2015
Lynda
Joseph Lowery
2:54
English
Why run a local server? Why let ISPs cap your bandwidth? Use Google's cloud-based Compute Engine to buy as much computing power as you need, when you need it, and for only as long as you need it. In this course, author Joseph Lowery shows how Compute Engine fits within the Google framework, and steps through project development in Compute Engine with two languages (JavaScript and Python), demonstrating how Google's virtual machines are managed programmatically. He also shows you how to coordinate resources and perform mission-critical tasks like load balancing.
Introduction
Welcome
Using the exercise files
Using the challenges
1. Introduction to Google Cloud Compute Engine
Understanding the inner workings of Compute Engine
Integrating with other Google Cloud products
Getting underway
2. Exploring Compute Engine
Setting up the Google Cloud SDK on a Mac
Setting up the Google Cloud SDK on a PC
Creating a Compute Engine instance
Accessing your project remotely
Setting up a cloud-based web server
3. Integrating User Authentication
Overview of Compute Engine authentication
Authorizing requests with OAuth 2.0
Working with service accounts
4. Developing with JavaScript and Compute Engine
Setting up the JavaScript client library
Authorizing requests
Displaying available instances and disks
Creating new instances
Removing instances
Challenge: JavaScript and Compute Engine
Solution: JavaScript and Compute Engine
5. Working with Python and Compute Engine
Establishing a Python runtime environment
Authorizing requests
Displaying available instances
Prepping to insert a new disk
Creating new instances
Challenge: Python and Compute Engine
Solution: Python and Compute Engine
6. Managing Resources with Compute Engine
Building your project team
Gearing up with an instance group
Working with Compute Engine metadata
Creating disk snapshots
Implementing network load balancing
Focusing resources with HTTP load balancing
Conclusion
Next steps
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