Cloud and Datacenter Management Blog

Microsoft Hybrid Cloud blogsite about Management


Leave a comment

#Azure IoT Pipeline with Microsoft #AzureDevOps Project #IoT #Code #Apps #SmartCities

Azure IoT Edge – Hub with Azure DevOps Pipeline

Configure continuous integration (CI) and continuous delivery (CD) for your IoT Edge application with DevOps Projects. DevOps Projects simplifies the initial configuration of a build and release pipeline in Azure Pipelines.

In the following steps you can see how easy it is to build your Continuous integration and continuous deployment to Azure IoT Edge with DevOps Project :

Select Simple IoT

Click on Next.

From here you set your Azure DevOps organization to your Azure IoT Hub. Click on additional settings

In additional settings you can set :

  • Azure Resource Group
  • Location ( region)
  • Container Registry
  • Container Registry name
  • Container registry SKU
  • Container Location
  • IoT Hub of Edge Devices
  • IoT Hub Location

Select Container Registry Plan

Azure Container Registry allows you to store images for all types of container deployments including DC/OS, Docker Swarm, Kubernetes, and Azure services such as App Service, Batch, Service Fabric, and others. Your DevOps team can manage the configuration of apps isolated from the configuration of the hosting environment.
More information about Azure Container Registry and pricing

Azure DevOps Project will do the rest of the deployment.

Of course Infrastructure as Code (IaC) is possible by ARM JSON Template.

Save the template for later.

here you got your ARM Templates.

Later you will see when you complete the deployment, that your JSON ARM template is in Azure DevOps Repo.
You can connect your Azure DevOps Repo via the portal but also via Visual Studio and Visual Studio Code.

The resources coming into myiotpipeline-rg

MyIOTPipeline-IoTHub is created.

MyIOTPipelineACR Container Registry is created.

MyIOTPipeline with Azure DevOps is created 🙂

Your Continuous integration and continuous deployment to Azure IoT Edge is deployed and active. Now you have your Azure Pipeline in place to continuously update your IoT Device App. From here you can go to Azure DevOps Project Homepage.

Via Agent phase you can see all the jobs of the deployment.

Azure DevOps Pipeline Release

here we have Azure DevOps Repos

Azure DevOps Services includes free unlimited private Git repos, so Azure Repos is easy to try out. Git is the most commonly used version control system today and is quickly becoming the standard for version control. Git is a distributed version control system, meaning that your local copy of code is a complete version control repository. These fully functional local repositories make it easy to work offline or remotely. You commit your work locally, and then sync your copy of the repository with the copy on the server.
Git in Azure Repos is standard Git. You can use the clients and tools of your choice, such as Git for Windows, Mac, partners’ Git services, and tools such as Visual Studio and Visual Studio Code.

All the Azure Resources for the IoT Edge Pipeline with Azure DevOps.

When you have your Azure DevOps Pipeline with IoT Edge devices running, you can monitor your pipeline with Analytics inside Azure DevOps.

Click Next.

Click on Install Analytics.

Select the right Azure DevOps Organization for your IoT Edge Pipeline.

Done !

 

Analytics is now active, you can make automated test plans in Azure DevOps and see the results via Analytics.

Azure DevOps Overview Dashboard.

There are a lot of predefined Analytics Views for you shared.

An Analytics view provides a simplified way to specify the filter criteria for a Power BI report based on the Analytics Service data store. The Analytics Service provides the reporting platform for Azure DevOps.
More information about Analytics in Azure DevOps here

Easy to start with Powerbi and Azure DevOps Connector.

Planned manual testing
Plan, execute, and track scripted tests with actionable defects and end-to-end traceability. Assess quality throughout the development lifecycle by testing your desktop or web applications.

More information about making your testplan for your IoT Edge Devices Azure DevOps Pipeline

Conclusion :

When you connect Microsoft Azure IoT Edge – HUB with your Internet of Things Devices and combine it with Microsoft Azure DevOps Team to develop your Azure IoT Pipeline, then you are in fully control of Continuous integration and continuous deployment to Azure IoT Edge. From here you can make your innovations and Intelligent Cloud & Edge with Artificial Intelligence and Machine Learning to your Devices. You will see that this combination will be Awesome for HealthCare, Smart Cities, Smart Buildings, Infrastructure, and the Tech Industry.

In this Microsoft article, you learn how to use the built-in Azure IoT Edge tasks for Azure Pipelines to create two pipelines for your IoT Edge solution. The first takes your code and builds the solution, pushing your module images to your container registry and creating a deployment manifest. The second deploys your modules to targeted IoT Edge devices.

Join the Azure DevOps Community on LinkedIn

Join Containers in the Cloud Community on LinkedIn

Join Microsoft Azure Monitor & Security for Hybrid IT Community on LinkedIn


Leave a comment

Enhancing Microsoft #Security using Artificial Intelligence E-book #AI #Azure #MachineLearning

At the Center of intelligent security management is the concept of working smarter, not harder. However, this is a significant undertaking when you consider the ever-evolving landscape of threats and security challenges, combined with the myriad of devices, apps, and user scenarios. In this e-book, learn how you can intelligently detect, protect, and respond to threats by leveraging the strong integration between Microsoft security solutions and our partners.
Read the full e-book to learn how Microsoft is using artificial intelligence (AI) in security features like:

  • Windows Hello
  • Azure Active Directory
  • Azure Advanced Threat Protection
  • Windows Defender SmartScreen
  • Windows Defender Network Protection
  • Exchange Online Protection and more…

You can download Enhancing Microsoft Security using Artificial Intelligence E-book here


Leave a comment

Microsoft Azure Machine Learning Cloud Platform with Free Ebook #Azure #MachineLearning

Azure Machine Learn

Blog Logo Azure MachineThe Microsoft Azure Machine Learning cloud platform provides simplified yet powerful data management, transformation and machine learning tools. R language scripts integrate with built in Azure ML modules to extend the platform. Additionally, models running in Azure ML can be published as web services.

You will be provided information on how to perform data science tasks including, data management, data transformation, and machine learning in the Azure ML cloud environment. You will learn:

  • Data management with Azure ML.
  • Data transformation with Azure ML and R.
  • Data I/O between Azure ML and the R Scripts.
  • R graphics with Azure ML.
  • Building and evaluating machine learning models with Azure ML and R.
  • Publishing Azure ML models as a web service.


Free tier Azure ML accounts are now available with a Microsoft ID at

https://studio.azureml.net/Home/Free.

Azure Machine Learning Ebook

Here you can sign up for a Free Ebook :

 Azure-Machine-Learning-351x185
Microsoft Azure Machine Learning BlogSite

Microsoft Azure Machine Learning on TechNet Wiki