The course is part of this learning path
This course touches on the similarities and differences between AWS, GCP, and Azure serverless functions. The idea is to give you insight into what using the different offerings look like. The primary learning objective is to help you make an informed decision about which provider to use and if it fits your use case. The 30-minute course covers the three different providers (content largely taken from the comparing cloud platforms course--but cut down for content), deploying a sample application on each, and the ecosystem around deploying serverless applications. The provider lesson uses the same application and demonstrate deploying and other operational characteristics of each provider.
- IT Pros
If you are not already familiar with serverless start with "Getting Started with Serverless Computing” before continuing with this course. You’ll also need some experience with cloud providers as well. Nothing specific is required, though you should have a general idea of how cloud computing works.
- Understand the state of serverless in 2017 List trade-offs between AWS, Google, and Microsoft platforms
- Learn to build, deploy, and run applications on the three platforms
- Learn open source tools for building serverless applications
This Course Includes
30 minutes of high-definition video.
What You'll Learn
Course Intro: What to expect from this course.
Serverless Overview: In this lesson, we’ll introduce you to the key players and prepare you for the hands-on demos in the following lessons.
AWS Lambda: In this lesson, you’ll learn about serverless on Lambda and deploy a Lambda function.
Azure Functions: In this lesson, we’ll discuss serverless Azure functions and learn how to deploy an HTTP function.
Google Cloud Functions: In this lesson, you’ll learn about serverless on Google Cloud and deploy an HTTP trigger function.
Ecosystems and Tools: In this lesson, you’ll learn about serverless framework and Apex.
Conclusion: A summary and review of what you have learned.
Hello and welcome back to the Serverless survey course. I'm Adam Hawkins and I'm your instructor for this lesson. This lesson concludes the course. Our objective is to recap what we covered and set you up with next steps. We started with Serverless architecture. Remember that Serverless does not imply there are no servers. Instead, it's more aligned with the idea of functions as a service. There are still servers, just that they're not your responsibility. The provider handles scaling, maintenance, and all the other operational aspects.
You provide source code and they take care of the rest. From there, we moved on and got our hands dirty. We deployed an HTTP function and explored day to day use cases in AWS Lambda, Azure Functions, and Google Cloud Functions. All the providers support different triggers include live code editors, logging metrics, and compute resource configuration like memory or CPU, but they differ in support of run times and how well they're integrated into that given provider. Luckily, the ecosystem provides projects to smooth out some of the rough edges.
Lastly, we used Serverless and Apex frameworks to deploy sample applications. So, the next question for you is, what do you do next? Well, you need to build something. Pick a provider and try to build a Pubstub application. That will teach you about the different triggers and the provider itself. Also, try out different supporting tools with your own application. Cloud Academy also has you covered with great webinars and an entire Serverless learning path. Keep your eyes open for more in depth courses on AWS Lambda, Azure Functions, and Google Cloud Functions. Also, the getting started guides and supporting documentations are great, as well.
There's a lot in there if you give it a chance. And finally, don't hesitate to ask questions. You can reach me and the other instructors on the Cloud Academy community forum. So, my friend, that ends our Serverless survey. Good luck out there and happy shipping.
About the Author
Adam is backend/service engineer turned deployment and infrastructure engineer. His passion is building rock solid services and equally powerful deployment pipelines. He has been working with Docker for years and leads the SRE team at Saltside. Outside of work he's a traveller, beach bum, and trance addict.