Building and Deploying Micro Services with Azure Kubernetes Service (AKS) and Azure DevOps Part-1

All parts are now available:
Part-1: Explain in details about Docker and setup local and development environments for Docker applications.
Part-2: Explain in details about Inner-loop development workflow for both Docker and Database applications.
Part-3: Explain in details about Outer-loop DevOps workflow for a Database application.
Part-4: Explain in details about creating Azure Kubernetes Service (AKS), Azure Container Registry (ACR) through the Azure CLI and Outer-loop DevOps workflow for a Docker applications.

Overview

This blog outlines the process to compile a Database application and Deploy into Azure SQL Database and also compile Docker-based ASP.NET Core Web application, API application as well as deploy web and API applications into to a Kubernetes cluster running on Azure Kubernetes Service (AKS) using the Azure DevOps.

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Introduction to Containers and Docker

  • Introduction to Containers
  • Containers vs VM’s
  • What is Docker?
  • Docker Benefits
  • Docker Architecture and Docker Terminology

Containers

  • Containerization is an approach to software development in which an application or service, its dependencies, and its configuration are packaged together as a container image. You then can test the containerized application as a unit and deploy it as a container image instance to the host operating system.
  • Placing software into containers makes it possible for developers and IT professionals to deploy those containers across environments with little or no modification.
  • Containers also isolate applications from one another on a shared operating system (OS). Containerized applications run on top of a container host, which in turn runs on the OS (Linux or Windows). Thus, containers have a significantly smaller footprint than virtual machine (VM) images.
  • Containers offer the benefits of isolation, portability, agility, scalability, and control across the entire application life cycle workflow. The most important benefit is the isolation provided between Dev and Ops.

Containers vs VM’s

Containers are lightweight because they don’t need the extra load of a hypervisor, but run directly within the host machine’s kernel. This means you can run more containers on a given hardware combination than if you were using virtual machines. You can even run Docker containers within host machines that are actually virtual machines!

Virtual machines include the application, the required libraries/binaries, and a full guest operating system. Full virtualization is a lot heavier than containerization.

Containers include the application and all of its dependencies but share the OS kernel with other containers, running as isolated processes in user space on the host operating system (except in “Hyper-V containers” where each container runs inside of a special virtual machine per container).

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What is Docker?

  • Docker is an open platform for developing, shipping, and running applications.
  • Docker enables you to separate your applications from your infrastructure so you can deliver software quickly.
  • With Docker, you can manage your infrastructure in the same ways you manage your applications.
  • By taking advantage of Docker’s methodologies for shipping, testing, and deploying code quickly, you can significantly reduce the delay between writing code and running it in production.
  • The Docker platform uses the Docker Engine to quickly build and package apps as Docker images created using files written in the Dockerfile format that then is deployed and run in a layered container

Docker Benefits

Fast, consistent delivery of your applications

Docker streamlines the development lifecycle by allowing developers to work in standardized environments using local containers which provide your applications and services. Containers are great for continuous integration and continuous delivery (CI/CD) workflows.

Consider the following example scenario:

  1. Your developers write code locally and share their work with their colleagues using Docker containers.
  2. They use Docker to push their applications into a test environment and execute automated and manual tests.
  3. When developers find bugs, they can fix them in the development environment and redeploy them to the test environment for testing and validation.
  4. When testing is complete, getting the fix to the customer is as simple as pushing the updated image to the production environment.

Running more workloads on the same hardware:

Docker is lightweight and fast. It provides a viable, cost-effective alternative to hypervisor-based virtual machines, so you can use more of your compute capacity to achieve your business goals.

Docker is perfect for high density environments and for small and medium deployments where you need to do more with fewer resources.

Docker Architecture and Docker Terminology

Docker Engine is a client-server application with these major components:

  • A server which is a type of long-running program called a daemon process.
  • A REST API which specifies interfaces that programs can use to talk to the daemon and instruct it what to do.
  • A command line interface (CLI) client (the Docker command).

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Docker Daemon:

  • The Docker daemon (dockerd) listens for Docker API requests and manages Docker objects such as images, containers, networks, and volumes.
  • A daemon can also communicate with other daemons to manage Docker services.

