Cloud and Datacenter Management Blog

Microsoft Hybrid Cloud blogsite about Management


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#AzureArc Services with Docker for Windows #Kubernetes Cluster for Testing #DevOps #MSBuild

Microsoft Build 2021 Global virtual event

I Hope everyone had a Great Microsoft Build 2021 Online Conference this week. Microsoft announced a lot of new features and Hybrid Cloud Solutions at Build 2021 🙂 If you missed this Awesome Build 2021 event, you can watch the highlights on demand here.

Microsoft also launched MSBuild Book of News 2021

Build 2021 Resources: Build consistent hybrid and multicloud applications with Azure Arc

DevOps and developers are increasingly using microservices-based architectures with containerized applications for agility and flexibility. Azure Arc extends the single control plane from Azure to enable you to build apps consistently across hybrid and multi-cloud environments. With this information I was thinking, can I connect Microsoft Azure Arc Services to my Surface Book 3 with Windows 10 Preview Insiders Build 21390 and Docker for Windows with Kubernetes Cluster 1.19.7 active?

IMPORTANT: The following step-by-step guide is for testing purpose only.

Installing Docker for Windows with Kubernetes Cluster on Windows 10

First you need to have Docker for Windows 10.

System requirements

Your Windows machine must meet the following requirements to successfully install Docker Desktop.

WSL 2 backend

  • Windows 10 64-bit: Home, Pro, Enterprise, or Education, version 1903 (Build 18362 or higher).
  • Enable the WSL 2 feature on Windows. For detailed instructions, refer to the Microsoft documentation.
  • The following hardware prerequisites are required to successfully run WSL 2 on Windows 10:

Here you can download Docker Desktop for Windows

With docker desktop for Windows you can switch between Windows Containers and Linux Containers. When you want to have a Kubernetes Cluster on your Windows 10 device active you have to switch to Linux Containers in the taskbar like this :

It’s now active for Linux Containers. (Default)

Right Click on the Docker tray icon and go to Settings.
Then go to Kubernetes to enable your Cluster locally on your Windows 10 Device.
When you apply it take some minutes for the installation.

When you see the Kubernetes icon on green, then your Cluster is running.

When you do a lot of DevOps work you use Microsoft Visual Studio Code for Free, because here you can see your Kubernetes Cluster and try your own code or Apps.

Kubernetes Cluster is running locally on your Windows 10 device.

Installing Microsoft Azure Arc Agent

The next step is to install the Microsoft Azure Arc agent on your Windows 10 device.

Login in your Azure Subscription, if you don’t have one you can start here

Search for Azure Arc in your subscription.

Click on Servers and Click on Add.

Click on add a Single Server.
Click on Generate Script.

Prerequisites for the Azure Arc Agent.

Select your Azure Subscription and Resource Group
Choose your Region.
Operating System is Windows. ( your Windows10 device)
Click on Next.

You can add your TAG here.
More information about Azure Tags

Here you can download the Installation script or do a Copy of the Azure Arc Agent.

Open PowerShell ISE in Administrator mode.
Paste the Azure Arc Agent PowerShell Script.
Click on run.

When you see this message open your browser and go to
https://microsoft.com/devicelogin

Copy the Code in the last rule of PowerShell here and click on Next.

Enter your Azure Subscription account here and click on Next.

Connection is made with Azure you can close this screen.

Azure Arc Agent is connect with your Windows 10 Device.

Here you see my Azure Arc Enabled Machine.

Now your Windows 10 device, my Surface Book 3 is connected with Microsoft Azure Arc Services.

Register a Kubernetes Cluster with Azure Arc

The last step is to register your kubernetes Cluster with Microsoft Azure Arc Services.

Click on kubernetes Clusters on the left.
Click on Register a Kubernetes Cluster with Azure Arc.

The prerequisites to add your Kubernetes Cluster to Azure Arc

Select your Azure Subscription
Select your Resource Group
Give your Cluster a Name in Azure
Select Region.
Are you behind a Proxy Server? Yes or No

Here you can add your TAG to the Kubernetes Cluster.

