To work with DevOps pipelines, you need to recognize how pipelines are managed using different cloud platforms. In Google Cloud Platform (GCP), working with pipelines is more advanced than some of the other providers. In this course, you'll identify the benefits of GCP DevOps pipelines and the prominent GCP components and services that build them. You'll list the essential elements used to implement IoT to analytics and the benefits of using Cloud Deployment Manager to create and manage cloud resources.
Next, you'll learn to create repositories to host sample app source codes, development environments from a feature branch, and GKE clusters. You'll set up a canary deployment environment and use a GCP pipeline to implement triggered deployment. You'll create Cloud Build config files to build and push Docker images to Container Registry, and configure CI/CD pipelines using GKE, Cloud Source Repositories, and Cloud Build. Finally, you'll write Dataflow pipelines and run Dataflow locally and on the cloud.
specify the benefits of GCP DevOps pipeline when implemented using Google cloud computing services
create GKE clusters that can be used in continuous deployment with Cloud Build
create repositories to host sample app source code and set up automated triggers in Cloud Build
create a development environment from a feature branch and push the branch to the Git server to enable Cloud Build to deploy the environment
set up a canary deployment environment and use a GCP pipeline to implement triggered deployments with the canary deployment strategy
create Cloud Build config files and use them to build and push Docker images to Container Registry
configure CI/CD pipelines to enable robust CI/CD pipelines using GKE, Cloud Source Repositories, and Cloud Build
list the prominent GCP components and services that can be used to build data pipelines
build serverless deployment pipelines on Google Cloud Platform
list the essential components of GCP that can be used to implement IoT to analytics and build analytical pipelines
write Dataflow pipelines and demonstrate the steps to run Dataflow locally and on the cloud
recall the benefits of using Cloud Deployment Manager to create and manage cloud resources with simple templates in GCP continuous deployment pipelines