Google Cloud Compute and Scalability for Azure Professionals
Google Cloud Compute and Scalability for Azure Professionals
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This is the second course of a four-course series for cloud architects and engineers with existing Azure knowledge. It aims to compare Google Cloud and Azure solutions and guide professionals on their use.
This course focuses on compute resources and load balancing in Google Cloud. The learner will apply the knowledge of using virtual machines and load balancers in Azure to explore the similarities and differences with configuring and managing compute resources and load balancers in Google Cloud. Learners will get hands-on practice building and managing Google Cloud resources.
Course Info
Objectives
- Create and configure a Compute Engine instance in Google Cloud.
- Explain the difference between Google Cloud images and Azure Custom Images.
- Compare and contrast Cloud Load Balancing with Azure Load Balancers.
- Explain the best use case for each specific type of load balancer (HTTP, TCP, SSL, Network, and Internal).
- Describe managed instance groups (MIGs) and how to use them.
Prerequisites
Familiarity with Azure terms and concepts
Audience
Cloud Architects or Cloud Engineers who are experienced with Azure cloud.
Available languages
English
What do I do when I finish this course?
After finishing this course, you can explore additional content in your learning path or browse the catalog.
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Interested in taking this course with one of our authorized on-demand partners?
Explore Google Cloud content on Coursera and Pluralsight.
Prefer learning with an instructor?
View the public classroom schedule here.
Can I take this course for free?
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