The Next step is to run the Script, you can do that with PowerShell or Bash. I Did this via Azure CLI and with Helm 3.

Microsoft Azure CLI active with Helm 3

Copy the Bash commando into your Azure CLI like here.

This operation might take a couple of minutes.

Done, the Kubernetes Cluster is added to Azure Arc.

Dockkube was successfully connected to Azure.

Kubernetes Cluster with Azure Arc

Now you Have connected your Kubernetes Cluster to Azure Arc Services, you can start exploring the extensions :

Kubernetes Cluster – Azure Arc extensions

You can work with GitOps on your Kubernetes Cluster via Azure Arc Services

GitOps on your Kubernetes Cluster via Azure Arc.

More Features like Security, Monitoring, Automation :

Features for Kubernetes in Azure Arc Services.

Here you see in Visual Studio Code your Azure-Arc Helm Release.

Conclusion

“Learn how to write once and run anywhere using your preferred cloud-native application services. Ensure governance, compliance and security for your deployments, all through a single pane of glass management experience in Azure.”

With Microsoft Azure Arc Services you bring Azure Cloud Technology anywhere for your Apps, Containers, microservices.
I Hope this is a first start for exploring and testing your Hybrid Cloud solution. Wish you a lot of fun and happy coding 😉

 


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Dapr for .NET Developers E-book #microservices #dotnet #Dapr #Kubernetes #Azure #DevOps #developers

Dapr is an open source, portable, event-driven runtime that makes it easy for developers to build resilient, microservice, stateless and stateful applications that run on the cloud and edge. Dapr enables developers to focus on writing business logic and not solving distributed system challenges, thereby significantly improving their productivity, and reducing development time. Dapr lowers the bar for entry to build modern cloud native applications based on a microservices architecture and with this v1.0 release, Dapr applications can be deployed to self-hosted infrastructure or Kubernetes clusters in production scenarios.

Here you find an E-book about Dapr for .NET Developers 

Foreword by Mark Russinovich Azure CTO and Technical Fellow Microsoft

With the wave of cloud adoption well underway, there is a major shift happening towards “cloud native” development, often built with microservice-architectures. These microservices are both stateless and stateful, and run on the cloud and edge, embracing the diversity of languages and frameworks available today. This enterprise shift is driven by both the market forces of faster time to market, as well as the scale and efficiencies of building services for the cloud. Even before COVID-19, cloud adoption was accelerating for enterprises and developers were being asked to do even more to deliver on building these distributed system applications, and that has only accelerated since. Developers in enterprises seek to focus on business logic, while leaning on platforms to imbue their applications with scale, resiliency, maintainability, elasticity, and the other attributes of cloud-native architectures, which is why there is also shift towards serverless platforms that hide the underlying infrastructure. Developers should not be expected to become distributed systems experts. This is where Dapr steps in to help you, whether you are building on infrastructure such as Kubernetes, or on a serverless platform.

Dapr is designed as an enterprise, developer-focused, microservices programming model platform with the mantra “any language, any framework, run anywhere”. It makes building distributed applications easy and portable across any infrastructure, from public-cloud, through hierarchical edge, and even down to single node IoT devices.  It emerged from both our experiences building services in Azure as well as time spent working with customers building applications on Azure Kubernetes Service and Azure Service Fabric. Over and over, we saw common problems that they had to address. It became clear that there was a need to provide a “library” of common microservice best practices that developers could use, not only in new greenfield applications, but also to aid in the modernization of existing applications. In the containerized, distributed, and networked cloud native world, the sidecar model has emerged as the preferred approach, in the same way DLLs are preferred in the client/server generation. Using Dapr’s sidecar and APIs give you, as a developer, all the power of distributed systems functionality, with the ease of a single HTTP or gRPC local call.

To address the wide range of scenarios that developers face, Dapr provides features such as state management, service to service invocation, pub/sub and integration to external systems with I/O bindings, which are based on the triggers and bindings of Azure Functions. These in turn take advantage of Dapr’s component model which allows you to “swap out”, say different underlying state stores, without having to change any code, making code more portable, more flexible and allowing for experimentation of what best suits your needs. Developers don’t need to learn and incorporate service SDKs into their code, worry about authentication, secret management, retries or conditional code that targets specific deployment environments.