Docker client:

  • The Docker client (docker) is the primary way that many Docker users interact with Docker.
  • When you use commands such as docker run, the client sends these commands to Docker Daemon, which carries them out.
  • The Docker client and daemon can run on the same system, or you can connect a Docker client to a remote Docker daemon.
  • The Docker client and daemon communicate using a REST API, over sockets or a network interface.
  • The Docker client can communicate with more than one daemon.

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Basic Docker Definitions

The following are the basic definitions anyone needs to understand before getting deeper into Docker.

Docker Image:

  • A package with all of the dependencies and information needed to create a container. An image includes all of the dependencies (such as frameworks) plus deployment and configuration to be used by a container runtime.
  • Usually, an image derives from multiple base images that are layers stacked one atop the other to form the container’s file system.
  • An image is immutable after it has been created.
        • Docker image containers can run natively on Linux and Windows.
            1. Windows images can run only on Windows host.
            2. Linux images can run only on Linux hosts, meaning a host server or a VM.
            3. Developers who work on Windows can create images for either Linux or Windows     Containers.

Container:

  • An instance of an image is called a container.
    • The container or instance of a Docker image will contain the following components:
          1. An operating system selection (for example, a Linux distribution or Windows)
          2. Files added by the developer (for example, app binaries)
          3. Configuration (for example, environment settings and dependencies)
          4. Instructions for what processes to run by Docker
            • A container represents a runtime for a single application, process, or service. It consists of the contents of a Docker image, a runtime environment, and a standard set of instructions.
            • You can create, start, stop, move, or delete a container using the Docker API or CLI.
            • When scaling a service, you create multiple instances of a container from the same image. Or, a batch job can create multiple containers from the same image, passing different parameters to each instance.

Tag:

  • A mark or label that you can apply to images so that different images or versions of the same image (depending on the version number or the destination environment) can be identified.

Dockerfile

  • A text file that contains instructions for how to build a Docker image.

Build

  • The action of building a container image based on the information and context provided by its Dockerfile as well as additional files in the folder where the image is built.
  • You can build images by using the Docker docker build command.

Repository (also known as repo)

  • A collection of related Docker images labeled with a tag that indicates the image version.
  • Some repositories contain multiple variants of a specific image, such as an image containing SDKs (heavier), an image containing only runtimes (lighter), and so on. Those variants can be marked with tags.
  • A single repository can contain platform variants, such as a Linux image and a Windows image.

Registry

  • A service that provides access to repositories.
  • The default registry for most public images is Docker Hub (owned by Docker as an organization).
  • A registry usually contains repositories from multiple teams.
  • Companies often have private registries to store and manage images that they’ve created.
  • Azure Container Registry is another example.

Docker Hub

  • A public registry to upload images and work with them.
  • Docker Hub provides Docker image hosting, public or private registries, build triggers and web hooks, and integration with GitHub and Bitbucket.

Azure Container Registry

  • A public resource for working with Docker images and its components in Azure.
  • This provides a registry that is close to your deployments in Azure and that gives you control over access, making it possible to use your Azure Active Directory groups and permissions.

Docker Trusted Registry (DTR)

  • A Docker registry service (from Docker) that you can install on-premises so that it resides within the organization’s datacenter and network. It is convenient for private images that should be managed within the enterprise. Docker Trusted Registry is included as part of the Docker Datacenter product. For more information, go to https://docs.docker.com/docker-trusted-registry/overview/.

Compose

  • A command-line tool and YAML file format with metadata for defining and running multi-container applications.
  • You define a single application based on multiple images with one or more .yml files that can override values depending on the environment.
  • After you have created the definitions, you can deploy the entire multi-container application by using a single command (docker-compose up) that creates a container per image on the Docker host.

Cluster

  • A collection of Docker hosts exposed as if they were a single virtual Docker host so that the application can scale to multiple instances of the services spread across multiple hosts within the cluster.
  • You can create Docker clusters by using Docker Swarm, Mesosphere DC/OS, Kubernetes, and Azure Service Fabric. (If you use Docker Swarm for managing a cluster, you typically refer to the cluster as a swarm instead of a cluster.)

Orchestrator

  • A tool that simplifies management of clusters and Docker hosts.
  • Using orchestrators, you can manage their images, containers, and hosts through a CLI or a graphical user interface.
  • You can manage container networking, configurations, load balancing, service discovery, high availability, Docker host configuration, and more.
  • An orchestrator is responsible for running, distributing, scaling, and healing workloads across a collection of nodes.
  • Typically, orchestrator products are the same products that provide cluster infrastructure, like Mesosphere DC/OS, Kubernetes, Docker Swarm, and Azure Service Fabric.

