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The latter approach requires far less setup and configuration, so that is the approach we will document here.

Guides

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Prerequisites

To automate the required steps in Azure DevOps, you will require…

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Azure DevOps Asset

Description

Projects

The container for Azure DevOps repositories, boards, and pipelines.

Agents and Agent Pools

Agent pools can be created easily using the Azure DevOps UI. Neither the number of pools your you create, or the names you give them, are relevant to your MettleCI-enabled pipelines as jobs are automatically assigned to agents by Azure DevOps based on the demands required bye by each of yoyr your pipelines' steps and the matching capabilities advertised by your agents.

The definition of Agents requires you to install one or more self-hosted Azure agents on a suitably equipped host (see https://learn.microsoft.com/en-us/azure/devops/pipelines/agents/windows-agent?view=azure-devops) and associate the agent(s) with a relevant agent pool.

Environments

The creation of Deployment Environments is not currently supported by the Azure CLI. Environments are created by the supplied pipelines as they are references. i.e., if you try and run a MettleCI deployment to an environment called MyQualityAssurance then environment of that name will be automatically created. Once a deploy environment has been created (either manually using the Azure UI or automatically) you can then configure its 'Approvals and checks' to restrict deployment to that environment as required.

Repositories

You’ll need two repositories: One for your DataStage assets and one for your Compliance rules. We provide commands to create these and import the supplied examples.

Variable Groups

You’ll need a variable group for each DataStage platform you operate. Typically, this will be one Development environment and one Production environment, and perhaps a separate Quality Assurance environment if your organisation structures its platforms like that.

We provide commands to crate the variable groups and populate them with example variables required to execute the sample pipelines. Passwords are configured as ‘secret’ variables. If you wish these values to reside in an Azure Key Store you’ll need to modify the supplied example commands to achieve that.

Pipelines

We provide four example pipelines:

  • devops-ci.yml - A DevOps continuous integration pipeline intended to be triggered by the commit of a DataStage asset to your repository. This pipeline demonstrates the invocation of Compliance and Unit Testing functions and the deployment of code to downstream environments.

  • hotfix-ci.yml - A pipeline which performs CI testing (Compliance and Unit Test operations) on a hotfix-specific branch of your code.

  • hotfix-deploy.yml - A pipeline which deploys your current DataStage software configuration from a hotfix-specific code branch directly into your production environment.

  • upgrade-ci.yml - A special case pipeline used to CI test commits from one environment and promote them into an environment running a different version of DataStage, converting artifacts as required in the process. This is commonly employed to provide a pipeline between DataStage v11.5 and v11.7 environments during an upgrade initiative.

Creating an Approvers Group (optional)

The purpose of this group is to approve promotion of code into an official environment, e.g., Test, QA, Pre-Production, Production. MettleCI CI projects are internal (or “unofficial”) and requiring approval for those would be counterproductive.

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Info

We have observed instances in Azure DevOps where the secret value variable is created but the value is not assigned. In this case you will need to update the value manually in the Azure DevOps administration console.

Create Environment

Creating an Environment is currently not supported by the Azure CLI, but can be achieved using the REST API. All environments need to be created: MettleCI CI environments, and ‘official’ environments, i.e. Test, QA, Production, etc.

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