This book shows how Dapr reduces your development time and overall code maintenance by incrementally “Daperizing” the canonical .NET reference application, eShop. For example, in the original eShop implementation, significant amounts of code were written to abstract between Azure Service Bus and RabbitMQ for publishing events between services. All this code can be discarded and simply replaced with Dapr’s pub/sub API and component model which had an even wider range of pub/sub brokers, rather than just two. Dapr’s actor model, when used in the reworked eShop application, shows the ease of building long running, stateful, event driven, workflow applications with all the difficulties of concurrency and multi-threading removed. By the end of this book, you will see the drastic simplification that Dapr brings to your application development, and I firmly believe all developers embarking on a cloud native app building journey should leverage Dapr.

We publicly announced Dapr with the v0.1 release in Oct 2019 and now, a year and half later, I am thrilled to say that Dapr is ready for production usage with the v1.0 release. Getting Dapr to v1.0 has truly been a community effort. It has been amazing to see the open-source community coalesce around Dapr and grow since it was first announced – from 114 contributors in October 2019 to over 700 in early 2021 – a six-fold increase in 16 months! Contributions to the project have gone to every Dapr repo and have ranged from opening issues, commenting on feature proposals, providing samples, and of course contributing code. The parts of the project community members have contributed to the most include the Dapr runtime, docs, CLI, SDKs and the creation of a rich ecosystem of components. Maintaining this openness is critical to Dapr’s future.

Dapr is really just getting started, though, and you should expect to see more Dapr capabilities and more support for Dapr in Azure services. I hope that you will take advantage of Dapr to enable you to focus on your core business logic and accelerate your microservices development. I am are excited to have you join us in the Dapr community on this journey athttps://github.com/dapr/ and on Discord https://aka.ms/dapr-discord.

Modern distributed systems are complex. You start with small, loosely coupled, independently deployable services. These services cross process and server boundaries. They then consume different kinds of infrastructure backing services (databases, message brokers, key vaults). Finally, these disparate pieces compose together to form an application.

Mark Russinovich Azure CTO and Technical Fellow Microsoft

Thank you Author; Rob Vettor, Sander Molenkamp and Edwin van Wijk for this Awesome E-book 😉


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Running #Dapr in WSL2 Ubuntu 20-04 distro in #WindowsInsider Build 21277 RS and #VSCode

Working with Dapr in WSL2 Remote VSCode and Ubuntu 20.04 distro

Dapr is a portable, event-driven runtime that makes it easy for any developer to build resilient, stateless and stateful applications that run on the cloud and edge and embraces the diversity of languages and developer frameworks.

 

Developer language SDKs and frameworks

To make using Dapr more natural for different languages, it also includes language specific SDKs for Go, Java, JavaScript, .NET and Python. These SDKs expose the functionality in the Dapr building blocks, such as saving state, publishing an event or creating an actor, through a typed, language API rather than calling the http/gRPC API. This enables you to write a combination of stateless and stateful functions and actors all in the language of their choice. And because these SDKs share the Dapr runtime, you get cross-language actor and functions support.

SDKs

Dapr in Standalone version.

I’m using Windows Insider Build version 21277-RS with Docker for Windows Edge and Visual Studio Code.

Docker for Windows Edge Version Running.

Because Docker for Windows Edge support WSL2 Engine and Visual Studio Code too, brought me to an idea to build dapr into Ubuntu 20.04 WSL Distro on my Windows Insiders 21277 RS version on my Surface Book 3. There for you must activate the WSL2 integration with my default WSL distro Ubuntu-20.04.

Docker for Windows WSL 2 Integration.

In your Ubuntu-20.04 WSL2 version, you can install Dapr into your linux distro, more information you find here on dapr.io

Microsoft Windows Subsystem for Linux Installation Guide for Windows 10 with all kind of Linux distro’s 

Dapr init ( in the Ubuntu-20.04 WSL2 Linux distro )

Here you find the Dapr dev environment installation types for Dapr init, I did the standalone version. Dapr makes then the following containers :

Dapr Containers.

