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  • PRIVATE BATCH
  • PUBLIC PROGRAM
  • ON DEMAND
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Course Details

  • Course Overview
  • Skills Gained
  • Who Can Benefit
  • Prerequisite
  • Syllabus

In this intensive course, application developers will learn how to design, develop, and deploy applications that successfully integrate components from the Google Cloud ecosystem. Through a mix of demo, presentations, and hands-on labs, students learn how to use GCP services and pre-trained machine learning APIs to build scalable, secure and intelligent cloud-native applications.

  • Use best practices for application development.
  • Choose the applicable data storage option for application data.
  • Develop loosely coupled application components or microservices.
  • Efficiently implement federated identity management.
  • Integrate application components and data sources.
  • Execute repeatable deployments with containers and deployment services.
  • Debug, trace, and monitor applications.
  • Choose the appropriate application on runtime environment; use Google Kubernetes Engine as a runtime environment and then switch to a no-ops solution with Google App Engine Flex.
Application developers who want to successfully build cloud-native applications or redesign existing applications that will run on Google Cloud Platform

To get the most benefit from this course, participants should have the following prerequisites:

  • Those who Completed Google Cloud Platform Fundamentals or have equal experience
  • Practical knowledge of Node.js
  • Experince on basic proficiency with command-line tools and Linux operating system environments


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

Audience

  • Developer

Public Program Schedule

Course Name Duration Brochure Location Schedule Enroll
There is no upcoming Public Batch Schedule, you can ask for Private Batch or for On-Demand Learning

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FAQ

  • What is a Google Cloud certification?
  • Why should I get a Google Cloud certification?
  • How long is a Google Cloud certification valid?
  • What is the recertification policy?
  • Why do I need to recertify?
  • How do I pay?
  • What are your cancellation & refund policy?

Google Cloud's certification program gives Google Cloud users, customers and partners a way to demonstrate their technical skills in a particular job role or technology. Individuals are assessed using a variety of rigorously developed industry standard methods to determine whether they meet Google Cloud's proficiency standards.

Google Cloud certifications give you benchmarks for your professional development. They help you gauge your skill set against your peers and demonstrate your value to hiring managers.

Unless explicitly stated in the detailed exam descriptions, all Google Cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status.

Unless explicitly stated in the detailed exam descriptions, all Google cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status and certificate number.

Google technology changes frequently. We require recertification to ensure you're maintaining your skills.

We accept all modes of payment. If you are being nominated by your organization, your organization need to release PO before the course start date. If you are an individual you can pay through credit / debit cards, online transfer (RTGS/NEFT) to our account 7 days prior to the course start date.

  • In a highly unlikely event of cancellation of batch from our end, we shall refund 100% that is paid by you. If client choose to cancel for any reasons, below is the terms.
  • If you cancel or reschedule your registration 5 or more calendar days before the scheduled start date of the class – No cancellation charges
  • If you cancel or reschedule your registration less than 5 calendar days before the scheduled start date of the class – cancellation charges 100% of the course fee
  • If you do not show up for the event, or cancel on the day of the event - cancellation charges 100% of the course fee

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