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Google Cloud Fundamentals for AWS Professionals

Course Details
Code: GCP-FUND-AWS
Tuition (USD): $950.00 • Classroom (1 day)
$950.00 • Virtual (1 day)
Course Details
GSA (USD): $509.57 • Classroom (1 day)
$509.57 • Virtual (1 day)

This 1-day instructor led course introduces AWS professionals to the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for Azure system administrators, Solution Architects and SysOps Administrators familiar with AWS features and setup; and want to gain experience configuring Google Cloud products immediately. With presentations, demos, and hands-on labs, participants get details of similarities, differences, and initial how-tos quickly.

Skills Gained

This course teaches participants the following skills:

  • 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

Who Can Benefit

This course is intended for the following participants:

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

Prerequisites

To get the most out of this course, participants should:

  • Have basic proficiency with networking technologies like subnets and routing
  • Have basic proficiency with command-line tools
  • Students are expected to have experience with Amazon VPC, Amazon EC2 instances, and disks. Familiarity with Amazon S3 and AWS database technologies is recommended.

Course Details

Course Outline

Module 1: Introducing Google Cloud

  • 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 Platform.
  • 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 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: Cloud Storage, Cloud SQL, Cloud Bigtable and 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 Container 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.

Summary and Review

  • Review the products that make up Google Cloud and remember how to choose among them
  • Understand next steps for training and certification
  • Understand, at a high level, the process of migrating from AWS to Google Cloud.
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