Developing Applications with Google Cloud

Learn how to successfully conceptualise, design, develop and deploy applications that seamlessly integrate components from Google Cloud’s own ecosystem on this three-day course.

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3 day course
Partner of the Year
Virtual, Private
Virtual Classroom
A convenient and interactive learning experience, that enables you to attend one of our courses from the comfort of your own home or anywhere you can log on. We offer Virtual Classroom on selected live classroom courses where this will appear as an option under the location drop down if available. These can also be booked as Private Virtual Classrooms for exclusive business sessions.
A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

As a trusted Google Cloud Partner, Jellyfish has been selected by Google to facilitate the delivery of this three-day course.

Through a combination of presentations, demos, and hands-on labs, you’ll learn how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. We’ll share best practices for application development and using Cloud Datastore and Google Cloud Storage.

Our Developing Applications with Google Cloud course is delivered via Virtual Classroom. We also offer it as a private training session that can be delivered virtually or at a location of your choice in the UK.

Course overview

Who should attend:

This course is for application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud.

What you'll learn:

By the end of this course, you will be able to:

  • 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


To get the most benefit from this course you should have completed Google Cloud Fundamentals or have equivalent experience. We also recommend you have a working knowledge of Node.js, and basic proficiency with command-line tools and Linux operating system environments.

Course agenda

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 Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner
Module 4: Best Practices for Using Datastore
  • Best practices related to the following: Queries; Built-in and composite indexes; Inserting and deleting data (batch operations); Transactions; and error handling
  • Demo: Explore Datastores
  • Demo: Use Dataflow to bulk-load data into Datastore
  • Lab: Store application data in Cloud Datastore
Module 5: Performing Operations on Buckets & 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 Google Cloud Storage
  • Naming buckets for static websites and other uses
  • Naming objects (from an access distribution perspective)
  • Performance considerations
  • Lab: Store files in Cloud Storage
Module 7: Handling Authentication & Authorisation
  • Cloud 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 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
  • Demo: Invoke Cloud Functions Through Direct Request-response
  • Lab: Processing Pub / Sub Data using Cloud Functions
Module 11: Managing APIs with Google Cloud Endpoints
  • Open API deployment configuration
  • Lab: Deploy an API for the Quiz application
Module 12: Deploying an Application
  • 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: Computer Options for Your Application
  • Considerations for choosing an execution environment for your application or service
  • Platform comparisons
Module 14: Debugging, Monitoring & 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
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