Docker Community Edition (CE)

  • Development tools for Windows and mac OS for building, running, and testing containers locally.
  • Docker CE for Windows provides development environments for both Linux and Windows Containers.
  • The Linux Docker host on Windows is based on a Hyper-V VM. The host for Windows Containers is directly based on Windows.
  • Docker CE for Mac is based on the Apple Hypervisor framework and the xhyve hypervisor, which provides a Linux Docker host VM on Mac OS X.
  • Docker CE for Windows and for Mac replaces Docker Toolbox, which was based on Oracle VirtualBox.

Docker Enterprise Edition

  • It is designed for enterprise development and is used by IT teams who build, ship, and run large business-critical applications in production.

Basic Docker taxonomy: containers, images, and registries

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Introduction to the Docker application lifecycle

The lifecycle of containerized applications is like a journey which starts with the developer. The developer chooses and begins with containers and Docker because it eliminates frictions in deployments and with IT Operations, which ultimately helps them to be more agile, more productive end-to-end, faster.

Picture1

Then by the very nature of the Containers and Docker technology, developers are able to easily share their software and dependencies with IT Operations and production environments while eliminating the typical “it works on my machine” excuse.

Containers solve application conflicts between different environments. Indirectly, Containers and Docker bring developers and IT Ops closer together. It makes easier for them to collaborate effectively.

With Docker Containers, developers own what’s inside the container (application/service and dependencies to frameworks/components) and how the containers/services behave together as an application composed by a collection of services.

The interdependencies of the multiple containers are defined with a docker-compose.yml file, or what could be called a deployment manifest.

Meanwhile, IT Operation teams (IT Pros and IT management) can focus on the management of production environments, infrastructure, and scalability, monitoring and ultimately making sure the applications are delivering right for the end-users, without having to know the contents of the various containers. Hence the “container” name because of the analogy to shipping containers in real-life. In a similar way than the shipping company gets the contents from a-b without knowing or caring about the contents, in the same way developers own the contents within a container.

Developers on the left of the above image, are writing code and running their code in Docker containers locally using Docker for Windows/Linux. They define their operating environment with a dockerfile that specifies the base OS they run on, and the build steps for building their code into a Docker image.

They define how the one or more images will inter-operate using a deployment manifest like a docker-compose.yml file. As they complete their local development, they push their application code plus the Docker configuration files to the code repository of their choice (i.e. Git repos).

The DevOps pillar defines the build-CI-pipelines using the dockerfile provided in the code repo. The CI system pulls the base container images from the Docker registries they’ve configured and builds the Docker images. The images are then validated and pushed to the Docker registry used for the deployments to multiple environments.

Operation teams on the right of the above image, are managing deployed applications and infrastructure in production while monitoring the environment and applications so they provide feedback and insights to the development team about how the application must be improved. Container apps are typically run in production using Container Orchestrators.

Introduction to a generic E2E Docker application lifecycle workflow

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Benefits from DevOps for containerized applications

The most important benefits provided by a solid DevOps workflow are:

  1. Deliver better quality software faster and with better compliance.
  2. Drive continuous improvement and adjustments earlier and more economically.
  3. Increase transparency and collaboration among stakeholders involved in delivering and operating software.
  4. Control costs and utilize provisioned resources more effectively while minimizing security risks.
  5. Plug and play well with many of your existing DevOps investments, including investments in open source

Introduction to the Microsoft platform and tools for containerized applications

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The above figure shows the main pillars in the lifecycle of Docker apps classified by the type of work delivered by multiple teams (app-development, DevOps infrastructure processes and IT Management and Operations).

Microsoft Technologies

3rd party-Azure pluggable

Platform for Docker Apps

  • Visual Studio & Visual Studio Code
  • .NET
  • Azure Kubernetes Service
  • Azure Service Fabric
  • Azure Container Registry

  • Any code editor (i.e. Sublime, etc.)
  • Any language (Node, Java etc.)
  • Any Orchestrator and Scheduler
  • Any Docker Registry

DevOps for Docker Apps

  • Azure DevOps Services
  • Team Foundation Server
  • Azure Kubernetes Service
  • Azure Service Fabric

  • GitHub, Git, Subversion, etc.
  • Jenkins, Chef, Puppet, Velocity, CircleCI, TravisCI, etc.
  • On-premises Docker Datacenter, Docker Swarm, Mesos DC/OS, Kubernetes,
    etc.