Then we have the following running :

  • Dapr Dashboard
  • Zipkin

Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in service architectures. Features include both the collection and lookup of this data.

Zipkin Traces

Dapr Dashboard

Now we have Dapr running in the WSL2 Ubuntu-20.04 distro, you can use Visual Studio Code on Windows Insiders using Remote WSL and work with your favourite dapr SDK like the list above 😉

Dapr Extension in VSCode

From here you can work with your dapr application.

In this guide dapr is running with Docker containers, but you can also install it on Kubernetes or K8s, AKS, Azure any where, see this overview :

Dapr with Kubenetes Containers.

Dapr Overview.

Important Note : Dapr is now production ready with version 1.0 ! Developers, DevOps, AzOps, you can start with it and Build and Test your own microservices and Container apps !  Hope you are having fun with it too 😉

 

 


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Deploy a 10 – Node Azure Service Fabric Standalone Cluster #microservices #Containers

Azure Service Fabric Standalone Cluster

Earlier I wrote a blogpost about Microsoft Azure Service Fabric Standalone Cluster for Dev testing.
This was 5 – Node Azure Service Fabric Cluster locally installed, but now I like to have a bigger ASF Cluster on my
Windows Server 2019 for testing with Visual Studio.

When you have downloaded the Microsoft Azure Service Fabric SDK into a directory

Here you see the JSON Cluster config files

I used the same JSON template for deploying a Azure Service Fabric Standalone Cluster :

Creating Cluster but with a Changed JSON Template.

Here you find the 10 – Node Azure Service Fabric Cluster Config file on Github

10 – Node Microsoft Azure Service Fabric Standalone Cluster for Dev Testing

Important : Use this Azure Service Fabric Standalone Cluster only for Learning and testing and not for production!

Here you find more information and documentation about Azure Service Fabric for Production.


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Microsoft Azure Service Fabric Standalone Cluster for Testing #microservices #Containers #Apps

Microsoft Azure Service Fabric standalone

Azure Service Fabric is a distributed systems platform that makes it easy to package, deploy, and manage scalable and reliable microservices and containers.

To build and run Azure Service Fabric applications on your Windows development machine, install the Service Fabric runtime, SDK, and tools. You also need to enable execution of the Windows PowerShell scripts included in the SDK.

I have installed the latest version :

  • Service Fabric SDK and Tools 4.1.409
  • Service Fabric runtime 7.1.409

here you find more information about installing Azure Service Fabric Standalone version for testing
I have installed the Azure Service Fabric Cluster on my Windows10 Machine for testing only.

When you want to great your own Azure Service Fabric Cluster for Production, you have to prepare your self and making a plan before you build.

When you have your Azure Service Fabric Standalone Cluster running, you want to deploy your microservices, apps or containers on it and test your solution. In the following steps I deploy with Visual Studio a Web App to Azure Service Fabric Cluster Standalone version 7.1.409

Here is a Github Sample for Azure Service Fabric.

git clone https://github.com/Azure-Samples/service-fabric-dotnet-quickstart

Here you have your Clone from Github.

To deploy this App to the Azure Service Fabric Cluster we use Microsoft Visual Studio

Once the application is downloaded, you can deploy it to a cluster directly from Visual Studio.

  1. Open Visual Studio
  2. Select File > Open
  3. Navigate to the folder you cloned the git repository to, and select Voting.sln
  4. Right-click on the Voting application project in the Solution Explorer and choose Publish

Click on Publish.

Select connection Endpoint Local Cluster and click on Publish.

The Web App is Published to the Azure Service Fabric Standalone Cluster.

When you open the Azure Service Fabric Explorer you will see your App Running

This sample is for testing only and is not secure for production, just to learn how it works 😉

Of course you can also deploy Containers with Visual Studio to your Azure Service Fabric Standalone Cluster.

Deploying Service Fabric Container via Visual Studio.

More Azure Service Fabric information

Here you find the Azure Service Fabric documentation

Here you find the Microsoft Azure Service Fabric website

Here you find the Azure Service Fabric Tech Community Blog

Happy Testing your Apps, microservices, and Containers.

