor does it support Terminal Services. However, we have a wide variety of options for managing Nano Server remotely, including Windows PowerShell, Windows Management Instrumentation (WMI), Windows Remote Management, and Emergency Management Services (EMS).

Upload a VHD to Storage Using AzCopy

What’s the best way to upload a VHD to Azure Storage? This question comes up on a regular basis and I decided that it was time to share an example that uses PowerShell and AzCopy to upload a VHD to Azure Blob Storage. As you go through this post, remember that a VHD must be uploaded as a Page Blob for it to be usable as a Virtual Machine (VM) image.

One Petaflop

In recent discussions around big compute I was asked what a Petaflop (PFlop) would look like on Azure. Now, I had heard the term before and knew it was used to describe a considerable capacity of compute. So what is a petaflop (PFlop) and how do we convert this into something that we can all relate to?

Using ARM to Deploy Global Solutions

Imagine deploying your secure load balanced solution to three datacenters, putting in place a worldwide load balancer and doing so in roughly 24 minutes. Did I mention that this deployment is predictable and repeatable?

Good, now that I’ve got your attention, it’s time to dive in!

Building on my previous post about managing compute resources on Azure I decided to modify the Azure Resource Manager(ARM) template to deploy a real-world environment to three datacenters (Yes I know, the diagrams shows two locations, but as I built the demo, I got greedy…). Using Azure Traffic Manager we are able positively affect a users experience by directing them to the closest datacenter.

Its important to note that ARM does not support nested copy operation. This means that we have to use a different strategy to deploy identical environments in multiple Azure regions. After a bit of research it became apparent that I had to use nested deployments. This technique requires us to break our template into multiple files. The parent template in this demo is the azuredeploy-multi-geo.json file. It contains the full list of parameters, a nested deployment that deploys instances of our environment to multiple Azure regions, and a Traffic Manager definition. The azuredeploy.json template file was refactored from the template used in my previous blog post. It contains networking, storage and Virtual Machine definitions.

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A little while ago, I wrote about building, using and destroying environments on Azure. At first, what I proposed may have seemed like overkill, so I took this as a challenge and built this short demo project to demonstrate why I favor destroying environments to shutting them down.

Using Azure PowerShell 1.0 & ARM

Recently the Azure team released a new version of Microsoft Azure PowerShell. They finally broke through v1.0, and that comes with a few breaking changes. But don’t worry, it’s for the best!

This blog post is all about deploying a Windows 10 Visual Studio Virtual Machine to a secured Virtual Network on Microsoft Azure.

Deploying an ARM Template Using PowerShell

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Microsoft Azure has a lot of options when it comes to provisioning environments and resources. In my last post about troubleshooting Virtual Machine allocations, I enumerated a few of these options and briefly mentioned that I favored destroying environments to shutting them down. In this post, I will try to give more context around my preference.

My Azure Virtual Machine Won’t Start

To benefit from elasticity on Microsoft Azure, we regularly leverage strategies that utilize Azure Automation to shut down and de-allocate Virtual Machines when they are not needed.

This strategy is excellent and usually works on pretty well. Due to Azure’s highly dynamic nature, the allocation of Large Virtual Machines can sometimes pose a challenge in the form of “The server encountered an internal error. Please retry the request.” or “Failed to produce an allocation for the service.“.