$1,995

Developing Applications With Google Cloud Platform, Virtual CDT

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Description

Developing Applications with Google Cloud Platform

(Formerly CPD200)

(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. A personal laptop is required for all workshops and will not be provided.

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: 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 ​Endpoints 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
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