Developing Applications with Google Cloud Platform

(3 days)

In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. 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

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

Module 12: Deploying ​an Application ​by ​Using ​Google ​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

** Notice: Cancellations will be charged an administrative fee through Eventbrite.