AZ-400 Designing and Implementing Microsoft DevOps Solutions Exam

Recommend a configuration management technology for application infrastructure

Configuration management is a process that ensures your servers and applications stay in a consistent, known state. When you recommend a technology, consider factors such as integration with Azure, community support, and the skills of your team. Popular options include Ansible, Chef, Puppet, and PowerShell Desired State Configuration (DSC). Each tool offers different strengths in automation, agent versus agentless management, and extensibility.

Next, evaluate how the technology handles complex deployments across multiple environments. For example, Ansible uses SSH agentless connections, while Chef and Puppet rely on agents installed on target machines. You should also look at existing investments in scripts or modules that can accelerate the setup process. Cost and licensing models are also important factors when choosing a solution.

Finally, make sure the recommended tool aligns with your organization’s security requirements and compliance policies. Look for built-in support for role-based access control and encryption of sensitive data. Check if the tool integrates with Azure services like Azure Key Vault to manage credentials. A well-chosen technology will simplify ongoing maintenance and reduce manual errors.

Implement a configuration management strategy for application infrastructure

After selecting a configuration management technology, you need a clear strategy to enforce consistency across your servers. Start by defining desired state configurations that describe how each machine should be set up. This includes settings such as installed software, file permissions, and service configurations. Storing these configurations in version control helps track changes and roll back if needed.

Your strategy should also include automation for enforcing configurations at scale. Use tools like Azure Automation State Configuration or built-in DSC pull servers to apply and monitor desired states. This continuous enforcement ensures drift is detected and corrected automatically. Schedule regular checks to validate that all servers remain compliant with the defined state.

Effective configuration management strategy also involves monitoring and reporting. Generate alerts when configurations drift or when an update fails. Use dashboards in Azure Monitor to visualize compliance across your infrastructure. These proactive measures help teams respond quickly to issues and maintain high reliability.

Define an IaC strategy, including source control and automation of testing and deployment

An Infrastructure as Code (IaC) strategy codifies your environment so you can deploy, version, and manage it like software. The first step is to store your templates or scripts in source control such as Azure Repos or GitHub. This enables collaboration, code reviews, and traceability of changes over time.

Next, integrate automated testing into your pipeline to validate IaC before it reaches production. Tests can include:

• Syntax checks for template correctness
• Unit tests to verify resource definitions
• Integration tests to deploy in a sandbox environment
  These checks catch errors early and ensure reliable deployments.

Finally, set up CI/CD pipelines in Azure DevOps or GitHub Actions to drive automated deployment. Use pull requests to trigger builds, run tests, and deploy to staging before production. Implement approval gates and quality checks to maintain control over changes. This holistic approach ensures your infrastructure changes are safe, repeatable, and documented.

Design and implement desired state configuration for environments

Desired State Configuration (DSC) is a declarative approach that lets you specify the exact state you want for machines and Azure resources. In Azure, you can use Azure Automation State Configuration, ARM templates, Bicep, and Azure Automanage Machine Configuration. Each tool defines resources in code, but they differ in syntax and capabilities.

ARM templates and Bicep focus on Azure resources, using JSON or a domain-specific language. Bicep provides a cleaner syntax and modular features, making it easier to write and maintain templates. On the other hand, Azure Automation State Configuration and Automanage manage OS-level settings using DSC pull servers and built-in profiles. These services ensure the OS configuration stays as defined.

When implementing DSC, break your configurations into modules to promote reuse and readability. Use parameters for environment-specific values, and test modules in isolated environments before rolling out. Monitor compliance through Azure dashboards and logs to detect configuration drift and correct it automatically. This ensures consistency across development, testing, and production.

Design and implement Azure Deployment Environments for on-demand self-deployment

Azure Deployment Environments allow teams to create self-service environments on demand, speeding up development and testing. You can define an environment with specific resources, templates, and configurations, then let users spin up instances as needed. This on-demand provisioning reduces wait times and frees ops teams from manual setups.

To set up these environments, use Azure DevOps Environments or GitHub Environments linked to your IaC definitions. Configure environment checks such as approvals, pipeline validations, and security policies. This ensures that every deployment meets organizational standards before it runs.

Developers can then request or trigger environment creation directly from the pipeline. The pipeline runs the IaC scripts to build the environment, runs tests, and tears it down when no longer needed. This approach promotes cost efficiency, as unused environments do not remain running indefinitely, and it fosters agility by giving teams the freedom to experiment safely.

Conclusion

In this section, we covered how to recommend and implement configuration management, ensuring servers and applications stay in the desired state using tools like Ansible and DSC. We defined a robust IaC strategy with source control, automated testing, and CI/CD to treat infrastructure as software. We also explored designing and implementing desired state configurations across Azure environments with ARM, Bicep, and Azure Automation. Finally, we looked at creating Azure Deployment Environments for on-demand self-service, empowering teams to provision and tear down environments quickly. Together, these concepts help you build a reliable, repeatable, and automated infrastructure in Azure.