Serverless Applications in the Cloud: Implementation Using Cloud Run
Google Cloud
| Intermediate
- 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
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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
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1m 50s
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10m 25s
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3. Cloud Run Architectures8m 14s
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4. Cloud Run Architecture Comparison7m 6s
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5. Features and Benefits of Cloud Run6m 33s
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6. Deploying to Cloud Run5m 49s
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7. Container Life Cycle on Cloud Run6m 22s
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8. Workflow Services to Orchestrate GCP Serverless6m 43s
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9. Google Cloud Platform Load Management6m 14s
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10. Cloud Tasks and Cloud Scheduler6m 4s
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11. Automated Building and Deploying with Cloud Run2m 29s
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12. Creating Cloud Run Services Using Cloud Code5m 11s
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13. Cloud Run Best Practices5m 51s
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14. Course Summary1m 18s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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