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Google Cloud Fundamentals for AWS Professionals

This course teaches AWS professionals about the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for AWS system...

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$950 USD GSA  $545.24
Course Code GCP-FUND-AWS
Duration 1.125 days
Available Formats Classroom, Virtual
5236 Reviews star_rate star_rate star_rate star_rate star_half
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This course teaches AWS professionals about the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database. It is designed for AWS system administrators, solutions architects, and SysOps administrators who are familiar with AWS features and setup and want to gain experience configuring Google Cloud products immediately. This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud.

Skills Gained

This course teaches participants the following skills:

  • Identify Google Cloud counterparts for Amazon VPC, subnets, routes, NACLs, IGW, Amazon EC2, Amazon EBS, auto-scaling, Elastic Load Balancing, Amazon S3, Amazon Glacier, Amazon RDS, Amazon Redshift, AWS IAM
  • 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

  • What is cloud computing?
  • Google Cloud Computing architectures
  • The Google network
  • Google Cloud Regions and Zones
  • Google Cloud versus AWS regions and zones
  • Open API's
  • Multi-layered security approach
  • Budgets and Billing

Module 2: Getting Started with Google Cloud

  • Google Cloud resource hierarchy
  • Comparison to AWS resource hierarchy
  • Identity and Access Management (IAM)
  • IAM Roles
  • Comparison to Azure AD
  • Interacting with Google Cloud
  • Cloud Marketplace

Module 3: Virtual Machines in the Cloud

  • Virtual Private Cloud (VPC) Network
  • How AWS VPC differs from Google VPC
  • Compute Engine
  • Comparing Amazon EC2 and Google Compute Engine
  • Important VPC Capabilities
  • How typical approaches to load-balancing in Google Cloud differ from those in AWS

Module 4: Storage in the Cloud

  • Cloud Storage
  • Cloud Storage Interactions
  • Comparing Amazon S3 and Amazon Glacier with Google Cloud Storage
  • Cloud Bigtable
  • Cloud SQL and Cloud Spanner
  • Cloud Datastore
  • Comparing Amazon RDS with Google Cloud’s managed database services
  • Comparing Storage Options

Module 5: Containers in the Cloud

  • Containers in the Cloud
  • Kubernetes and Kubernetes Engine
  • Hybrid and Multi-Cloud
  • How Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) differ from GKE

Module 6: Applications in the Cloud

  • App Engine Standard Environment
  • App Engine Flexible Environment
  • Comparison to Azure App Service
  • Cloud Endpoints and Apigee Edge

Module 7: Developing, Deploying and Monitoring in the Cloud

  • Development in the cloud
  • Deployment: Infrastructure as code
  • How Cloud Deployment Manager differs from AWS CloudFormation
  • Monitoring: Proactive instrumentation
  • How Cloud Operations differs from Amazon CloudWatch and AWS CloudTrail

Module 8: Big Data and Machine Learning in the Cloud

  • Google Cloud Big Data Platform
  • Dataflow
  • BigQuery
  • How BigQuery differs from Amazon Redshift
  • Pub/sub and Datalab
  • How Cloud Pub/Sub differs from Amazon SQS
  • Google Cloud Machine Learning Platform
  • ML APIs
  • How GCP’s machine-learning APIs differ from AWS’s

Module 9: Summary and Review

  • Course Review
  • The Process of migrating from AWS to Google Cloud
  • Next Steps
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