EncartaLabs

Developing Applications with Google Cloud Platform

( Duration: 3 Days )

The Developing Applications with Google Cloud Platform training course provides skills 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, you will learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

By attending Developing Applications with Google Cloud Platform workshop, delegates will learn 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; use Google Kubernetes Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex.

  • Attend a training on Google Cloud Platform Fundamentals or have equivalent experience
  • Working knowledge of Node.js
  • Basic proficiency with command-line tools and Linux operating system environments

The Developing Applications with Google Cloud Platform class is ideal for:

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

COURSE 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
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
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
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
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
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
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
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
14

Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver

  • Stackdriver Debugger
  • Stackdriver 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

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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