Course: DevOps Pipelines

$107.69 incl. vat


duration: 6 hours |

Language: English (US) |

access duration: 90 days |

In Onbeperkt Leren


A DevOps pipeline is a set of practices that the development (Dev) and operations (Ops) teams implement to build, test, and deploy software faster and easier. One of the primary purposes of a pipeline is to keep the software development process organized and focused. You start this course by learning about the various action type integrations that facilitate AWS CodePipeline configuration. Next, you will discover the various Azure Pipelines stages and define the role of approvals and gates. Finally, you’ll learn how to use the more advanced pipelines in Google Cloud Platform (GCP).


After completing this course, you have sufficient knowledge to implement DevOps pipelines in you daily work.


You have experience with software development and/or operations.

Target audience

Software Developer, Web Developer


DevOps Pipelines

6 hours

DevOps Pipelines: Using Action Type Integrations to Configure AWS 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.

DevOps Pipelines: Configuring & Building Core Elements of Azure Pipelines

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.

DevOps Pipelines: Configuring a GCP Pipeline

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.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 


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