Developing Applications with Google Cloud Platform

$1,995.00 USD

3 Days


Delivery Methods
Virtual Instructor Led
Private Group

Course 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.

Course Objectives

  • 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
  • Kubernetes Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex.
  • Who Should Attend?

    Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform
    • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
    • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
    • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
    • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
    • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
    • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

    Course Prerequisites

  • 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
  • Agenda

    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

    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

    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

    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
    • Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow
    • Lab: Store application data in Cloud Datastore

    5 - Performing Operations on Buckets and Objects

    • Operations that can be performed on buckets and objects
    • Consistency model
    • Error handling

    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

    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

    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

    9 - Adding Intelligence to Your Application

    • Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API

    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

    11 - Managing APIs with Google Cloud Endpoints

    • Open API deployment configuration
    • Lab: Deploy an API for your application

    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

    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

    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

    Upcoming Class Dates and Times

    Jul 24, 25, 26
    8:00 AM - 4:00 PM
    ENROLL $1,995.00 USD

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