AZ-400 Designing and Implementing Microsoft DevOps Solutions Exam

Recommend package management tools including GitHub Packages registry and Azure Artifacts

Choosing the right package management tool helps teams store and share code libraries. Two popular options in Azure DevOps are GitHub Packages and Azure Artifacts. GitHub Packages integrates directly with GitHub repositories, so you can publish and consume packages without leaving your code environment. This close integration makes it easy for teams already using GitHub for version control.

Azure Artifacts is a service within Azure DevOps that offers universal package management. You can host multiple package types like NuGet, npm, and Maven all in one place. Azure Artifacts also provides features such as upstream sources and scoped feeds to make sharing packages across projects simpler. This flexibility helps teams adopt a consistent package workflow.

When deciding between the two tools, consider factors like existing workflows and ecosystem fit. If your organization is heavily invested in GitHub, GitHub Packages might be the natural choice. On the other hand, if you use Azure Pipelines and other Azure DevOps services, Azure Artifacts can streamline your build and release processes. Matching tools to team habits reduces friction and improves adoption.

Finally, think about scalability and security. Both tools support fine-grained access controls and audit logs. By using Azure Active Directory or GitHub’s enterprise features, you can enforce policies and track usage. Ensuring secure package delivery is critical for maintaining a reliable and compliant software supply chain.

Design and implement package feeds and views for local and upstream packages

A package feed is a repository where stored packages are organized and served. Local feeds hold internally published packages, while upstream sources pull packages from public registries. By setting up views, you can control which package versions different teams or environments see.

To design a feed, start by creating clear naming conventions and permissions. Use:

• Scoped feeds for team-specific packages
• Global feeds for widely used libraries
• Upstream sources to cache external packages and improve build reliability

This structure helps avoid package conflicts and ensures consistent builds across environments.

Implementing views lets you lock down package versions for production while allowing newer versions in development. For example, a “@Release” view only shows tested packages, and a “@CI” view always shows the latest. Views help enforce stability in critical pipelines and speed up innovation in early stages. Separate views reduce the risk of accidentally deploying untested code.

Finally, monitor your feeds and views with built-in analytics and logs. Tracking package downloads and failures helps you spot issues early. You can also set retention policies to remove old or unused packages. This ongoing management keeps your feeds clean and efficient.

Design and implement a dependency versioning strategy for code assets and packages, including semantic versioning and date-based

A strong dependency versioning strategy ensures that your projects use the right package versions. Two popular approaches are semantic versioning and date-based versioning. Semantic versioning uses three digits (major.minor.patch) to communicate the impact of changes. This clarity helps developers know when an update may break existing code.

In semantic versioning:

• Major increases for incompatible API changes
• Minor increases when adding functionality in a backward-compatible manner
• Patch increases for backward-compatible bug fixes

Date-based versioning uses the release date, such as 2023.04.15, to identify versions. This can simplify identifying when a package was released but may not clearly signal breaking changes. Teams often combine both methods by appending dates or build numbers.

When designing your strategy, document your rules and train the team on how to update versions. Use automated tools or pipeline tasks to bump versions during builds. Automation ensures consistency and reduces human error. Also, enforce policy checks in pull requests so that all changes follow the versioning scheme.

Regularly review your versioning approach to make sure it meets evolving needs. As projects grow, you may need to adjust policies or adopt new tooling for managing versions. Staying flexible helps teams handle complex dependencies without risking build failures.

Design and implement a versioning strategy for pipeline artifacts

Pipeline artifacts include compiled binaries, test results, and other build outputs. Having a clear versioning strategy for these artifacts makes it easier to track and deploy the right builds. Artifact versioning often ties in with the package version or uses a unique build identifier.

One common practice is to use the build number from your CI pipeline as part of the artifact version. For example, you might name an artifact MyApp-20230415.42 where 42 is the build count. This approach ensures each artifact has a globally unique identifier. It also makes troubleshooting easier since you can trace back to the exact pipeline run.

Another strategy is to incorporate commit hashes or Git tags into the artifact name. This method links the artifact directly to a specific code state in your repository. Using Git metadata helps in audits and rollbacks if you identify a faulty release. Combining build numbers and commit IDs provides both uniqueness and traceability.

Automate the versioning process within your pipelines to avoid manual errors. For instance, use variables in Azure Pipelines to set the artifact name and version dynamically. Implement checks to prevent version collisions and ensure that only authorized builds create releases. Automation also helps maintain a consistent approach across multiple projects.

Conclusion

In this section, we covered how to recommend package management tools like GitHub Packages and Azure Artifacts to fit your team’s workflow. We explored designing and implementing package feeds and views to organize local and upstream packages. Next, we discussed setting up a dependency versioning strategy with semantic and date-based approaches to keep code consistency. Finally, we outlined versioning strategies for pipeline artifacts to track build outputs accurately. Together, these practices form a robust package management strategy that supports reliable, secure, and scalable software delivery.