Azure DevOps Security & Permissions REST API

Every Few months I notice the following Saga repeats. I face a challenge where I need to programmatically manage security aspects of Azure DevOps resources (like Repository, Pipeline, Environment etc.). I do lookup the Azure DevOps REST API documentation, realize that the Permissions & Security API’s are notoriously complicated and inadequately documented. So, I begin with F8 to kick off the Development tools for Browser and intercepting HTTP requests. Trying to guess what’s payloads are exchanged and try to come up with appropriate HTTP requests myself. However strange it might sound, usually this method works for me (actually worked almost all the time). But it’s a painful and time-consuming process. Recently I had to go through this process one more time and I promised to myself that once I am done, I will write a Blog post about it and put the code in a GitHub repository – so next time I will save myself some time & pain. That’s exactly what this post is all about.

Security & Permission REST API

As I have said, the security REST API is relatively complicated and to inadequately documented. Typically, each family of resources (work items, Git repositories, etc.) is secured using a different namespace. The first challenge is to find out the namespace IDs.

Then each security namespace contains zero or more access control lists. Each access control list contains a token, an inherit flag and a set of zero or more access control entries. Each access control entry contains an identity descriptor, an allowed permissions bitmask and a denied permissions bitmask.

Tokens are arbitrary strings representing resources in Azure DevOps. Token format differs per resource type; however, hierarchy and separator characters are common between all tokens. Now, where do you find these tokens format? Well, I mostly find them by intercepting the Browser HTTP payloads. To save me from future efforts, I have created a .net Object model around the security namespace IDs, permissions and tokens – so when I consume those libraries, I can ignore these lower level elements and have a higher order APIs to manage permissions. You can look into the GitHub repository to learn about it. However, just to make it more fun to use, I have spent a bit time to create a Manifest file (Yes, stolen from Kubernetes world) where I can get my future job done only by writing YAML files – as oppose to .net/C# codes.

Instructions to use

The repository containes two projects (once is a Library – produced a DLL and another is the console executable application) and the console executable is named as azdoctl.exe.

The idea is to create a manifest file (yaml format) and apply the changes via the azdoctl.exe:

> azdoctl apply -f manifest.yaml
Manifest file

You need to create a manifest file to descibe your Azure DevOps project and permissions. The format of the manifest file is in yaml (and idea is borrowed from Kubernetes manufest files.)


Here’s the schema of the manifest file:

apiVersion: apps/v1
kind: Project
  name: Bi-Team-Project
  description: Project for BI Engineering team
  name: Agile
  sourceControlType: Git

Manifest file starts with the team project name and description. Each manifest file can have only one team project definition.


Next, we can define teams for the project with following yaml block:

  - name: Bi-Core-Team
    description: The core team that run BI projects
      - name: Timothy Green
        id: 4ae3c851-6ef3-4748-bef9-4f809736d538
      - name: Linda
        id: 9c5918c7-ef03-4059-a49e-aa6e6d761423
        - name: 'UX Specialists'
          id: a2931c86-e975-4220-aa89-dc3f952290f4
        - name: Timothy Green
          id: 4ae3c851-6ef3-4748-bef9-4f809736d538
        - name: Linda
          id: 9c5918c7-ef03-4059-a49e-aa6e6d761423

Here we can create teams and assign admins and members to them. All the references (name and ids) must be valid in Azure Active Directory. Ids are Object ID for group or users in Azure Active directory.


Next, we can define the repository – that must be created and assigned permissions to.

  - name: Sample-Git-Repository
      - group: 'Data-Scientists'
        origin: aad
          - GenericRead
          - GenericContribute
          - CreateBranch
          - PullRequestContribute
      - group: 'BI-Scrum-masters'
        origin: aad
          - GenericRead
          - GenericContribute
          - CreateBranch
          - PullRequestContribute
          - PolicyExempt

Again, you can apply an Azure AD group with very fine-grained permissions to each repository that you want to create.

List of all the allowed permissions:



You can create environments and assign permissions to them with following yaml block.

  - name: Development-Environment
    description: 'Deployment environment for Developers'
      - group: 'Bi-Developers'
        origin: aad
          - Administrator
  - name: Production-Environment
    description: 'Deployment environment for Production'
      - group: 'Bi-Developers'
        origin: aad
          - User        

Build and Release (pipeline) folders

You can also create Folders for build and release pipelines and apply specific permission during bootstrap. That way teams can have fine grained permissions into these folders.

Build Pipeline Folders

Here’s the snippet for creating build folders.

