DevOps Pipelines: Configuring a GCP Pipeline

DevOps    |    Intermediate
  • 14 Videos | 1h 3m 2s
  • Includes Assessment
  • Earns a Badge
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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.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    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
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 18s
    UP NEXT
  • Playable
    2. 
    GCP DevOps Pipeline Benefits
    4m 43s
  • Locked
    3. 
    Using GKE Clusters for Continuous Deployment
    4m 57s
    FREE ACCESS
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    4. 
    Creating Repos and Setting up Triggers
    3m 55s
    FREE ACCESS
  • Locked
    5. 
    Creating Development Environments
    3m 10s
    FREE ACCESS
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    6. 
    Setting up Canary Deployments
    7m 41s
    FREE ACCESS
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    7. 
    Creating Cloud Build Config Files
    3m 47s
    FREE ACCESS
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    8. 
    Configuring CI/CD With GCP
    4m 13s
    FREE ACCESS
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    9. 
    GCP Components for Data Pipelines
    5m 24s
    FREE ACCESS
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    10. 
    Building Serverless Deployment Pipelines
    2m 42s
    FREE ACCESS
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    11. 
    GCP Components for Implementing IoT to Analytics
    5m 50s
    FREE ACCESS
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    12. 
    Writing Dataflow Pipelines for Analytics
    2m 37s
    FREE ACCESS
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    13. 
    Cloud Deployment Manager
    5m 5s
    FREE ACCESS
  • Locked
    14. 
    Course Summary
    1m 40s
    FREE ACCESS

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