What solution stack should you adopt for a CI/CD pipeline that allows building and deploying custom Compute Engine images?

The correct choice involves using Cloud Build with Packer for building and deploying custom Compute Engine images because this combination is specifically designed for the task at hand.

Cloud Build is a powerful CI/CD tool that allows you to automate the building, testing, and deploying of applications on Google Cloud. It integrates seamlessly with other Google Cloud services and can execute builds defined in YAML configurations. Packer, on the other hand, is a tool specifically for creating identical machine images for multiple platforms from a single source configuration. By using Packer alongside Cloud Build, you can automate the process of creating custom Compute Engine images, allowing you to define your image configuration code in a variety of formats such as JSON or HCL (HashiCorp Configuration Language). This results in a streamlined and repeatable process for managing and deploying infrastructure.

The other options either pertain to different deployment contexts or do not provide the necessary tools for building custom images specifically for Compute Engine. Using Google Cloud Deploy is not directly suited for creating images but instead focuses more on deploying applications across services. Google Kubernetes Engine is oriented towards container orchestration rather than virtual machine image creation, and kpt is tailored for managing Kubernetes applications and configurations rather than crafting Compute Engine images. Therefore, the combination of Cloud Build and