Google Cloud Platform: Fundamentals
The course is part of these learning paths
Google Cloud Platform for System Administrators
Google Cloud Platform for Solution Architects
Google Cloud Platform Fundamentals
Introduction to the Public Cloud Platforms
Cloud Architect – Professional Certification Preparation for Google
Google Cloud Platform for Developers
Google Cloud Platform: Fundamentals
If you’re going to work with modern software systems, then you can escape learning about cloud technologies. And that’s a rather broad umbrella. Across the three major cloud platform providers, we have a lot of different service options, and there’s a lot value in them all.
However, the area that I think Google Cloud Platform excels in is providing elastic fully managed services. Google Cloud Platform to me, is the optimal cloud platform for developers. It provides so many services for building out highly available - highly scalable web applications and mobile back-ends.
For me personally, Google Cloud Platform has quickly become my personal favorite cloud platform. Now, opinions are subject, but I’ll share why I like it so much.
I’ve worked as a developer for years, and for much of that time I was responsible for getting my code into production environments and keeping it running. I worked on a lot of smaller teams where there were no operations engineers.
So, here’s what I like about the Google Cloud Platform, it allows me to think about the code and the features I need to develop, without worrying about the operations side. Because many of the service offerings are fully managed.
So things such as App Engine allow me to write my code, test it locally, run it through the CI/CD pipeline, and then deploy it. And once it’s deployed, for the most part, unless I’ve introduced some software bug, I don’t have to think about it. Google’s engineers keep it up-and-running, and highly available. And having Google as your ops team, is really cool!
Another thing I really like about is the ease of use of things such as BigQuery and their Machine Learning APIs. If you’ve ever worked with large datasets, you know that some queries take forever to run. BigQuery can query massive datasets in just seconds. Which allows me to get the data I need quickly, so I can move on to other things.
And with the machine learning APIs I can use a REST interface to do things like language translation, or speech to text, with ease. And that allows me the ability to integrate this into my applications, which gives the end-users a better user experience.
So for me personally, I love that I can focus on building out applications; and spend my time adding value to the end-users.
If you’re looking to learn the fundamentals about a platform that’s not only developer friendly, but cost friendly, then this is the right course for you!
By the end of this course, you'll know:
- The purpose and value of each products and services
- How to choose an appropriate deployment environment
- How to deploy an application to App Engine, Container Engine, and Compute Engine
- The different storage options
- The value of cloud Datastore
- How to get started with BigQuery
This is a intermediate level course because it assumes:
- You have at least a basic understanding of the cloud
- You’re at least familiar with building and deploying code
What You'll Learn
SummaryA review of the course
|Lecture||What you'll learn|
|Intro||What will be covered in this course|
|Introducing Google Cloud Platform||An introduction to the Google Cloud Platform|
|Getting Started||A review of projects and permissions.|
|App Engine and Cloud Datastore||An intro to the PaaS option for building web apps and the NoSQL database that works so well with App Engine.|
|Cloud Storage Options||What options exist for data storage?|
|Container Engine||How do we run Docker containers in the cloud?|
|Compute Engine||The IaaS option on Google Cloud.|
|Big Data and Machine Learning.||What options exist for data processing and machine learning|
About the Author
Ben Lambert is the Director of Engineering and was previously the lead author for DevOps and Microsoft Azure training content at Cloud Academy. His courses and learning paths covered Cloud Ecosystem technologies such as DC/OS, configuration management tools, and containers. As a software engineer, Ben’s experience includes building highly available web and mobile apps.
When he’s not building the first platform to run and measure enterprise transformation initiatives at Cloud Academy, he’s hiking, camping, or creating video games.