Join the Containers in the Cloud LinkedIn Community Group

 


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Kubernetes Up and Running Second Edition Ebook

 

Kubernetes Up & Running Second Edition Ebook

Whether you are new to distributed systems or have been deploying cloud-native systems for years, containers and Kubernetes can help you achieve new levels of velocity, agility, reliability, and efficiency. This book describes the Kubernetes cluster orchestrator and how its tools and APIs can be used to improve the development, delivery, and maintenance of distributed applications. Though no previous experience with Kubernetes is assumed, to make maximal use of the book you should be comfortable building and deploying server-based applications. Familiarity with concepts like load balancers and network storage will be useful, though not required. Likewise, experience with Linux, Linux containers, and Docker, though not essential, will help you make the most of this book.


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Installing and Maintaining #Azure Kubernetes Cluster #AKS #ContainerInsights #AzureDevOps

Start Creating Azure Kubernetes Cluster for your Containers.

Managed Azure Kubernetes Service (AKS) makes deploying and managing containerized applications easy. It offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. As a hosted Kubernetes service, Azure handles critical tasks like health monitoring and maintenance for you. The Kubernetes masters are managed by Azure. You only manage and maintain the agent nodes. As a managed Kubernetes service, AKS is free – you only pay for the agent nodes within your clusters, not for the masters. In the following steps you can see the different ways for creating Azure Kubernetes Cluster via the Azure Portal, or via Azure Cloud Shell, or via Azure Resource Template. When the Microsoft Azure Kubernetes Cluster is running, then I will explain the different ways for deploying container workloads on AKS. When your workload is running on Azure Kubernetes Services, you also have to monitor your Container workloads with Azure Monitor Container Insights to keep in Controle. Let’s start with installing Azure Kubernetes Services (AKS)

Installing Azure Kubernetes Cluster via the Portal.

To begin you need of course a Microsoft Azure Subscription and you can start for free here

Basics information of the Azure Kubernetes Cluster

To Create the Azure Kubernetes Cluster, you have to follow these steps and type the right information in the Portal:

  1. Basics
  2. Scale
  3. Authentication
  4. Networking
  5. Monitoring
  6. Tags
  7. Review + Create

At the basics screen you select the right Azure Subscription and the Resource Group. You can create a New Resource Group or one you already made.
At Cluster details, you give your Cluster a name and select the Kubernetes version.

Here you select the Kubernetes Node size for your Container workload and the number of nodes.
You can start a Cluster already with One node, but choose to start with the right size for your workloads.
When you click on Change size, you can choose your nodes to do the job. 😉

Select the right Size node

Then we go to step 2 and that is Scale.

2. Scale options in Azure Kubernetes Cluster

Here you have two options :

  1. Virtual Nodes
  2. VM Scale sets (Preview)

To quickly deploy workloads in an Azure Kubernetes Service (AKS) cluster, you can use virtual nodes. With virtual nodes, you have fast provisioning of pods, and only pay per second for their execution time. In a scaling scenario, you don’t need to wait for the Kubernetes cluster autoscaler to deploy VM compute nodes to run the additional pods. Virtual nodes are only supported with Linux pods and nodes. More information here about Virtual Nodes

To create an AKS cluster that can use multiple node pools, first enable two feature flags on your subscription. Multi-node pool clusters use a virtual machine scale set (VMSS) to manage the deployment and configuration of the Kubernetes nodes. With this Preview feature you can run Linux Containers and Windows Containers on the same Cluster. More information here about VM Scale sets (Preview)

3, Authentication

The service principal is needed to dynamically create and manage other Azure resources such as an Azure load balancer or container registry (ACR). To interact with Azure APIs, an AKS cluster requires an Azure Active Directory (AD) service principal. More information about the Service Principal can be found here

Azure Kubernetes Service (AKS) can be configured to use Azure Active Directory (Azure AD) for user authentication. In this configuration, you can sign in to an AKS cluster by using your Azure AD authentication token.
Cluster administrators can configure Kubernetes role-based access control (RBAC) based on a user’s identity or directory group membership. More information about RBAC for AKS

4. Networking

Configuring the virtual Networks for your Azure Kubernetes Cluster is important for the right IP range but later on also for the Network Security Groups (NSG).