  - path: '/Bi-Application-Builds'
      - group: 'Bi-Developers'
        origin: aad
          - ViewBuilds
          - QueueBuilds
          - StopBuilds
          - ViewBuildDefinition
          - EditBuildDefinition
          - DeleteBuilds

And, for the release pipelines:

  - path: '/Bi-Application-Relases'
      - group: 'Bi-Developers'
        origin: aad
          - ViewReleaseDefinition
          - EditReleaseDefinition
          - ViewReleases
          - CreateReleases
          - EditReleaseEnvironment
          - DeleteReleaseEnvironment
          - ManageDeployments

Once you have the yaml file defined, you can apply it as described above.


That’s pretty much it for today. By the way,

The code is provided as-is, with MIT license. You can use it, replicate it, modify it as much as you wish. I would appreciate if you acknowledge the usefulness, but that’s not enforced. You are free to use it anyway you want.

And, that also means, the author is not taking any responsibility to provide any guarantee or such.


Azure DevOps Multi-Stage pipelines for Enterprise AKS scenarios


Multi-Stage Azure pipelines enables writing the build (continuous integration) and deploy (continuous delivery) in Pipeline-as-Code (YAML) that gets stored into a version control (Git repository). However, deploying in multiple environments (test, acceptance, production etc.) needs approvals/control gates. Often different stakeholders (product owners/Operations folks) are involved into that process of approvals. In addition to that, restricting secrets/credentials for higher-order stages (i.e. production) from developers are not uncommon.

Good news is Azure DevOps allows doing all that, with notions called Environment and resources. The idea is environment (e.g. Production) are configured with resources (e.g. Kubernetes, Virtual machine etc.) in them, then “approval policy” configured for the environment. When a pipeline targets environment in deployment stage, it pauses with a pending approval from responsible authorities (i.e. groups or users). Azure DevOps offers awesome UI to create environments, setting up approval policies.

The problem begins when we want to automate environment creations to scale the process.

Problem statement

As of today (while writing this article)- provisioning and setting up approve policies for environments via REST API is not documented and publicly unavailable – there is a feature request awaiting.
In this article, I will share some code that can be used to automate provisioning environment, approval policy management.


It’s fairly common (in fact best practice) to logically isolate AKS clusters for separate teams and projects. To minimize the number of physical AKS clusters we deploy to isolate teams or applications.

With logical isolation, a single AKS cluster can be used for multiple workloads, teams, or environments. Kubernetes Namespaces form the logical isolation boundary for workloads and resources.

When we setup such isolation for multiple teams, it’s crucial to automate the bootstrap of team projects in Azure DevOps– setting up scoped environments, service accounts so teams can’t deploy to namespaces of other teams etc. The need for automation is right there – and that’s all this article is about.

The process I am trying to establish as follows:

  1. Cluster Administrators will provision a namespace for a team (GitOps )
  2. Automatically create an Environment for the team’s namespace and configure approvals
  3. Team 1 will use the environment in their multi-stage pipeline

Let’s do this!

Provision namespace for teams

It all begins with a demand from a team – they need a namespace for development/deployment. The cluster administrators would keep a Git repository that contains the Kubernetes manifest files describing these namespaces. And there is a pipeline that applies them to the cluster each time a new file is added/modified. This repository will be restricted to the Cluster administrators (operation folks) only. Developers could issue a pull request but the PR approvals and commits to master should only be accepted by a cluster administrator or people with similar responsibility.

After that, we will create a service account for each of the namespaces. These are the accounts that will be used later when we will define Azure DevOps environment for each team.

Now the pipeline for this repository essentially applies all the manifests (both for namespaces and services accounts) to the cluster.

- master
- stage: Build
  displayName: Provision namespace and service accounts
  - job: Build
    displayName: Update namespace and service accounts
      <… omitted irrelevant codes …>
      - bash: |
          kubectl apply -f ./namespaces 
        displayName: 'Update namespaces'
      - bash: |
          kubectl apply -f ./ServiceAccounts 
        displayName: 'Update service accounts'   
      - bash: |
          dotnet ado-env-gen.dll
        displayName: 'Provision Azure DevOps Environments'       

At this point, we have service account configured for each namespace that we will use to create the environment, endpoints etc. You might notice that I have created some label for each service account (i.e. purpose=ado-automation), this is to tag along the Azure DevOps Project name to a service account. This will come handy when we will provision environments.

The last task that runs a .net core console app (i.e. ado-env-gen.dll) – which I will described in detail later in this article.

