Gain an understanding of the core capabilities of Google Cloud in the four technology pillars: networking, compute, storage, and database on this one-day instructor-led course.
1 day course
Supporting material
Google Cloud Partner of the Year
Private
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 fundamentals course, which is designed for Azure professionals familiar with Azure features and setup; and want to gain experience configuring Google Cloud products immediately.
Through a combination of presentations, demos, and hands-on labs, you will quickly gain an understanding of the similarities, differences, and initial how-tos.
This Google Cloud Fundamentals for Azure Professionals course is offered as a private training session. It can be delivered at our own training venue in the Arenco Tower, any location of your choice or via Virtual Classroom.
Jellyfish has recently been named a Google Cloud Specialisation Partner of the Year. This title recognises our commitment to provide world-leading Cloud-based Training solutions that help our clients succeed.
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 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
Understand, at a high level, the process of migrating from Azure 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, as well as command-line tools. It is recommended learners have experience with Microsoft Azure and IIS.
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 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 of 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: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore
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 Kubernetes Engine and Kubernetes
Understand how Azure Kubernetes Service differs 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
1 day course
Supporting material
Google Cloud Partner of the Year
Private