Management & Monitoring

  • Operations Management Suite
  • Application Insights
  • Marathon, Chronos, etc

The Microsoft platform and tools for containerized Docker applications, as defined in above Figure has the following components:

    • Platform for Docker Apps development. The development of a service, or collection of services that make up an “app”. The development platform provides all the work a developer requires prior to pushing their code to a shared code repo. Developing services, deployed as containers, are very similar to the development of the same apps or services without Docker. You continue to use your preferred language (.NET, Node.js, Go, etc.) and preferred editor or IDE like Visual Studio or Visual Studio Code. However, rather than consider Docker a deployment target, you develop your services in the Docker environment. You build, run, test and debug your code in containers locally, providing the target environment at development time. By providing the target environment locally, Docker containers enable what will drastically help you improve your Development and Operations lifecycle. Visual Studio and Visual Studio Code have extensions to integrate the container build, run and test your .NET, .NET Core and Node.js applications.
    • DevOps for Docker Apps. Developers creating Docker applications can leverage Azure DevOps Services (Azure DevOps) or any other third party product like Jenkins, to build out a comprehensive automated application lifecycle management (ALM).
      With Azure DevOps, developers can create container-focused DevOps for a fast, iterative process that covers source-code control from anywhere (Azure DevOps-Git, GitHub, any remote Git repository or Subversion), continuous integration (CI), and internal unit tests, inter container/service integration tests, continuous delivery CD, and release management (RM). Developers can also automate their Docker application releases into Azure Kubernetes Service, from development to staging and production environments.
      • IT production management and monitoring.
        Management –
        IT can manage production applications and services in several ways:
        1. Azure portal. If using OSS orchestrators, Azure Kubernetes Service (AKS) plus cluster management tools like Docker Datacenter and Mesosphere Marathon help you to set up and maintain your Docker environments. If using Azure Service Fabric, the Service Fabric Explorer tool allows you to visualize and configure your cluster
        2. Docker tools. You can manage your container applications using familiar tools. There’s no need to change your existing Docker management practices to move container workloads to the cloud. Use the application management tools you’re already familiar with and connect via the standard API endpoints for the orchestrator of your choice. You can also use other third party tools to manage your Docker applications like Docker Datacenter or even CLI Docker tools.
        3. Open source tools. Because AKS expose the standard API endpoints for the orchestration engine, the most popular tools are compatible with Azure Kubernetes Service and, in most cases, will work out of the box—including visualizers, monitoring, command line tools, and even future tools as they become available.
        Monitoring – While running production environments, you can monitor every angle with:
        1. Operations Management Suite (OMS). The “OMS Container Solution” can manage and monitor Docker hosts and containers by showing information about where your containers and container hosts are, which containers are running or failed, and Docker daemon and container logs. It also shows performance metrics such as CPU, memory, network and storage for the container and hosts to help you troubleshoot and find noisy neighbour containers.
        2. Application Insights. You can monitor production Docker applications by simply setting up its SDK into your services so you can get telemetry data from the applications.

Set up a local environment for Docker

A local development environment for Dockers has the following prerequisites:

If your system does not meet the requirements to run Docker for Windows, you can install Docker Toolbox, which uses Oracle Virtual Box instead of Hyper-V.

  • README FIRST for Docker Toolbox and Docker Machine users: Docker for Windows requires Microsoft Hyper-V to run. The Docker for Windows installer enables Hyper-V for you, if needed, and restart your machine. After Hyper-V is enabled, VirtualBox no longer works, but any VirtualBox VM images remain. VirtualBox VMs created with docker-machine (including the default one typically created during Toolbox install) no longer start. These VMs cannot be used side-by-side with Docker for Windows. However, you can still use docker-machine to manage remote VMs.
  • Virtualization must be enabled in BIOS and CPU SLAT-capable. Typically, virtualization is enabled by default. This is different from having Hyper-V enabled. For more detail see Virtualization must be enabled in Troubleshooting.

Enable Hypervisor

Hypervisor enables virtualization, which is the foundation on which all container orchestrators operate, including Kubernetes.

