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Developing Applications with Google Cloud

  • Length 3 days
Course overview
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Why study this course

In this three-day course, students learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem.

The course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

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What you’ll learn

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


logo: Google Cloud Partner

Google Cloud at Lumify Work

Lumify Work is Australia's only national Google Cloud Authorised Training Partner. Get the skills needed to build, test, and deploy applications on this highly scalable infrastructure. Engineered to handle the most data-intensive work you can throw at it, Lumify Work can support you through training wherever you are in your Cloud adoption journey.


Who is the course for?

Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud.


Course subjects

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: Getting Started with Google Cloud Development

  • Overview of Google Cloud services for apps and scripts:

    • Google Cloud APIs

    • Cloud SDK

    • Cloud Client Libraries

    • Cloud Shell

    • Cloud Code

  • Demo: Google APIs Explorer

  • Lab: Setting up a Development Environment

Module 3: Overview of Data Storage Options

  • Overview of options to store application data

  • Use cases for Cloud Storage, Firestore, Cloud Bigtable, Cloud SQL, and Cloud Spanner

  • Demo: Connecting Securely to a Cloud SQL Database

Module 4: Best Practices for Using Datastore

  • Best practices related to using Firestore in Datastore mode for:

    • Queries

    • Built-in and composite indexes

    • Inserting and deleting data (batch operations)

    • Transactions

    • Error handling

  • Demo: Explore Datastore

  • Demo: Use Dataflow to Bulk-load Data into Datastore

  • Lab: Storing Application Data in Datastore

Module 5: Performing Operations on Buckets and Objects

  • Cloud Storage concepts

  • Consistency model

  • Demo: Explore Cloud Storage

  • Request endpoints

  • Composite objects and parallel uploads

  • Truncated exponential backoff

  • Demo: Enable CORS Configuration in Cloud Storage

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

  • Lab: Storing Image and Video Files in Cloud Storage

Module 7: Handling Authentication and Authorisation

  • Identity and Access Management (IAM) roles and service accounts

  • User authentication by using Firebase Authentication

  • User authentication and authorisation by using Cloud Identity-Aware Proxy

  • Lab: Adding User Authentication to your Application

Module 8: Using Pub/Sub to Integrate Components of Your Application

  • Topics, publishers, and subscribers

  • Pull and push subscriptions

  • Use cases for Cloud Pub/Sub

  • Lab: Developing a Backend Service

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

  • Demo: Invoke Cloud Functions Through Direct Request-response

  • Lab: Processing Pub/Sub Data using Cloud Functions

Module 11: Managing APIs with Cloud Endpoints

  • Open API deployment configuration

  • Lab: Deploying an API for the Quiz Application

Module 12: Deploying Applications

  • Creating and storing container images

  • Repeatable deployments with deployment configuration and templates

  • Demo: Exploring Cloud Build and Cloud Container Registry

  • Lab: Deploying the Application into Kubernetes Engine

Module 13: Compute Options for Your Application

  • Considerations for choosing an execution environment for your application or service:

    • Compute Engine

    • Google Kubernetes Engine (GKE)

    • Cloud Run

    • Cloud Functions

  • Platform comparisons

    • Comparing App Engine and Cloud Run

Module 14: Debugging, Monitoring, and Tuning Performance

  • Google Cloud’s operations suite

  • Managing performance

  • Lab: Debugging Application Errors

  • Logging

  • Monitoring and tuning performance

  • Identifying and troubleshooting performance issues

  • Lab: Harnessing Cloud Trace and Cloud Monitoring


Prerequisites

To get the most out of this course, participants should have:


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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