Developing Applications with Google Cloud
In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem.
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Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
Objectives
This course teaches participants the following skills:
- Use best practices for application development
- Choose the appropriate data storage option for application data
- Implement federated identity management
- Develop loosely coupled application components or microservices
- Integrate application components and data sources
- Debug, trace, and monitor applications
- Perform repeatable deployments with containers and deployment services
- Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex
Audience
Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform.
Prerequisites
To get the most of out of this course, participants should have:
- Completed Google Cloud Platform Fundamentals or have equivalent experience
- Working knowledge of Node.js
- Basic proficiency with command-line tools and Linux operating system environments
All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer.
Course Outline
Module 1: Best Practices for Application Development
-Code and environment management
-Design and development of secure, scalable, reliable, loosely coupled application components and microservices
-Continuous integration and delivery
-Re-architecting applications for the cloud
Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
-How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
-Lab: Set up Google Client Libraries, Google Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials
Module 3: Overview of Data Storage Options
-Overview of options to store application data
-Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner
Module 4: Best Practices for Using Cloud Datastore
-Best practices related to the following:
-Queries
-Built-in and composite indexes
-Inserting and deleting data (batch operations)
-Transactions
-Error handling
-Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow
-Lab: Store application data in Cloud Datastore
Module 5: Performing Operations on Buckets and Objects
-Operations that can be performed on buckets and objects
-Consistency model
-Error handling
Module 6: Best Practices for Using Cloud Storage
-Naming buckets for static websites and other uses
-Naming objects (from an access distribution perspective)
-Performance considerations
-Setting up and debugging a CORS configuration on a bucket
-Lab: Store files in Cloud Storage
Module 7: Handling Authentication and Authorization
-Cloud Identity and Access Management (IAM) roles and service accounts
-User authentication by using Firebase Authentication
-User authentication and authorization by using Cloud Identity-Aware Proxy
-Lab: Authenticate users by using Firebase Authentication
Module 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application
-Topics, publishers, and subscribers
-Pull and push subscriptions
-Use cases for Cloud Pub/Sub
-Lab: Develop a backend service to process messages in a message queue
Module 9: Adding Intelligence to Your Application
-Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API
Module 10: Using Cloud Functions for Event-Driven Processing
-Key concepts such as triggers, background functions, HTTP functions
-Use cases
-Developing and deploying functions
-Logging, error reporting, and monitoring
Module 11: Managing APIs with Google Cloud Endpoints
-Open API deployment configuration
-Lab: Deploy an API for your application
-Creating and storing container images
-Repeatable deployments with deployment configuration and templates
-Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments
Module 13: Execution Environments for Your Application
-Considerations for choosing an execution environment for your application or service:
-Google Compute Engine
-Kubernetes Engine
-App Engine flexible environment
-Cloud Functions
-Cloud Dataflow
-Lab: Deploying your application on App Engine flexible environment
Module 14: Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver
-Stackdriver Debugger
-Stackdriver Error Reporting
-Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting
-Stackdriver Logging
-Key concepts related to Stackdriver Trace and Stackdriver Monitoring.
-Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance
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