Google Cloud Fundamentals for AWS Professionals

Name: Google Cloud Fundamentals for AWS Professionals
Start: 2020-11-11 00:00:00
Location: Virtual Classroom

If you're an AWS professional looking to explore the ease and power of Google Cloud solutions, then this one-day fundamentals course is ideal.

1 day course

Supporting material

Virtual, Private

Classroom

Face to face, interactive classroom training run from our global training centres.

Virtual Classroom

A convenient and interactive learning experience, that enables you to attend on of our courses from the comfort of your own home or anywhere you can log on. We offer Virtual Classroom on selected live classroom courses where this will appear as an option under the location drop down if available. These can also be booked as Private Virtual Classrooms for exclusive business sessions.

Private

A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

Jellyfish has been selected by Google to facilitate the delivery of this one-day course, which introduces AWS professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database.

This course is designed for AWS Solution Architects and professionals who are familiar with AWS features and setup; and want to gain experience configuring Google Cloud products immediately.

Through a combination of presentations, demos, and hands-on labs, you'll get details of similarities, differences, and initial how-tos quickly.

This Google Cloud Fundamentals for AWS Professionals course is offered as a Virtual Classroom course, which will be hosted from the UK on British Summer Time (BST). It is also available as a private training session and can be delivered at our own training venues in the Rosebank Link, Johannesburg or Umhlanga, or any location of your choice.

Course overview

Who should attend:

This course is intended for the following participants:

Individuals planning to deploy applications and create application environments on Google Cloud Platform
Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform
Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs

Walk away with the ability to:

Identify Google Cloud counterparts for AWS IaaS, AWS PaaS, AWS SQL, AWS Blob Storage, AWS Application Insights, and AWS 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
Understand, at a high level, the process of migrating from AWS to Google Cloud

Prerequisites

To get the most of out of this course, you should have basic proficiency with networking technologies like subnets and routing and command-line tools. In addition you should have experience with Amazon VPC, Amazon EC2 instances, and disks. Familiarity with Amazon S3 and AWS database technologies is also recommended.

Course agenda

Module 1: Introducing Google Cloud Platform

Explain the advantages of Google Cloud
Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones
Understand the difference between Infrastructure-as-a- Service (IaaS) and Platform-as-a-Service (PaaS)

Module 2: Getting Started with Google Cloud

Identify the purpose of projects on Google Cloud
Understand how AWS’s resource hierarchy differs from Google Cloud’s
Understand the purpose of and use cases for Identity and Access Management
Understand how AWS IAM differs from Google Cloud IAM
List the methods of interacting with Google Cloud Platform
Launch a solution using Cloud Marketplace

Module 3: Virtual Machines in the Cloud

Identify the purpose of and use cases for Google Compute Engine
Understand the basics of networking in Google Cloud Platform
Understand how Amazon VPC differs from Google VPC
Understand the similarities and differences between Amazon EC2 and Google Compute Engine
Understand how typical approaches to load-balancing in Google Cloud differ from those in AWS
Deploy applications using Google Compute Engine

Module 4: Storage in the Cloud

Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore
Understand how Amazon S3 and Amazon Glacier compare to Cloud Storage
Compare Google Cloud’s managed database services with Amazon RDS and Amazon Aurora
Learn how to choose among the various storage options on Google Cloud Platform
Load data from Cloud Storage into BigQuery
Perform a query on the data in BigQuery

Module 5: Containers in the Cloud

Define the concept of a container and identify uses for containers
Identify the purpose of and use cases for Google Kubernetes Engine and Kubernetes
Understand how Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) differ from GKE
Provision a Kubernetes cluster using Kubernetes Engine
Deploy and manage Docker containers using kubectl

Module 6: Applications in the Cloud

Understand the purpose of and use cases for Google App Engine
Contrast the App Engine Standard environment with the App Engine Flexible environment
Understand how App Engine differs from Amazon Elastic Beanstalk
Understand the purpose of and use cases for Google Cloud Endpoints

Module 7: Developing, Deploying, and Monitoring in the Cloud

Understand options for software developers to host their source code
Understand the purpose of template-based creation and management of resources
Understand how Cloud Deployment Manager differs from AWS CloudFormation
Understand the purpose of integrated monitoring, alerting, and debugging
Understand how Google Monitoring differs from Amazon CloudWatch and AWS CloudTrail
Create a Deployment Manager deployment
Update a Deployment Manager deployment
View the load on a VM instance using Google Monitoring

Module 8: Big Data and Machine Learning in the Cloud

Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms
Understand how Google Cloud BigQuery differs from AWS Data Lake
Understand how Google Cloud Pub/Sub differs from AWS Event Hubs and Service Bus
Understand how Google Cloud’s machine-learning APIs differ from AWS's
Load data into BigQuery from Cloud Storage
Perform queries using BigQuery to gain insight into data

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