This blog uses Hyper-V as the hypervisor. On many Windows 10 versions, Hyper-V is already installed—for example, on 64-bit versions of Windows Professional, Enterprise, and Education in Windows 8 and later. It is not available on Windows Home edition.

NOTE: If you’re running something other than Windows 10 on your development platforms, another hypervisor option is to use VirtualBox, a cross-platform virtualization application. For a list of hypervisors, see “Install a Hypervisor” on the Minikube page of the Kubernetes documentation.

NOTE:
Install Hyper-V on Windows 10: https://docs.microsoft.com/en-us/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v

To enable Hyper-V manually on Windows 10 and set up a virtual switch:

          1. Go to the Control Panel >select Programs then click on Turn Windows features on or off.
            Picture2
          2. Select the Hyper-V check boxes, then click OK.
          3. To set up a virtual switch, type hyper in the Windows Start menu, then select Hyper-V Manager.
          4. In Hyper-V Manager, select Virtual Switch Manager.
          5. Select External as the type of virtual switch.
          6. Select the Create Virtual Switch button.
          7. Ensure that the Allow management operating system to share this network adapter checkbox is selected.

The current version of Docker for Windows runs on 64bit Windows 10 Pro, Enterprise and Education (1607 Anniversary Update, Build 14393 or later).

Containers and images created with Docker for Windows are shared between all user accounts on machines where it is installed. This is because all Windows accounts use the same VM to build and run containers.

Nested virtualization scenarios, such as running Docker for Windows on a VMWare or Parallels instance, might work, but come with no guarantees. For more information, see Running Docker for Windows in nested virtualization scenarios

Installing Docker for Windows

Docker for Windows is a Docker Community Edition (CE) app.

  • The Docker for Windows install package includes everything you need to run Docker on a Windows system.
  • Download the above file, and double click on downloaded installer file then follow the install wizard to accept the license, authorize the installer, and proceed with the install.
  • You are asked to authorize Docker.app with your system password during the install process. Privileged access is needed to install networking components, links to the Docker apps, and manage the Hyper-V VMs.
  • Click Finish on the setup complete dialog to launch Docker.
  • The installation provides Docker Engine, Docker CLI client, Docker Compose, Docker Machine, and Kitematic.

More info:  To learn more about installing Docker for Windows, go to https://docs.docker.com/docker-for-windows/.

Note:

  1. You can develop both Docker Linux containers and Docker Windows containers with Docker for Windows.
  2. The current version of Docker for Windows runs on 64bit Windows 10 Pro, Enterprise and Education (1607 Anniversary Update, Build 14393 or later).
  3. Virtualization must be enabled. You can verify that virtualization is enabled by checking the Performance tab on the Task Manager.
  4. The Docker for Windows installer enables Hyper-V for you.
  5. Containers and images created with Docker for Windows are shared between all user accounts on machines where it is installed. This is because all Windows accounts use the same VM to build and run containers.
  6. We can switch between Windows and Linux containers.

Test your Docker installation

  1. Open a terminal window (Command Prompt or PowerShell, but not PowerShell ISE).
  2. Run docker –version or docker version to ensure that you have a supported version of Docker:
  3. The output should tell you the basic details about your Docker environment:

docker –version

Docker version 18.05.0-ce, build f150324

docker version

Client:
Version: 18.05.0-ce
API version: 1.37
Go version: go1.9.5
Git commit: f150324
Built: Wed May 9 22:12:05 2018
OS/Arch: windows/amd64
Experimental: false
Orchestrator: swarm

Server:
Engine:
Version: 18.05.0-ce
API version: 1.37 (minimum version 1.12)
Go version: go1.10.1
Git commit: f150324
Built: Wed May 9 22:20:16 2018
OS/Arch: linux/amd64
Experimental: true

Note: The OS/Arch field tells you the operating system you’re using. Docker is cross-platform, so you can manage Windows Docker servers from a Linux client and vice-versa, using the same docker commands.

Start Docker for Windows

Docker does not start automatically after installation. To start it, search for Docker, select Docker for Windows in the search results, and click it (or hit Enter).

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When the whale in the status bar stays steady, Docker is up-and-running, and accessible from any terminal window.

Picture4

If the whale is hidden in the Notifications area, click the up arrow on the taskbar to show it. To learn more, see Docker Settings.

If you just installed the app, you also get a popup success message with suggested next steps, and a link to this documentation.

