The course is part of these learning paths
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 of 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 subjective, 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 product and service
- How to choose an appropriate deployment environment
- How to deploy an application to App Engine, Kubernetes Engine, and Compute Engine
- The different storage options
- The value of Cloud Firestore
- How to get started with BigQuery
This is an 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
- Anyone who would like to learn how to use Google Cloud Platform
Welcome back to Google Cloud Platform: Fundamentals. I'm Ben Lambert and I'll be your instructor for this lesson.
Hopefully by this point, you agree that Google Cloud Platform offers a lot of power and flexibility. Let's do a high-level overview of what we've covered throughout the course. The Google Cloud Platform offers a wide variety of services including infrastructure as a service and platform as a service, as well as a lot of APIs that allow us to incorporate some rather advanced functionality into our applications with ease. If we had to build our own translation or speech-to-text or even image recognition APIs, we'd invest an awful lot of time. But we have Google Cloud Platform which gives us those services. Let's go through some of the other services.
We have App Engine, which provides us with the items that are common to web applications and mobile back-ends, allowing developers to focus on code and not the underlying infrastructure. Google Cloud Platform has several storage options, covering blob storage to the different queryable storage methods, and most of them are built to be highly scalable.
We have Kubernetes Engine, which gives us the ability to create managed Kubernetes clusters, which can make it easier if we're also running Kubernetes outside of this cloud environment because we'll have one platform that we deploy all of our applications to regardless to where that cluster is located.
Compute Engine is a great way to have access to the raw components for creating networks and running virtual machines, and it provides us things like load balancers that scale so well that they don't even require pre-warming, which is very cool.
And the big data options allow us to query massive data sets very quickly as well as allowing us to run our Hadoop jobs in the cloud. Google Cloud Platform gains new service offerings all the time which means as these service options grow, we'll be able to easily incorporate the services that are useful to us into our applications.
Alright, that's going to wrap up this course. I hope you found this a helpful foundation for the Google Cloud Platform. Thank you so much for watching, and I will see you in a future course.
Ben Lambert is a software engineer 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 software, he’s hiking, camping, or creating video games.