Course: DevOps Pipelines

Creating pipelines in AWS involves knowing how to use a series of CodePipeline action types for integration with products and services. In this course, you'll recognize the various action type integrations that facilitate AWS CodePipeline configuration. You'll identify the pipeline and stage structure requirements in AWS and list the test action integrations that can be included in pipelines and the deploy action integrations that can be used to deploy diversified applications. You'll then recognize the AWS services that can be used to configure approvals and invoke action integrations in CodePipeline and the prominent AWS service integrations not based on CodePipeline action types.

Additionally, you'll create IAM users and configure IAM managed policies. You'll create two-stage pipelines and configure AWS CodeDeploy. You'll configure CodePipeline and CodeBuild to build pipelines and stages of pipelines. Finally, you'll use Step Functions invoke actions and create Lambda functions to be added as actions.

Azure Pipelines comprises various components to enable better code delivery. In this course, you'll outline the various Azure Pipelines stages and define the role of approvals and gates. You'll describe deployment conditions and triggers and the concept of queuing policies to control deployment. You'll identify the types of resources that can be used by Azure Pipelines and recognize the role of agents. You'll also outline how to translate Jenkins and Travis pipeline configurations to Azure pipelines.

Next, you'll create pipelines to build a GitHub repository, configure and execute Azure Pipelines jobs, organize deployment jobs in release pipelines into stages, and configure resource triggers from different branches. You'll then change the default branch for a pipeline and create new resource groups and virtual machine scale sets. Finally, you'll install extensions to organizations and create a custom extension for Azure DevOps to place in the marketplace.

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.