Edureka Fan

Edureka Fan

1618235682

Azure DevOps Pipeline Tutorial | Azure DevOps CI/CD Pipeline

This Edureka live video on “Azure DevOps CI/CD Pipeline” will give you a brief introduction on how you can implement DevOps practices on Microsoft Azure.

#azure #devops

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Buddha Community

Azure DevOps Pipeline Tutorial | Azure DevOps CI/CD Pipeline

CI/CD Tutorial for Xamarin Android with Google Play Publishing in Azure DevOps | Part 2.

If you haven’t seen part 1, click here, and start build up your CI/CD pipeline now.

Part 2 Contains:

  • Configuring build with creating signed APK, and making artifacts from it
  • Setting up branch policy to master

Configure some magic

Let’s go back to Pipelines. Edit your previously created pipeline by clicking the three dot on the pipelines row.

Edit the previously created pipeline

CI is based on cloud machines hosted somewhere over the world. This computers called as agents. They are used to follow your instructions, defined in the yml file. The base Xamarin.Android yml is only to build your code. But we will make some additional steps in order to create a signed APK of every build. Follow up, to complete this setup.

Recommended branching strategy for this is to keep a development branch, and pull request your feature branches to it, and finally pull request the development branch to the master, and keep your master is always at your production version. The figure below shows visually this method. Source: https://dzone.com/articles/feature-branching-using-feature-flags-1

Create a signed APK or bundle from every build

First, set up some variables for this pipeline. You will find a Variables button on the right top of the tab. Click on it.

#xamarin #azure #azure devops #ci #ci/cd #pipeline #pipelines #xamarin

Nella  Brown

Nella Brown

1625113200

Azure Machine Learning training pipeline using CI/CD with Azure DevOps

When code checked trigger CI/CD using Azure DevOps

Prerequisite

  • Azure Account
  • Azure Machine learning
  • Create a compute instance
  • Create a compute cluster as cpu-cluster
  • Select Standard D series version
  • Create Train file to train the model
  • Create a pipeline file to run the as pipeline

Steps

Create Train file as train.py

  • Create a directory ./train_src
  • Create a train.py
  • Should be a python file not notebook

#machine-learning #azure-devops #azure-machine-learning #devops #ci/cd

Matt  Towne

Matt Towne

1589791867

Serverless CI/CD on the AWS Cloud

CI/CD pipelines have long played a major role in speeding up the development and deployment of cloud-native apps. Cloud services like AWS lend themselves to more agile deployment through the services they offer as well as approaches such as Infrastructure as Code. There is no shortage of tools to help you manage your CI/CD pipeline as well.

While the majority of development teams have streamlined their pipelines to take full advantage of cloud-native features, there is still so much that can be done to refine CI/CD even further. The entire pipeline can now be built as code and managed either via Git as a single source of truth or by using visual tools to help guide the process.

The entire process can be fully automated. Even better, it can be made serverless, which allows the CI/CD pipeline to operate with immense efficiency. Git branches can even be utilized as a base for multiple pipelines. Thanks to the three tools from Amazon; AWS CodeCommit, AWS CodeBuild, and AWS CodeDeploy, serverless CI/CD on the AWS cloud is now easy to set up.

#aws #aws codebuild #aws codecommit #aws codedeploy #cd #cd pipeline #ci #ci/cd processes #ci/cd workflow #serverless

Adelle  Hackett

Adelle Hackett

1595021683

How To Setup a CI/CD Pipeline With Kubernetes 2020 - DZone DevOps

When it comes to DevOps, the word that clicks in mind is CI/CD pipeline. Let’s have a look at Definition of CI/CD pipeline:

CI is straightforward and stands for continuous integration, a practice that focuses on making preparing a release easier. But CD can either mean continuous delivery or continuous deployment and while those two practices have a lot in common, they also have a significant difference that can have critical consequences for a business.

CI stands for Continuous Integration, and CD stands for Continuous Delivery and Continuous Deployment. You can think of it as a process which is similar to a software development lifecycle.

Systems provide automation of the software build and validation process-driven continuously by running a configured sequence of operations every time a software change is checked into the source code management repository. These are closely associated with agile development practices and closely related to the emerging DevOps toolsets.

In the DevOps world, we have a plethora of toolsets that can help and leverage CICD capabilities.

