Google Cloud Professional Data Engineer Exam

To build a CI/CD pipeline for Dataflow jobs with minimal effort, which tool should you use?

1. Cloud Build

2. Compute Engine

3. Cloud Code

4. Terraform

The correct answer is: Cloud Build

Using Cloud Build to build a CI/CD pipeline for Dataflow jobs is an effective choice due to its integration capabilities and focus on automation for development processes. Cloud Build is designed to facilitate continuous integration and continuous deployment by allowing developers to define custom build steps in a YAML configuration file. This makes it straightforward to automate the deployment of Dataflow jobs each time there are updates to the code repository. Cloud Build supports triggers that can initiate builds based on events in source repositories, which streamlines the process of deploying new Dataflow jobs and promotes a seamless development workflow. Furthermore, it integrates well with other Google Cloud tools and services, enabling a more cohesive pipeline from code to production. This ease of integration with version control systems and its ability to orchestrate the deployment process with minimal manual intervention are key advantages for creating a CI/CD pipeline. Other tools mentioned may provide useful functionalities in their own contexts but do not specifically cater to building CI/CD pipelines for Dataflow jobs in as minimal and integrated a manner as Cloud Build. For instance, while Compute Engine offers raw computing resources, it doesn't inherently provide CI/CD capabilities. Cloud Code is useful for development but focuses more on integrating IDEs with GCP services rather than full-scale CI/CD pipelines. Terraform is primarily used for infrastructure