Category: Devops

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Add variable to PATH inside windows container – reload env variables

In a previous article I explained how you can add python on PATH when you install it on a windows container image.

Install python silently on Windows container and add to PATH

However if you try to use the python verb immediately you may face a problem that variable is not recognized.

In order to resolve this issue you will have to reload the environmental variables so that change reflects the current powershell session that you use.

By performing the below powershell command you can reload env variables and continue the execution of your scripts with variables reloaded.

$env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
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dynamically set dependsOn using variables – Azure devops

DependsOn is a condition on Azure devops with which you can define dependencies between jobs and stages.

An example can be found in the below picture where the stage2 depends from the production stage and will execute only when the production stage finishes. If the production stage fails, then the stage2 will not continue its execution.

The typical way to define a dependency would be by naming the stages and note on which stage you need your dependencies. For example in the stage2 we use dependsOn with the value stage1

stages:
- stage: stage1
  displayName: running stage1
  jobs:
  - job: job1
    displayName: running job1
    steps:
    - script: echo job1.task1
      displayName: running job1.task1  

- stage: stage2
  dependsOn: stage1
  displayName: running stage2
  jobs:
  - job: job2
    displayName: running job2
    steps:
    - script: echo job2.task1
      displayName: running job1.task1

However you can also define dependsOn using a variable. This means that you can dynamically set under which stage another stage will depend and not by setting that as a static variable.

An example of this can be found below:

parameters:
  - name: myparam
    type: string
    values:
      - production
      - dev
      - qa

variables:
  ${{ if eq( parameters['myparam'], 'production' ) }}:
    myenv: production
  ${{ elseif eq( parameters['myparam'], 'dev' ) }}:
    myenv: dev
  ${{ elseif eq( parameters['myparam'], 'qa' ) }}:
    myenv: qa

trigger:
- none

pool:
  vmImage: ubuntu-latest

stages:
- stage: ${{ variables.myenv }}
  displayName: running ${{ variables.myenv }}
  jobs:
  - job: job1
    displayName: running job1
    steps:
    - script: echo job1.task1
      displayName: running job1.task1  

- stage: stage2
  dependsOn: ${{ variables.myenv }}
  displayName: running stage2
  jobs:
  - job: job2
    displayName: running job2
    steps:
    - script: echo job2.task1
      displayName: running job1.task1

When we run the pipeline we will be asked for the environment as a parameter.

This parameter will be then passed into a variable and then this variable will be used for dependsOn condition.

You could also use the parameter itself as shown below.

- stage: stage2
  dependsOn: ${{ variables.myenv }}
  displayName: running stage2
  jobs:
  - job: job2
    displayName: running job2
    steps:
    - script: echo job2.task1
      displayName: running job1.task1

Keep in mind that when you use variables, you should use the template syntax which is processed at compile time.

Youtube video:

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Deploy kubernetes cluster with kubectl and azure devops

In this guide we will examine how you can deploy pods on your Azure Kubernetes Cluster with Azure devops. In order to getting started you will need to create an AKS cluster under a resource group and connect this cluster with azure devops. After the creation you will need to connect with the cluster and export the kubeconfig file for the ado service connection.

You can do that by pressing connect

You can read the rest of the article on Medium using the link below:

View at Medium.com

A detailed deployment video can be found on my Udemy course:
https://www.udemy.com/course/mastering-azure-devops-cicd-pipelines-with-yaml/

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Jobs explained in Azure Pipelines – Azure DevOps

Following the article about stages in Azure DevOps in this article we will examine jobs, which are units of tasks grouped together.

Stages explained in Azure Pipelines – Azure DevOps

In more detail we will check the dependsOn along with the condition keyword in order to create dependencies between various jobs and indicate which should run first and if it will be executed.

Main scenario
We have a stage which contains multiple jobs. This stage could be a larger unit of actions like the deployment to production environment. A procedure like a deployment could be very complex with many different components working together for the outcome. In the stage1 there are 4 jobs with the names job1..4. Job1 needs to run first and the job2 depends on the job1 as a result it needs to wait the execution. Job2 will execute successful or fail based on the input that the user provides. Then job3 and job4 will be executed with a condition. The job3 will be executed if all the previous jobs have succeeded and job4 will be executed if one of the previous jobs had a failure and the pipeline stopped.

Example 1
We execute the pipeline with parameter equal to 1 in order to have the job2 failed. Then we will see that only job4 runs and job3 will be skipped because of the conditions.

run-1

Code

trigger:
- none

parameters:
  - name: state
    displayName: select 1 for failure and 0 for success
    type: number
    values:
      - 0
      - 1 

pool:
  vmImage: ubuntu-latest

stages:
- stage: stage1
  displayName: stage1
  jobs:
  - job: job1
    timeoutInMinutes: 60
    displayName:  job1
    steps:
    - script: echo running task1
      displayName: task1

  - job: job2
    dependsOn: job1
    displayName:  job2
    continueOnError: true
    steps:
    - script: exit ${{ parameters.state }}
      displayName: task will succeed or fail based on user input

  - job: job3
    dependsOn: job2
    condition: succeeded()
    displayName:  job3
    steps:
    - script: echo task to be executed on success
      displayName: execute on success

  - job: job4
    condition: failed()
    dependsOn: job2
    displayName:  job4
    steps:
    - script: echo task to be executed on failure
      displayName: execute on failure

Then we execute the pipeline with parameter equal to 0 in order to have the job2 run. As a result job3 will run and job4 will be skipped.

run-2

Example 2
We will now execute the same jobs but we will also use the continueOnError keyword on job2. This will allow subsequent tasks to run and skip the failure of the pipeline. By looking at the execution we will now see that job3 seems to be executed in comparison with the run that did not have the continueOnError. This is done because job2 is handled as partially failed and the next steps will continue. The job4 was skipped because pipeline did not recognize a failure.

run-3

If we execute again the pipeline with continueOnError and 0 as the parameter we will get the same result as with run-2.

Microsoft Docs:
https://learn.microsoft.com/en-us/azure/devops/pipelines/process/phases?view=azure-devops&tabs=yaml

Youtube video: