Google Cloud Fundamentals for Azure Professionals

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.

This course teaches participants the following skills: 

• 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

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.
• Understand how Azure's resource hierarchy differs from Google Cloud's.
• Understand the purpose of and use cases for Identity and Access Management.
• Understand how Azure AD differs from Google Cloud IAM.
• List the methods of interacting with Google Cloud.
• 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.
• Understand how Azure VPC differs from Google VPC.
• Understand the similarities and differences between Azure VM and Google Compute Engine.
• Understand how typical approaches to load-balancing in Google Cloud differ from those in Azure.
• 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 Azure Blob compares to Cloud Storage.
• Compare Google Cloud’s managed database services with Azure SQL.
• Learn how to choose among the various storage options on Google Cloud.
• Load data from Cloud Storage into 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 Azure Kubernetes Service differs from from Google Kubernetes Engine.
• 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 Azure App Service.
• 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 Google Cloud Deployment Manager differs from Azure Resource Manager.
• Understand the purpose of integrated monitoring, alerting, and debugging.
• Understand 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.

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 Azure Data Lake.
• Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus.
• Understand 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.

Module 9: 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 Azure to Google Cloud.

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
• Have experience with Microsoft Azure and IIS