Picture5

When initialization is complete, select About Docker from the notification area icon to verify that you have the latest version.

Congratulations! You are up and running with Docker for Windows.

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Important Docker Commands

Description

Docker command

To get the list of all Images

docker images -a

docker image ls -a

To Remove the Docker Image based in ID:

docker rmi d62ae1319d0a

To get the list of all Docker Containers

docker ps -a

docker container ls -a

To Remove the Docker Container based in ID:

docker container rm d62ae1319d0a

To Remove ALL Docker Containers

docker container rm -f $(docker container ls -a -q)

Getting Terminal Access of a Container in Running state

docker exec -it <containername> /bin/bash (For Linux)

docker exec -it <containername> cmd.exe (For Windows)

Set up Development environment for Docker apps

Development tools choices: IDE or editor

No matter if you prefer a full and powerful IDE or a lightweight and agile editor, either way Microsoft have you covered when developing Docker applications?

Visual Studio Code and Docker CLI (Cross-Platform Tools for Mac, Linux and Windows). If you prefer a lightweight and cross-platform editor supporting any development language, you can use Microsoft Visual Studio Code and Docker CLI.

These products provide a simple yet robust experience which is critical for streamlining the developer workflow.

By installing “Docker for Mac” or “Docker for Windows” (development environment), Docker developers can use a single Docker CLI to build apps for either Windows or Linux (execution environment). Plus, Visual Studio code supports extensions for Docker with intellisense for Docker files and shortcut-tasks to run Docker commands from the editor.

Download and Install Visual Studio Code

Download and Install Docker for Mac and Windows

Visual Studio with Docker Tools.

When using Visual Studio 2015 you can install the add-on tools “Docker Tools for Visual Studio”.

When using Visual Studio 2017, Docker Tools come built-in already.

In both cases you can develop, run and validate your applications directly in the target Docker environment.

F5 your application (single container or multiple containers) directly into a Docker host with debugging, or CTRL + F5 to edit & refresh your app without having to rebuild the container.

This is the simples and more powerful choice for Windows developers targeting Docker containers for Linux or Windows.

Download and Install Visual Studio Enterprise 2015/2017

Download and Install Docker for Mac and Windows

If you’re using Visual Studio 2015, you must have Update 3 or a later version plus the Visual Studio Tools for Docker.

More info:  For instructions on installing Visual Studio, go to https://www.visualstudio.com/
products/vs-2015-product-editions
.

To see more about installing Visual Studio Tools for Docker, go to http://aka.ms/vstoolsfordocker and https://docs.microsoft.com/aspnet/core/host-and-deploy/docker/visual-studio-tools-for-docker.

If you’re using Visual Studio 2017, Docker support is already included.

Language and framework choices

You can develop Docker applications and Microsoft tools with most modern languages. The following is an initial list, but you are not limited to it.

  1. .NET Core and ASP.NET Core
  2. Node.js
  3. Go Lang
  4. Java
  5. Ruby
  6. Python

Basically, you can use any modern language supported by Docker in Linux or Windows.

Note: But In this blog, we are using development IDE as Visual Studi0 2017 and use .NET Core and ASP.NET Core programming languages for developing Containerized based applications.

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I am happy to announce that my book on “Building Enterprise Bots with Microsoft Bot Framework and Azure” has been accepted and successfully published by the publisher.

Book is available at https://www.packtpub.com/application-development/building-bots-microsoft-bot-framework

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Thank you.

Connecting On-Premise/private NuGet packages or feed URL in source code from VSTS for build and deploy

Step 1: Hosting your own private NuGet feeds

NuGet.Server is a package provided by the .NET Foundation that creates an ASP.NET application that can host a package feed on any server that runs IIS. Simply said, NuGet.Server basically makes a folder on the server available through HTTP(S) (specifically OData). As such it’s best for simple scenarios and is easy to set up.

The process is as follows:

  1. Create an empty ASP.NET Web application in Visual Studio and add the NuGet.Server package to it.
  2. Configure the Packages folder in the application and add packages.
  3. Deploy the application to a suitable server.

