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Jan 1

Developing Applications with Google Cloud Platform

January 1 @ 8:00 AM - 5:00 PM AEST

Virtual Class Virtual Class
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Developing Applications with Google Cloud Platform

This instructor led live training will help you learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This 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.

What you Will learn

What's Included?

Instructor Live Training

An instructor will answer your questions

OFFICIAL GOOGLE CLOUD CONTENT

Course content reflects the latest google cloud class

hands on labs

Real world hands on labs provided by Qwiklabs and supported by instructor

CertIficate of completion

Receive official certificate on completion of 80% of labs

Who's this course for?

Level

Language

Duration

Prerequisites

products

Course Content

Topics

  • 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

Objectivies

  • Design and develop secure, scalable, reliable, loosely coupled application components and microservices.
  • Understand how to re-architect applications for the cloud.

Activities

  • 1 quiz

Topics

  • How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google
    Firebase SDK
  • Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials

Objectives

  • Understand how to set up and use Cloud Client Libraries, the Cloud SDK, and Firebase SDKs.

Activities

  • 1 demo, 1 lab and 1 quiz

Topics

  • Overview of options to store application data
  • Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner

Objectivies

  • Choose the appropriate data storage option for application data.

Activities

  • 1 demo and 1 quiz

Topics

  • Best practices related to using Cloud Firestore in Datastore mode for:
    • Queries
    • Built-in and composite indexes
    • Inserting and deleting data (batch operations)
    • Transactions
    • Error handling
  • Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow
  • Lab: Store application data in Cloud Datastore

Objectives

  • Bulk-load data into Cloud Firestore by using Dataflow.
  • Understand best practices related to queries, built-in and composite indexes,
    inserting and deleting data (batch operations), and transactions error handling.

Activites

  • 2 demos, 1 lab and 1 quiz

Topics

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

Objectives

  • Understand how to name buckets for static websites and other uses, how to name objects (from an access distribution perspective), performance considerations, and setting up and debugging a CORS configuration on a bucket.

Activities

  • 2 ddemos, 1 lab and 1 quiz

Topics

  • 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

Objectives

  • Implement federated identity management.

Activities

  • 1 lab and 1 quiz

Topics

  • 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

Objectives

  • Understand Pub/Sub topics, publishers, and subscribers.
  • Understand pull and push subscriptions.
  • Explore use cases for Cloud Pub/Sub.

Activities

  • 1 lab and 1 quiz

Topics

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

Objectives

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

Activities

  • 1 quiz

Topics

  • Key concepts such as triggers, background functions, HTTP functions
  • Use cases
  • Developing and deploying functions
  • Logging, error reporting, and monitoring

Objectives

  • Use Google Cloud Functions for event-driven processing.

Activites

  • 1 demo, 1 lab and 1 quiz

Topics

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

Objectives

  • Understand OpenAPI deployment configuration.

Activities

  • 1 lab and 1 quiz

Topics

  • 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

Objectives

  • Understand how to create and store container images.
  • Create repeatable deployments with deployment configuration and templates.

Activities

  • 1 demo, 1 lab and 1 quiz

Topics

  • Considerations for choosing an execution environment for your application or service:
    • Google Compute Engine (GCE)
    • Google Kubernetes Engine (GKE)
    • App Engine flexible environment
    • Cloud Functions
    • Cloud Dataflow
    • Cloud Run
    • Lab: Deploying your application on App Engine flexible environment

Objectives

  • Explore considerations for choosing an execution environment for your
    application or service

Activities

  • 1 lab and 1 quiz

Topics

  • Application Performance Management Tools
  • 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

Objectives

  • Debug an application error by using Cloud Debugger and Error Reporting.
  • Use Cloud Monitoring and Cloud Trace to trace a request across services, observe,
    and optimize performance.

Activities

  • 1 demo, 2 labs and 1 quiz

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Ref: T-GCPDEV-I-01

Location

Online

Instructor

Axalon Academy
Email:
training@axalon.io
View Instructor Website

Other

Competencies
Intermediate
Learning Path
Cloud Developer, Database Engineer