Serverless Applications in the Cloud: Implementation Using Cloud Run

Google Cloud 2021
  • 14 Videos | 1h 20m 8s
  • Includes Assessment
  • Earns a Badge
Cloud Run on the Google Cloud Platform (GCP) enhances the experience of building and deploying scalable serverless applications. Use this course to become familiar with using Cloud Run on a GCP-powered, fully managed serverless platform. Explore Cloud Run architectures, the role of Knative, and how Cloud Run and Cloud Run for Anthos differ. Investigate the lifecycle of a Cloud Run container, services for defining serverless service workflows, and GCP's load balancing and autoscaling capabilities. Differentiate between Cloud Tasks and Cloud Scheduler and outline best practices for designing, implementing, testing, and deploying Cloud Run services. After completing the course, you'll be able to package a simple Node.js application into a container image, deploy it to Cloud Run, use Cloud Build triggers to automate builds and deployments to Cloud Run, set up Cloud Code extension on IntelliJ, and create Cloud Run services using Cloud Code's starter templates.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    recall the prominent serverless solutions afforded by GCP that can be used to build, develop, and deploy functions and applications
    recognize the Cloud Run architectures along with the role of Knative that help Google Cloud Run combine serverless with containers
    compare the differences between fully managed Cloud Run and Cloud Run for Anthos and how this awareness helps serverless architects select the right architecture
    recognize the key features and benefits provided by Cloud Run along with the prominent implementation scenarios of Cloud Run
    create a simple Node.js application, package it into a container image, upload the container image to a container registry, and deploy the container image to Cloud Run
    describe the end-to-end life cycle of a container on Cloud Run
  • recall the concept of workflows with the help of use cases and list the prominent services that help define workflows to orchestrate Google Cloud Platform serverless services
    recognize the load balancing and autoscaling capabilities afforded by Google Cloud Platform
    list the key features of Cloud Tasks and Cloud Scheduler that can be used to initiate actions outside of the immediate context and differentiate between Cloud Tasks and Cloud Scheduler
    work with Cloud Build to automate builds and deployments to Cloud Run with the use of a Cloud Build trigger to automatically build and deploy code
    install IntelliJ, set up the Cloud Code extension, and create a new Cloud Run service using one of Cloud Code's starter templates
    describe the recommended best practices that need to be applied when designing, implementing, testing, and deploying Cloud Run services
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 50s
    UP NEXT
  • Playable
    2. 
    GCP Serverless Solutions
    10m 25s
  • Locked
    3. 
    Cloud Run Architectures
    8m 14s
  • Locked
    4. 
    Cloud Run Architecture Comparison
    7m 6s
  • Locked
    5. 
    Features and Benefits of Cloud Run
    6m 33s
  • Locked
    6. 
    Deploying to Cloud Run
    5m 49s
  • Locked
    7. 
    Container Life Cycle on Cloud Run
    6m 22s
  • Locked
    8. 
    Workflow Services to Orchestrate GCP Serverless
    6m 43s
  • Locked
    9. 
    Google Cloud Platform Load Management
    6m 14s
  • Locked
    10. 
    Cloud Tasks and Cloud Scheduler
    6m 4s
  • Locked
    11. 
    Automated Building and Deploying with Cloud Run
    2m 29s
  • Locked
    12. 
    Creating Cloud Run Services Using Cloud Code
    5m 11s
  • Locked
    13. 
    Cloud Run Best Practices
    5m 51s
  • Locked
    14. 
    Course Summary
    1m 18s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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