Azure Custom Vision AI : From training to deploying the container export on the Azure Kuberenetes Service (AKS)

Introduction

Todays post will be the backend tour of “Frietjes-of-Niet” (translated from Dutch : “French-Frites-or-Not?”). A big part of the mission of Azure is about democratizing technology so it becomes accessible to organizations in order for them to achieve more. AI (Artificial Intelligence) is a key part of that vision.

 

End-to-End Flow

What will be the flow for today?

  • We’ll train a model to recognize fries
  • Next we’ll be exporting that model to be used as a container
  • Afterwards we’ll build that container
  • To end with deploying (and testing) it onto AKS

Sound cool? Let’s get to it..

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Taking a glance at Rancher’s ability to manage the Azure Kubernetes Service (AKS)

Introduction

Pfew, it’s odd to admit that it has been a while since I’ve posted about Rancher. Though today is as good a day as any to pick up that thread… So today we’ll go through give or take the same objective as in the past, where we’ll notice that the integration has improved significantly with the arrival of AKS! Let’s get today’s post underway and deploy AKS from our Rancher control plane.

Preparation

Before the below started, I already had the following things ready ;

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Azure Functions : Compiled or interpreted C#… What impact does it have on my performance?

Introduction

Last week I did a post about how to integrate Compiled Azure Functions working with VSTS… In the closing thoughts I made a statement about my observation that compiled functions had a performance improvement.

 

Here I should have known Nills would challenge me on that… 😉

 

So… #challengeaccepted

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Trying out the Azure Firewall in a Hub & Spoke deployment model

Introduction

A few weeks ago the Azure Firewall went into public preview. Today’s post will be around taking it for a spin in a hub & spoke deployment.

 

Architecture

First off, what will the architecture of our deployment look like?

  • A central hub, where we’ll deploy the Azure Firewall. This will consist of the address space 172.16.0.0/12.
  • Two spokes, each with their own address space (10.[1/2].0.0/16) where a UDR will send all traffic to the Azure Firewall (172.16.254.4).
  • In each VNET, we’ll deploy a “SUBNET000” in which we’ll setup a vm to do our basic connectivity testing.
  • Each spoke is connected with a bidirectional VNET peering with the spokes. Both spokes can only talk to each other over the HUB.
  • The Azure firewall will be configured to allow traffic within the 10.0.0.0/8 range.

 

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VSTS & Compiled Azure Functions – How to set up your basic CI/CD pipeline

Introduction

A question that pops up occasionally is how to setup your Azure Functions DevOps flow when you’re using C# underneath. Today’s post will be a brief one to run you through this process. If you should prefer a video on this… That exists too! Curtosiy of the app service product group.

 

Quick Howto

Let’s take a look at the build process. We have (at least, as this flow did not do any testing => “Shame on me!”) three steps in the build process ;

  • Restore the nuget packages
  • Build the solution (and create a single zip file)
  • Publish the artifact

 

So let’s take a look at one of my own builds… First I kick off with installing NuGet on my build agent (should it not already be present).

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IoT Prototyping in Azure with Particle & Grove

Introduction

Today’s post will be on how I see the smoothest way to do prototyping & hobby projects in regards to IoT. What is my main principle in deciding this? I only want to spend time on “business logic” and not waste time on the nuts & bolts of the engine.

Architecture

So what’s the architecture we’ll be using for this?

  1. Device : Particle Photon + Grove Expansion Board + Grove Sensors (Temperature & Air Quality )
  2. Particle Platform : Used for the development
  3. Azure IoT Hub : Basically a 1:1 link with Particle, which will take over once we go to a production grade setup.
  4. Azure Stream Analytics : Streaming the ingest data from our IoT Hub towards our various landing zones.
  5. Azure CosmosDB : For storing the data we’ll use in our reports.
  6. Azure Storage Account : Cheap storage where we keep all the data we collected, and which we could use for our analytics.
  7. PowerBI : The make nice reports of the data we collected. 😉

Now let’s delve into these parts one by one!

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Taking a look under the hood of the Linux VM Authentication

Introduction

Today we’ll do a deep-dive into how you can log into an Azure Linux VM with Azure Active Directory (AAD). In essence, we’ll go through the following documentation flow, and then take a look how that looks under the hood.

 

Part one : “Creation”

The part on creating & integrating the VM is VERY straightforward…

  • Create a resource group
  • Create a Linux virtual machine
  • Add the “Azure AD login VM”-extension

And that’s it! Really, that’s it…

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