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Developing Applications with Google Cloud

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Details
Categories:
Cloud Software and DevOps
Level:
Intermediate
Code:
GCPDA
Exam:
Yes - Available separately

Overview

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

Audience:

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



Prerequisites

What's included

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What is Virtual?

Live, instructor-led training delivered online

Enables teams or individuals to learn together without travel, maintaining interaction, discussion and practical exercises while minimising time away from the business and supporting scalable training delivery.

Who is it for: Individuals and teams needing flexible, instructor-led learning without time away from the business.

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Join in person or remotely, with the same live instruction, interaction and hands-on experience—wherever you are.

What's included?

3 Days instructor led course

Exam included

6 month free access to QA learning platform

Free 6-Month Access: Learning Platform Discovery plan

Included FREE with every instructor‑led course

Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.

Learn AI, Cloud, Data, and Leadership skills at your own pace.

Put skills into practice with hands-on Labs and Simulabs.

Validate knowledge and highlight gaps with skills assessments.

What is bespoke training? 

Custom instructor-led training designed by QA to fit your needs

Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.

Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.

 

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Dates

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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
  • 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
  • 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

Good to know

Why choose QA

Google Cloud learning paths

= Required
= Certification
Data Scientist
Data Engineer
Developer Software Development Experience
Architect Enterprise Architecture Experience
Administrator Windows Administrator Experience

Google Cloud Development learning paths

= Required
= Certification

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Cloud Portfolio Director - Cloud

Stuart leads the strategic direction of the cloud training portfolio, empowering organizations and individuals to build practical, scalable skills across AWS and other platforms. He designs learning experiences that make cloud adoption more accessible, efficient, and aligned to real-world business goals. Visit my page
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