Here you see an example of the Kubernetes NSG which is connected to the Internet by Default after installation, you can deep dive into security but be careful which settings you do here because Microsoft resources must have access to service the Azure Kubernetes Cluster.

NSG created after installation is finished

NSG Rule set Inbound and outbound

In a container-based microservices approach to application development, application components must work together to process their tasks. Kubernetes provides various resources that enable this application communication. You can connect to and expose applications internally or externally. To build highly available applications, you can load balance your applications. More complex applications may require configuration of ingress traffic for SSL/TLS termination or routing of multiple components. For security reasons, you may also need to restrict the flow of network traffic into or between pods and nodes.

Best practices for network connectivity and security in Azure Kubernetes Service (AKS):

Here is more information about networking and Security for AKS

5. Monitoring

Keep Azure Monitoring Enabled and Connect to your Log Analytics workspace or create a new workspace for Container monitoring of your Azure Kubernetes Cluster.

Azure Monitor for containers is a feature designed to monitor the performance of container workloads deployed to either Azure Container Instances or managed Kubernetes clusters hosted on Azure Kubernetes Service (AKS). Monitoring your containers is critical, especially when you’re running a production cluster, at scale, with multiple applications.

Azure Monitor for containers gives you performance visibility by collecting memory and processor metrics from controllers, nodes, and containers that are available in Kubernetes through the Metrics API. Container logs are also collected. After you enable monitoring from Kubernetes clusters, metrics and logs are automatically collected for you through a containerized version of the Log Analytics agent for Linux. Metrics are written to the metrics store and log data is written to the logs store associated with your Log Analytics workspace.

6. Tags

When you build more Azure Kubernetes Clusters for different departments or teams you can TAG your Clusters for organizing your billing and security for example. Here you find more information about tagging.

After this you click on the last step Review and Create
The Azure portal will do a validation of your Azure Kubernetes Cluster settings, and when it’s validated you hit Create. But when you want more Automation, you can download the JSON ARM template first and use that.

Installing Azure Kubernetes Cluster via Cloud Shell

Azure Cloud Shell AKS CLI

Azure hosts Azure Cloud Shell, an interactive shell environment that you can use through your browser. Cloud Shell lets you use either bash or PowerShell to work with Azure services. You can use the Cloud Shell pre-installed commands to run the code in this article without having to install anything on your local environment.

Here you see an Example of AKS CLI with Auto Scaler with max count of nodes 😉

Installing Azure Kubernetes Cluster via Template

Create Azure Kubernetes Cluster via Template in the Portal

Here you find an Example at GitHub for a Template deployment

Now you have your Microsoft Azure Kubernetes Cluster (AKS) running in the Cloud, you want to deploy your Container workloads on the Cluster. In the following steps you see different deployments.

Deploy Container workload with Azure DevOps Project

Deployment Center

First you select your repository where your source code is of your workload.

Set the information right and click Next.

Simple example Click Next

Create a Container Registry.

Building Pipeline with Azure DevOps.

Here you see the Building in Microsoft Azure DevOps.

Build, test, and deploy in any language, to any cloud—or on-premises. Run in parallel on Linux, macOS, and Windows, and deploy containers to individual hosts or Kubernetes.

Here you find all the information about Microsoft Azure DevOps for your workloads, code and Deployments.

Deploying Container workload completed with Azure DevOps.

 

Deploy Container Workloads via Visual Studio Code

When you download and install Visual Studio Code on your computer, you can install the Azure Kubernetes extension for VSCode.

Install Kubernetes extension for VSCode

VSCode with Kubernetes Extension

Here you see Microsoft Visual Studio Code connected with my Azure subscription where my Azure Kubernetes Cluster is running. With the standard Helm Repository packages for deployment to your AKS Cluster. Here you see a WordPress yaml file which I deployed to the Kubernetes Cluster on Azure.

