Google Cloud Fundamentals for Azure Professionals

Google Cloud Fundamentals for Azure Professionals

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Recorded content
Of Total 10 Hrs.
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Duration
3 Months (50 hours)
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LIVE sessions
4 Workshops
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Hands-On Learning
With Practice Modules
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Certificate
With License

Overview

This Google Cloud Fundamentals for Azure Professionals training course teaches Azure professionals how to leverage the power of Google Cloud products immediately. Attendees learn the similarities and differences, as well as best Google Cloud Platform (GCP) practices.

Objective

  • Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake
  • Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing, storage, databases, IAM, and more
  • Manage and monitor applications
  • Explain feature and pricing model differences

Outline

  • • Advantages of Google Cloud
  • • The components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones
  • • The difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS)
  • • Identify the purpose of projects on Google Cloud
  • • How Azure's resource hierarchy differs from Google Cloud's
  • • Use cases for Identity and Access Management
  • • How Azure AD differs from Google Cloud IAM
  • • The methods of interacting with Google Cloud
  • • Launch a solution using Cloud Marketplace

  • • Use cases for Google Compute Engine
  • • Networking in Google Cloud
  • • How Azure VPC differs from Google VPC
  • • The similarities and differences between Azure VM and Google Compute Engine
  • • How typical approaches to load-balancing in Google Cloud differ from those in Azure
  • • Deploy applications using Google Compute Engine

  • • Use cases for Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore
  • • How Azure Blob compares to Cloud Storage
  • • Compare Google Cloud’s managed database services with Azure SQL
  • • How to choose among the various storage options on Google Cloud
  • • Load data from Cloud Storage into BigQuery

  • • Define the concept of a container and identify uses for containers
  • • Use cases for Google Container Engine and Kubernetes
  • • How Azure Kubernetes Service differs from Google Kubernetes Engine
  • • Provision a Kubernetes cluster using Kubernetes Engine
  • • Deploy and manage Docker containers using kubectl

  • • Use cases for Google App Engine
  • • Contrast the App Engine Standard environment with the App Engine Flexible environment
  • • How App Engine differs from Azure App Service.
  • • Use cases for Google Cloud Endpoints.

  • • Options for software developers to host their source code.
  • • Template-based creation and management of resources
  • • How Google Cloud Deployment Manager differs from Azure Resource Manager.
  • • Integrated monitoring, alerting, and debugging
  • • How Google Monitoring differs from Azure Application Insights and Azure Log Analytics.
  • • Create a Deployment Manager deployment
  • • Update a Deployment Manager deployment
  • • View the load on a VM instance using Google Monitoring

  • • Use cases for the products and services in the Google Cloud big data and machine learning platforms
  • • How Google Cloud BigQuery differs from Azure Data Lake
  • • How Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus.
  • • How Google Cloud’s machine-learning APIs differ from Azure's.
  • • Load data into BigQuery from Cloud Storage
  • • Perform queries using BigQuery to gain insight into data

  • • Review the products that make up Google Cloud and remember how to choose among them
  • • Understand next steps for training and certification
  • • The process of migrating from Azure to Google Cloud

Training Materials

All GCP training students receive comprehensive courseware.

Software Requirements

Students must have a modern web browser (ideally Chrome) and Internet access.

Why Online Bootcamps

Develop skills for real career growth

Cutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills

Learn by working on real-world problems

Capstone projects involving real world data sets with virtual labs for hands-on learning

Learn from experts active in their field, not out-of-touch trainers

Leading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.

Structured guidance ensuring learning never stops

24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts