Course Content

• Module 1: Best Practices for Application Development
• Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
• Module 3: Overview of Data Storage Options
• Module 4: Best Practices for Using Google Cloud Datastore
• Module 5: Performing Operations on Buckets and Objects
• Module 6: Best Practices for Using Google Cloud Storage
• Module 7: Handling Authentication and Authorization Module
• 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application
• Module 9: Adding Intelligence to Your Application Module
• 10: Using Google Cloud Functions for Event- Driven Processing
• Module 11: Managing APIs with Google Cloud Endpoints
• Module 12: Deploying an Application by Using Google Cloud Cloud Build, Google Cloud Container Registry, and Google Cloud Deployment Manager
• Module 13: Execution Environments for Your Application
• Module 14: Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver

Detailed 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 Google 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 Google 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 Google 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

Module 12: Deploying an Application by Using Google Cloud Cloud Build, Google Cloud Container Registry, and Google Cloud Deployment Manager

• 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