Provisioning Environment in Azure DevOps

NOTE: Provisioning environment via REST api currently is undocumented and might change in coming future – beware of that.

It takes multiple steps to create an Environment to Azure DevOps. The steps are below:

  1. Create a Service endpoint with Kubernetes Service Account
  2. Create an empty environment (with no resources yet)
  3. Connect the service endpoint to the environment as Resource

I’ve used .net (C#) for this, but any REST client technology could do that.

Creating Service Endpoint

Following method creates a service endpoint in Azure DevOps that uses a Service Account scoped to a given namespace.

        public async Task<Endpoint> CreateKubernetesEndpointAsync(
            Guid projectId, string projectName,
            string endpointName, string endpointDescription,
            string clusterApiUri,
            string serviceAccountCertificate, string apiToken)
            return await GetAzureDevOpsDefaultUri()
                    authorization = new
                        parameters = new
                            isCreatedFromSecretYaml = true,
                            apitoken = apiToken
                        scheme = "Token"
                    data = new
                        authorizationType = "ServiceAccount"
                    name = endpointName,
                    owner = "library",
                    type = "kubernetes",
                    url = clusterApiUri,
                    description = endpointDescription,
                    serviceEndpointProjectReferences = new List<Object>
                            description = endpointDescription,
                            name =  endpointName,
                            projectReference = new
                                id =  projectId,
                                name =  projectName
                }, await GetBearerTokenAsync());

We will find out how to invoke this method in a moment. Before that, Step 2, let’s create the empty environment now.

Creating Environment in Azure DevOps

        public async Task<PipelineEnvironment> CreateEnvironmentAsync(
            string project, string envName, string envDesc)
            var env = await GetAzureDevOpsDefaultUri()
                    name = envName,
                    description = envDesc
                await GetBearerTokenAsync());

            return env;

Now we have environment, but it still empty. We need to add a resource into it and that would be the Service Endpoint – so the environment comes to life.

        public async Task<string> CreateKubernetesResourceAsync(
            string projectName, long environmentId, Guid endpointId,
            string kubernetesNamespace, string kubernetesClusterName)
            var link = await GetAzureDevOpsDefaultUri()
                                name = kubernetesNamespace,
                                @namespace = kubernetesNamespace,
                                clusterName = kubernetesClusterName,
                                serviceEndpointId = endpointId
                            await GetBearerTokenAsync());
            return link;

Of course, environment needs to have Approval policies configure. The following method configures a Azure DevOps group as Approver to the environment. Hence any pipeline that reference this environment will be paused and wait for approval from one of the members of the group.

        public async Task<string> CreateApprovalPolicyAsync(
            string projectName, Guid groupId, long envId, 
            string instruction = "Please approve the Deployment")
            var response = await GetAzureDevOpsDefaultUri()
                    timeout = 43200,
                    type = new
                        name = "Approval"
                    settings = new
                        executionOrder = 1,
                        instructions = instruction,
                        blockedApprovers = new List<object> { },
                        minRequiredApprovers = 0,
                        requesterCannotBeApprover = false,
                        approvers = new List<object> { new { id = groupId } }
                    resource = new
                        type = "environment",
                        id = envId.ToString()
                }, await GetBearerTokenAsync());
            return response;

So far so good. But we need to stich all these together. Before we do so, one last item needs attention. We would want to create a Service connection to the Azure container registry so the teams can push/pull images to that. And we would do that using Service Principals designated to the teams – instead of the Admin keys of ACR.

Creating Container Registry connection

The following snippet allows us provisioning Service Connection to Azure Container Registry with Service principals – which can have fine grained RBAC roles (i.e. ACRPush or ACRPull etc.) that makes sense for the team.

        public async Task<string> CreateAcrConnectionAsync(
            string projectName, string acrName, string name, string description,
            string subscriptionId, string subscriptionName, string resourceGroup,
            string clientId, string secret, string tenantId)
            var response = await GetAzureDevOpsDefaultUri()
                    type = "dockerregistry",
                    url = $"https://{acrName}",
                    isShared = false,
                    owner = "library",
                    data = new
                        registryId = $"/subscriptions/{subscriptionId}/resourceGroups/{resourceGroup}/providers/Microsoft.ContainerRegistry/registries/{acrName}",
                        registrytype = "ACR",
                    authorization = new
                        scheme = "ServicePrincipal",
                        parameters = new
                            loginServer = $"{acrName}",
                            servicePrincipalId = clientId,
                            serviceprincipalkey = secret
                await GetBearerTokenAsync());
            return response;

We came pretty close to a wrap. We’ll stitch all the methods above together. Plan is to create a simple console application will fix everything (using the above methods). Here’s the pseudo steps:

  1. Find all Service Account created for this purpose
  2. For each Service Account: determining the correct Team Project and
    • Create Service Endpoint with the Account
    • Create Environment
    • Connect Service Endpoint to Environment (adding resource)
    • Configure Approval policies
    • Create Azure Container Registry connection

The first step needs to communicate to the cluster – obviously. I have used the official .net client for Kubernetes for that.

