IT Professional Curricula     Internet and Network Technologies Solution Area     Cloud Computing     Serverless with Cloud Run

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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.

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Objectives

Serverless Applications in the Cloud: Implementation Using Cloud Run 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