  • Docker
  • Kubernetes
  • Proxies
  • Git
  • Jenkins/ Jenkins X
  • Ansible
  • Chef
  • Code Pipeline, etc

This blog gives direction to up and running your CICD pipeline running on the Kubernetes cluster by the GitLab CICD pipeline.

Prerequisites

  • Hands-on knowledge of Docker containers
  • Hands-on knowledge of Kubernetes architecture and understanding
  • The Idea of how to write YAML files
  • Up and Running Kubernetes cluster

#docker #kubernetes #ci/cd #devops tools #devops 2020 #ci/cd pipeline

Noah  Rowe

Noah Rowe

1595494080

Azure DevOps Pipelines: Multi-Stage Pipelines

The last couple of posts have been dealing with Release managed from the Releases area under Azure Pipelines. This week we are going to take what we were doing in that separate area of Azure DevOps and instead make it part of the YAML that currently builds our application. If you need some background on how the project got to this point check out the following posts.

Getting Started with Azure DevOps

Pipeline Creation in Azure DevOps

Azure DevOps Publish Artifacts for ASP.NET Core

Azure DevOps Pipelines: Multiple Jobs in YAML

Azure DevOps Pipelines: Reusable YAML

Azure DevOps Pipelines: Use YAML Across Repos

Azure DevOps Pipelines: Conditionals in YAML

Azure DevOps Pipelines: Naming and Tagging

Azure DevOps Pipelines: Manual Tagging

Azure DevOps Pipelines: Depends On with Conditionals in YAML

Azure DevOps Pipelines: PowerShell Task

Azure DevOps Releases: Auto Create New Release After Pipeline Build

Azure DevOps Releases: Auto Create Release with Pull Requests

Image for post

Recap

The current setup we have uses a YAML based Azure Pipeline to build a couple of ASP.NET Core web applications. Then on the Release side, we have basically a dummy release that doesn’t actually do anything but served as a demo of how to configure a continuous deployment type release. The following is the current YAML for our Pipeline for reference.

name: $(SourceBranchName)_$(date:yyyyMMdd)$(rev:.r)

resources:      
  repositories: 
  - repository: Shared
    name: Playground/Shared
    type: git 
    ref: master #branch name

trigger: none

variables:
  buildConfiguration: 'Release'

jobs:
- job: WebApp1
  displayName: 'Build WebApp1'
  pool:
    vmImage: 'ubuntu-latest'

  steps:
  - task: PowerShell@2
    inputs:
      targetType: 'inline'
      script: 'Get-ChildItem -Path Env:\'

  - template: buildCoreWebProject.yml@Shared
    parameters:
      buildConFiguration: $(buildConfiguration)
      project: WebApp1.csproj
      artifactName: WebApp1

- job: WebApp2
  displayName: 'Build WebApp2'
  condition: and(succeeded(), eq(variables['BuildWebApp2'], 'true'))
  pool:
    vmImage: 'ubuntu-latest'

  steps:
  - template: build.yml
    parameters:
      buildConFiguration: $(buildConfiguration)
      project: WebApp2.csproj
      artifactName: WebApp2

- job: DependentJob
  displayName: 'Build Dependent Job'
  pool:
    vmImage: 'ubuntu-latest'

  dependsOn:
  - WebApp1
  - WebApp2

  steps:
  - template: buildCoreWebProject.yml@Shared
    parameters:
      buildConFiguration: $(buildConfiguration)
      project: WebApp1.csproj
      artifactName: WebApp1Again

- job: TagSources
  displayName: 'Tag Sources'
  pool:
    vmImage: 'ubuntu-latest'

  dependsOn:
  - WebApp1
  - WebApp2
  - DependentJob
  condition: |
    and
    (
      eq(dependencies.WebApp1.result, 'Succeeded'),
      in(dependencies.WebApp2.result, 'Succeeded', 'Skipped'),
      in(dependencies.DependentJob.result, 'Succeeded', 'Skipped')
    )

  steps:
  - checkout: self
    persistCredentials: true
    clean: true
    fetchDepth: 1

  - task: PowerShell@2
    inputs:
      targetType: 'inline'
      script: |
        $env:GIT_REDIRECT_STDERR` = '2>&1'
        $tag = "manual_$(Build.BuildNumber)".replace(' ', '_')
        git tag $tag
        Write-Host "Successfully created tag $tag" 

        git push --tags
         Write-Host "Successfully pushed tag $tag"     

      failOnStderr: false

#azure-pipelines #azure #azure-devops #devops