Bringing all together

All the above methods are invoked from a simple C# console application. Below is the relevant part of the main method that brings all the above together:

        private static async Task Main(string [] args)
            var clusterApiUrl = Environment.GetEnvironmentVariable("AKS_URI");
            var adoUrl = Environment.GetEnvironmentVariable("AZDO_ORG_SERVICE_URL");
            var pat = Environment.GetEnvironmentVariable("AZDO_PERSONAL_ACCESS_TOKEN");
            var adoClient = new AdoClient(adoUrl, pat);
            var groups = await adoClient.ListGroupsAsync();

            var config = KubernetesClientConfiguration.BuildConfigFromConfigFile();
            var client = new Kubernetes(config);

We started by collecting some secret and configuration data – all from environment variables – so we can run this console as part of the pipeline task and use pipeline variables at ease.

        var accounts = await client
            .ListServiceAccountForAllNamespacesAsync(labelSelector: "purpose=ado-automation");

This gets us the list of all the service accounts we have provisioned specially for this purpose (filtered using the labels).

            foreach (var account in accounts.Items)
                var project = await GetProjectAsync(account.Metadata.Labels["project"], adoClient);
                var secretName = account.Secrets[0].Name;
                var secret = await client
                    .ReadNamespacedSecretAsync(secretName, account.Metadata.NamespaceProperty);

We are iterating all the accounts and retrieving their secrets from the cluster. Next step, creating the environment with these secrets.

                var endpoint = await adoClient.CreateKubernetesEndpointAsync(
                    $"Service endpoint to the namespace {account.Metadata.NamespaceProperty}",

                var environment = await adoClient.CreateEnvironmentAsync(project.Name,
                    $"Environment scoped to the namespace {account.Metadata.NamespaceProperty}");

                await adoClient.CreateKubernetesResourceAsync(project.Name, 
                    environment.Id, endpoint.Id,

That will give us the environment – correctly configured with the appropriate Service Accounts. Let’s set up the approval policy now:

                var group = groups.FirstOrDefault(g => g.DisplayName
                    .Equals($"[{project.Name}]\\Release Administrators", StringComparison.OrdinalIgnoreCase));
                await adoClient.CreateApprovalPolicyAsync(project.Name, group.OriginId, environment.Id);

We are taking a designated project group “Release Administrators” and set them as approves.

            await adoClient.CreateAcrConnectionAsync(project.Name, 
                $"ACR-Connection", "The connection to the ACR",

Lastly created the ACR connection as well.

The entire project is in GitHub – in case you want to have a read!

Verify everything

We have got our orchestration completed. Every time we add a new team, we create one manifest for their namespace and Service account and create a PR to the repository described above. A cluster admin approves the PR and a pipeline gets kicked off.

The pipeline ensures:

  1. All the namespaces and service accounts are created
  2. An environment with the appropriate service accounts are created in the correct team project.

Now a team can create their own pipeline in their repository – referring to the environment. Voila, all starts working nice. All they need is to refer the name of the environment that’s provisioned for their team (for instance “team-1”), as following example:

- stage: Deploy
  displayName: Deploy stage
  dependsOn: Build
  - deployment: Deploy
    condition: and(succeeded(), not(startsWith(variables['Build.SourceBranch'], 'refs/pull/')))
    displayName: Deploy
      vmImage: $(vmImageName)
    environment: ''
          - download: current
            artifact: kube-manifests
          - task: KubernetesManifest@0
            displayName: Deploy to Kubernetes cluster
              action: deploy
              manifests: |

Now the multi-stage pipeline knows how to talk to the correct namespace in AKS with approval awaiting.


This might appear an overkill for small-scale projects, as it involves quite some overhead of development and maintenance. However, on multiple occasions (especially within large enterprises), I have experienced the need for orchestrations via REST API to onboard teams in Azure DevOps, bootstrapping configurations across multiple teams’ projects etc. If you’re on the same boat, this article might be an interesting read for you!

Thanks for reading!