Developing Applications with Google Cloud (GO6593)

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: Securing Your Application

• • 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: Using Cloud Endpoint to Deploy APIs

• • Open API deployment configuration
• • Lab: Deploy an API for your application

Module 12: Debugging Your Application by Using Google Stackdriver

• • Stackdriver Debugger
• • Stackdriver Error Reporting
• • Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting

Module 13: Deploying an Application by Using Google Cloud Container Builder, 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 Flex test and production environments

Module 14: Execution Environments for Your Application

• • Considerations for choosing an execution environment for your application or service: Google Compute Engine, Container Engine, App Engine Flex, Cloud Functions, Cloud Dataflow
• • Lab: Deploying your application on App Engine Flex

Module 15: Monitoring and Tuning Performance

• • Best practices and watchpoints for performance
• • Key concepts related to Stackdriver Trace and Stackdriver Monitoring
• • Detecting and resolving performance issues
• • Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance