Google Cloud Fundamentals Training 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.
Location and Pricing
This course is taught as a private, live online class for teams of 3 or more. All our courses are hands-on, instructor-led, and tailored to fit your group’s goals and needs. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for online corporate training, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
All student will learn how to:
- 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
Prerequisites
All attendees must have:
- Basic proficiency with networking technologies like subnets and routing
- Basic proficiency with command-line tools
- Experience with Microsoft Azure and IIS
Outline
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Introducing Google Cloud
- 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)
Getting Started with Google Cloud
- 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
Virtual Machines in the Cloud
- 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
Storage in the Cloud
- 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
Containers in the Cloud
- 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
Applications in the Cloud
- 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.
Developing, Deploying and Monitoring in the Cloud
- 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
Big Data and Machine Learning in the Cloud
- 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
Conclusion
- 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
Conclusion
Training Materials
All GCP training students receive comprehensive courseware.
Software Requirements
Students must have a modern web browser (ideally Chrome) and Internet access.