Create and deploy an ASP.NET Web application with NuGet.Server

  1. In Visual Studio, select File > New > Project, set the target framework for .NET Framework 4.6 (see below), search for “ASP.NET”, and select the ASP.NET Web Application (.NET Framework) template for C#.
    NuGetServer_001
  2. Enter the application name, click OK, and in the next dialog, select ASP.NET 4.6 – Empty template and click OK.
    NuGetServer_002
  3. Right-click on the project, select Manage NuGet Packages, and in the Package Manager, search and install the latest version of the NuGet.Server package if you’re targeting .NET Framework 4.6.
    NuGetServer_003
  4. Installing NuGet.Server converts the empty Web application into a package source. It creates a Packages folder in the application and overwrites web.config to include additional settings.
    NuGetServer_004
  5. To make packages available in the feed when you publish the application to a server, add their .nupkg files to the Packages folder in Visual Studio, then set their Build Action to Content and Copy to Output Directory to Copy always:
    NuGetServer_005
  6. Run the site locally in Visual Studio.
    NuGetServer_006
  7. Click on here in the area outlined above to see the OData feed of packages.
    NuGetServer_007
  8. By running the application the first time, the Packages folder gets restructured into a folder for each package. This matches the local storage layout introduced with NuGet 3.3 to improve performance. When adding more packages, continue to follow this structure.
    NuGetServer_008
  9. Once you’ve tested your local deployment, you can deploy the application to any other internal or external site as needed.
  10. Once deployed to http://<domain&gt;, the URL that you use for the package source will be http://<domain>/nuget.

Step 2: Publish your NuGet Server

  1. For demo purpose, I am deploying in to my local IIS server. Open IIS and create an empty site in it.
    NuGetServer_009
  2. Under Bindings, select IP address of your PC, then click on Ok.
    NuGetServer_010
  3. Now, Right click on your project and select Publish option. On publish window select IIS, FTP option as shown below (VS2017).
    NuGetServer_011
  4. Enter Server name (nothing but your PC name), Enter Site name that you created in IIS, click on validate, Next and save. It starts publishing now.
    NuGetServer_012
  5. Once it’s published successfully; you can browse the site with your IP address.
    NuGetServer_013NuGetServer_014
  6. In browser, you will see something similar as shown below.
    NuGetServer_015

Step 3: Enable Basic Authentication to your feed

  1. To enable your feed private with authentication, you can do that by enabling Basic Authentication in IIS.
  2. Go to IIS, select Authentication under IIS category.
    NuGetServer_016
  3. Enable Basic Authentication.
    NuGetServer_017
  4. Now, add a local user. Go to start menu and search for Computer Management, open it.
    NuGetServer_018
  5. Expand Local Users and Groups, right click on Users and select New User.
    NuGetServer_019
  6. Enter user name and password, select password never expire and then click on create.
    NuGetServer_020
  7. Now navigate to InetPub->wwwroot and right click on DemoNuGetFeed folder where we published your NuGet server and select properties.
    NuGetServer_021
  8. Under properties, go to Security, select DemoFeedUser from user list and then click on Edit. Give read/write permissions and then click on Apply and Ok.
    NuGetServer_022
  9. Now try to browse your server, it should prompt you for user name and password as shown below.
    NuGetServer_023
  10. This step is only for users connected to a router, if you are connected to a router then you need to enable port forwarding to your machine so that all the requests coming to port 80 will automatically redirect to your PC.
    To do this, login to your router and go to port forwarding settings and add Port no 80 and select your machine IP address. The settings will look like below.
    NuGetServer_024
    Service Port and Internal Port are 80 because in my machine IIS I configured my NuGet server port number with 80. IP address is the machine where your NuGet server running/published.
  11. Now if you browse the url with your IP address it should automatically navigate to your NuGet server as shown below. Now you can access your NuGet feed from anywhere in the world using http://<IPAddress>/nuget.

Step 4: Configure your private feed in VSTS build

  1. Open your Solution/Project where you want to use your private feed in Visual Studio.
  2. Add nuget.config file in to the project. It should have the following structure.
    NuGetServer_025
  3. Add your feed URL under PackageSources tag as shown below.
    NuGetServer_026
  4. Check-In and Push the code to VSTS.
  5. Login to VSTS, Navigate to your team project.
  6. Go to Builds, and create a new build definition with build template which suits to your project.
    NuGetServer_027
  7. Now add a task, select NuGet task and click on add.
    NuGetServer_028
  8. Select nuget restore step which you added in above step, in right side configuration area expand Feeds & Authentication section. In that enter/select path to nuget.config file as shown in below screenshot.
    NuGetServer_029
  9. Now add credentials for each feed by clicking on plus icon.
    NuGetServer_030
  10. On Add new Nuget connection window, select Authentication type here for example we selected Basic Authentication.
    NuGetServer_031
  11. Save the Build definition and queue a new build.