Just Select your Package and Install on Azure Kubernetes.

From here you can into the Container and read the logs.

I’m using Visual Studio Code a lot for Azure Kubernetes but also for Docker Containers and images.
Making Azure ARM JSON templates and this great for Infrastructure as Code.

 

Azure Monitoring with Container Insights

In One Dashboard you can see the Status of all your Clusters

 

Azure Monitor Container Insights Live View

Because we installed Azure Monitor for Containers on the Microsoft Azure Kubernetes Cluster, we can live see what is happening inside the Kubernetes Cluster with the containers. This is a great feature when you have a issue with a Container for troubleshooting fast and see what is happening.

Conclusion

Microsoft Azure Kubernetes Cluster is fast and easy to manage. You can upgrade your Cluster without downtime of your Container workload. With Azure Monitor for Containers you can see what’s happening inside the container and you can set alerts when something went wrong. This keeps you in Controle of the solution. With Deployment center alias Azure DevOps Projects you can deploy your workload via Azure DevOps Pipeline and work on versioning, testplans, Azure DevOps repo and work together with a Team on the following releases. Working with Azure Kubernetes Multi node pools with Linux and Windows on the same Cluster is possible. Try it yourself and start with a Proof of Concept for your Business.

JOIN Containers in the Cloud Community Group on LinkedIn


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Microsoft #Azure Service Fabric Mesh for your #Microservices and #Container Apps in the #Cloud

Microsoft Service Fabric Mesh

Azure Service Fabric Mesh is a fully managed service that enables developers to deploy microservices applications without managing virtual machines, storage, or networking. Applications hosted on Service Fabric Mesh run and scale without you worrying about the infrastructure powering it. Service Fabric Mesh consists of clusters of thousands of machines. All cluster operations are hidden from the developer. Simply upload your code and specify resources you need, availability requirements, and resource limits. Service Fabric Mesh automatically allocates the infrastructure and handles infrastructure failures, making sure your applications are highly available. You only need to care about the health and responsiveness of your application-not the infrastructure.

With Service Fabric Mesh you can:

  • “Lift and shift” existing applications into containers to modernize and run your current applications at scale.
  • Build and deploy new microservices applications at scale in Azure. Integrate with other Azure services or existing applications running in containers. Each microservice is part of a secure, network isolated application with resource governance policies defined for CPU cores, memory, disk space, and more.
  • Integrate with and extend existing applications without making changes to those applications. Use your own virtual network to connect existing application to the new application.
  • Modernize your existing Cloud Services applications by migrating to Service Fabric Mesh.

Build high-availability into your application architecture by co-locating your compute, storage, networking, and data resources within a zone and replicating in other zones. Azure services that support Availability Zones fall into two categories:

  • Zonal services – you pin the resource to a specific zone (for example, virtual machines, managed disks, IP addresses)
  • Zone-redundant services – platform replicates automatically across zones (for example, zone-redundant storage, SQL Database).

To achieve comprehensive business continuity on Azure, build your application architecture using the combination of Availability Zones with Azure region pairs. You can synchronously replicate your applications and data using Availability Zones within an Azure region for high-availability and asynchronously replicate across Azure regions for disaster recovery protection.

Store state in an Azure Service Fabric Mesh application by mounting an Azure Files based volume inside the container

Twitter AMA on Service Fabric Mesh :

The Service Fabric team will be hosting an Ask Me Anything (AMA) (more like “ask us anything”!) session for Service Fabric Mesh on Twitter on Tuesday, October 30thfrom 9am to 10:30am PST. Tweet to @servicefabric or @AzureSupport using #SFMeshAMA with your questions on Mesh and Service Fabric. More information here

More information about Azure Service Fabric Mesh :

Microsoft Azure Service Fabric Mesh LAB on Github

Get started with Microsoft Azure Service Fabric for your Microservices and Container Apps

Service Fabric Microsoft Ignite 2018 sessions

JOIN Containers in the Cloud Community Group on LinkedIn here


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Installing #Azure Service Fabric Cluster on Windows Server 2019 Insiders #Containers #Winserv

Microsoft Azure Service Fabric Cluster

Azure Service Fabric is a distributed systems platform that makes it easy to package, deploy, and manage scalable and reliable microservices and containers. Service Fabric also addresses the significant challenges in developing and managing cloud native applications. Developers and administrators can avoid complex infrastructure problems and focus on implementing mission-critical, demanding workloads that are scalable, reliable, and manageable. Service Fabric represents the next-generation platform for building and managing these enterprise-class, tier-1, cloud-scale applications running in containers.

