Unified monitoring view in Kubernetes : Linking infrastructure monitoring with application monitoring

Introduction

Typically you notice that there are two dimensions / viewpoints when it comes to monitoring. On one side there is a team that wants to view everything related to the “infrastructure”, like for instance the kubernetes cluster. On the other hand, there is the typical application performance monitoring that starts from the application side. Sadly enough, in a lot of cases, those two are separated islands… ūüė¶

 

As you might know, on the Azure front you can do Application Performance Monitoring with Application Insights and there is like a really awesome integration with Azure Monitor (“Log Analytics”) from the container space (kubernetes). Though I see you thinking it… Two separate solutions. Though, what a lot of people forget, is that they are actually using “Log Analytics” under the hood. And… That you can query across workspaces in Log Analytics! Which means that you can join the two and have an aggregated view to span both worlds.

 

Let’s take a look!

For this test, I’ve created a k8s cluster which is linked to a separate log analytics work-space. Where next to it, there is an application (Azure Function) inside of a docker container that is linked to Application Insights.

 

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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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Replatforming Azure Functions into an Azure Functions Container

Introduction

A while ago I talked about¬† “Faas/Serverless” in relation to vendor lock-in. Today we’ll be continuing in that road, where we’ll be doing a small proof-of-concept (PoC). In this PoC, we’ll be replatforming¬†existing Azure Functions code into an Azure Functions container!

 

Things to know

Since Azure Functions 2.0 (in preview at the time of writing this post), you are able to leverage containers. Though be aware that there are several known issues. Do check them out first before embarking on your journey!

 

Testdriving 2.0

So first, we’ll start off with testing the Azure Functions Core Tools!¬† If you’re looking to follow this guide, be sure to have the Azure Functions Core Tools installed, which also depends on .NET Core 2.0 and Nodejs. Once you have those installed, do a “func –help”, and you’ll see what capabilities are at hand…

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A first glance at the preview AKS (Azure Kubernetes Service)

Introduction

Today the new “AKS” (Azure Kubernetes Services) was launched in preview. This is a managed container service. So where ACS used to rely on IaaS and used a set of best practices to deploy the cluster. AKS will go a step further, where it’ll managed the master nodes & provide upgrade tracks.

 

Deploying

Let’s start with deploying an AKS cluster… Here we can select the k8s (kubernetes) version too.

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From Github to ACI – A tale how to use Visual Studio Team Services & Azure Container Registry for Container CI/CD

Introduction

Today’s post is conceptually a rather simple one… Let’s see how we can go from this ;

To here ;

By using a CI/CD pipeline.

 

Flow of the day

What will we be doing today?

  • Kick-off a VSTS build once a change has been made to our Github repo
    • Build a container via VSTS
    • Publish the container to an ACR (Azure Container Registry)
  • Kick-off a VSTS release once the build succeeded
    • Use an ARM template to deploy an ACI (Azure Container Instance) with our docker container underneath

Sound cool? Let’s get to it!

Continue reading “From Github to ACI – A tale how to use Visual Studio Team Services & Azure Container Registry for Container CI/CD”

Azure Service Fabric : Deploying your first container…

Introduction

In the past I’ve already done several posts about containers. This by using various orchestrators & workflow management tools.¬†Today’s post will be about deploying a Linux container with Service Fabric… The main goals is to provide you with the look & feel of the initial steps. In a future posts, I’ll delve into the more advanced stuff (like data persistence & inter-container connectivity).

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A quick glance at the newly announced Azure Container Instances

Introduction

The Azure Container Instances (ACI) have just been announced. Today we’ll take a quick glance on how it looks in reality. Though what are ACIs?

Azure Container Instances offers the fastest and simplest way to run a container in Azure, without having to provision any virtual machines and without having to adopt a higher-level service.

Want to try it yourself? Check out the ACI Quickstart!

 

Let’s see how it looks?

In contrast to the quick start, I’m going to use the portal… This is currently not the preferred way, though let’s see how that one looks at the moment.

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