 

 

 

Successfully published my book on Developing Enterprise Bot Applications

I am happy to announce that my book on Developing Enterprise Bot applications has been successfully published. Book is available in stores and online at .

Packt: https://www.packtpub.com/application-development/building-bots-microsoft-bot-framework

Amazon: https://www.amazon.com/Building-Bots-Microsoft-Bot-Framework-ebook/dp/B01M9JQ0U9 Book Cover

Screen shot of Amazon link:Amazon

Atlanta Decode 2017 – Microsoft Azure and GE Digital Hackathon

Logo

Microsoft and GE came together to host the Decode Atlanta event where folks from GE Digital including GE Predix teams as well as folks from Microsoft Azure came together for a Hackathon festival in Atlanta. As part of Microsoft Azure team, I delivered workshop on developing enterprise bot applications and another workshop on Cognitive Services for AI Digital assistants.

welcome

Image 1: Welcoming participants to the event

with GE CTO

Image 2: Chris Drumgoole addressing attendees

 

scottgu showing off cloud shell in the

Image 3: Scott Guthrie in action

 

1

Image 4: Hackathon in action

 

Bot for Slack & Skype – Find Nearby Places

Add to Slack

Clicking on Add to Slack means, you are agreeing to the Nearby Bot Privacy Policy.
Add to Skype

Click this button to add Nearby Bot to your Skype account. Clicking on Add to Skype means, you are agreeing to the Nearby Bot Terms of Service & Privacy Policy.

Our NearbyBot is enabled by Microsoft’s Bot Framework. Bot Framework is a set of web-services that enable intelligent services and connections using conversation channels you authorize. As a service provider, Microsoft will create a Bot Framework user profile and receive content you provide to our bot/service in order to enable the service and to help improve Microsoft services. For more information about Microsoft privacy policies please see their privacy statement here: http://go.microsoft.com/fwlink/?LinkId=521839. To report abuse when using a bot that uses Bot Framework to Microsoft, please visit the Microsoft Bot Framework website at https://www.botframework.com and use the “Report Abuse” link in the menu to contact Microsoft.

Installing and Usage of Nearby Bot:

When you click on Add to Slack/Skype button, it will prompt you to enter team domain name or sign-in. Once you successfully add the Nearby bot to your account, go to Nearby Bot user and just say “Restaurants in Boston” that’s it, you will see all list of restaurants in Boston. Similarly you can ask anything you want to find out in your city.

Privacy Policy:

Your privacy is very important to us. Accordingly, we have developed this Policy in order for you to understand how we collect, use, communicate and disclose and make use of personal information. The following outlines our

Internet Connection

  • Nearby Bot uses internet connection for loading and displaying the nearby restaurants or book stores etc.

Collecting Your Information

  • The app doesn’t collects any information from the user except the search keyword and city information for getting data and we don’t store any information related to user.

Changes to this Privacy Policy

  • Nearby Bot may change or modify this Privacy Policy in the future. We recommend you to check this Privacy Policy from time to time to review the most current Privacy Policy.

We will make readily available to customer’s information about our policies and practices relating to the management of personal information.

Contact Us:

If you have questions about this Privacy Policy, please contact us at:

kishore1021@hotmail.com

 Powered by the Microsoft Bot Framework: https://botframework.com

Bot – Natural Speech & Intent Processing bot

Add to Slack

Clicking on Add to Slack means, you are agreeing to the Natural Speech & Intent Processing Bot Terms of Service & Privacy Policy.

Your privacy is very important to us. Accordingly, we have developed this Policy in order for you to understand how we collect, use, communicate and disclose and make use of personal information. The following outlines our

  • The application uses internet connection to show results.
  •  This  application won’t collect any personal information.
  • We will make readily available to customers information about our policies and practices relating to the management of personal information.
  • If the app is deleted, all the information is deleted automatically.

We will make readily available to customer’s information about our policies and practices relating to the management of personal information.

Contact Us:

If you have questions about this Privacy Policy, please contact us at:

kishore1021@hotmail.com

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