In the following Step-by-Step Guide I created a Standalone Microsoft Azure Service Fabric Cluster
on Windows Server 2019 Insiders Preview for DevOps testing :

First I downloaded the Contents of Service Fabric Standalone package for Windows Server here

Several sample cluster configuration files are installed with the setup package. ClusterConfig.Unsecure.DevCluster.json is the simplest cluster configuration: an unsecure, three-node cluster running on a single computer. Other config files describe single or multi-machine clusters secured with X.509 certificates or Windows security. You don’t need to modify any of the default config settings for this tutorial, but look through the config file and get familiar with the settings.

I made the Unsecure three-node Cluster running on Windows Server 2019 Insiders Preview in my MVPLAB.

 

Open Powershell in Administrator modus and run the Script :

.\CreateServiceFabricCluster.ps1 -ClusterConfigFilePath .\ClusterConfig.Unsecure.DevCluster.json -AcceptEULA

Connect-ServiceFabricCluster

 

Service Fabric Explorer (SFX) is an open-source tool for inspecting and managing Azure Service Fabric clusters. Service Fabric Explorer is a desktop application for Windows, macOS and Linux.

I Installed Azure Service Fabric Explorer to visualize the Cluster.

Here we got Azure Service Fabric 3-Node Cluster running on Windows Server 2019 Insiders

Azure Service Fabric CLI

The Azure Service Fabric command-line interface (CLI) is a command-line utility for interacting with and managing Service Fabric entities. The Service Fabric CLI can be used with either Windows or Linux clusters. The Service Fabric CLI runs on any platform where Python is supported.

Prior to installation, make sure your environment has both Python and pip installed.
The CLI supports Python versions 2.7, 3.5, 3.6, and 3.7. Python 3.x is the recommended version, since Python 2.7 will reach end of support soon.

You can download the latest Python version here

Check the Python version and the Pip version by typing :

python –version
Pip –version

The Pip version which is delivered via Python has to be updated with the following command :

python -m pip install –upgrade pip

We now have pip version 18.0 instead of 10.0.1

Installing Service Fabric CLI by command :

pip install -I sfctl

Done ! Service Fabric CLI is installed on my Windows 10 Surface.

sfctl -h 

Now we have installed Microsoft Azure Service Fabric Cluster on Windows Server 2019 Insiders Preview and the Service Fabric CLI on Windows 10, we now can connect to the 3-node Fabric Cluster via CLI.
Because we are working under Windows 10 and not on the host itself we have to set an endpoint connection :

sfctl cluster select –endpoint http://192.168.2.15:19080

sfctl cluster health

sfctl node list

Microsoft Visual Studio 2017 Enterprise and Service Fabric SDK

As a Developer or DevOps you like to work from Microsoft Visual Studio to deploy your Apps, Microservices or Containers to the Azure Service Fabric Cluster.

You need to install the Service Fabric SDK in Visual Studio before you can deploy :

Select Service Fabric Application at New Project

Visual Studio 2017 Enterprise : Service Fabric SDK must be installed

Installing Microsoft Azure Service Fabric SDK

Done.

Now you can make your Service Fabric Container.

Happy Developing 😉

More information on Microsoft Azure Service Fabric Cluster :

Service Fabric on GitHub

Add or remove nodes to a standalone Service Fabric cluster running on Windows Server :

Scaling your Azure Service Fabric Cluster

More info :

Microsoft Azure Service Fabric documentation

Microsoft Azure Service Fabric Cluster Learning Path


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A Great #Microservices E-book about Architecture for Containerized #dotnet Apps #Docker #Kubernetes #Containers

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