Learn how to run large-scale, data-intensive workloads with Compute Engine, Google’s cloud platform. Written by Google engineers, this tutorial walks you through the details of this Infrastructure as a Service by showing you how to develop a project with it from beginning to end. You’ll learn best practices for using Compute Engine, with a focus on solving practical problems.
Access and manage Compute Engine resources with a web UI, command-line interface, or RESTful interface
Configure, customize, and work with Linux VM instances
Explore storage options: persistent disk, Cloud Storage, Cloud SQL (MySQL in the cloud), or Cloud Datastore NoSQL service
Use multiple private networks, and multiple instances on each network
Build, deploy, and test a simple but comprehensive cloud computing application step-by-step
Use Compute Engine with Docker, Node.js, ZeroMQ, Web Starter Kit, AngularJS, WebSocket, and D3.js
Chapter 1Getting Started
Creating a Compute Engine Project
Compute Engine Resources
Creating an Instance Using the Developers Console
Accessing an Instance Using the Developers Console
Marc manages Google's Developer Relations Engineering team in London, which helps software developers get the most out of the Google APIs and services in the EMEA region. In a previous life,Marc helped design and build communication systems at Bell Labs and Lucent Technologies. When he's not working, Marc enjoys indie music and films, writing, teaching, and chess.
Kathryn Hurley is a Developer Programs Engineer at Google for Compute Engine. In this role, she helps developers learn how to use the Compute Engine API by developing sample applications. She received an MS in Web Science from the University of San Francisco and a BS in Genetics from the University of California, Davis. Prior work experience includes research in mobile and peer-to-peer computing.
Paul Newson is a Software Engineer at Google. Currently, he is focusing on helping developers harness the power of the Google Could Platform to solve their Big Data problems. Prior to his current role in Developer Relations, Paul was helping build Google's Cloud Platform as an engineer on Google Cloud Storage. Before joining Google, Paul cofounded a tiny game technology startup, sold it to Microsoft, where he then worked on DirectX, Xbox, Xbox Live, and Forza Motorsport, before spending some time working on interesting machine learning problems in Microsoft Research. Outside of work Paul enjoys rock climbing, motorcycling, and other activities that demand complete focus.
The animal on the cover of Google Compute Engine is a Rufous treepie. This bird is native to India and other parts of southeast Asia, such as Thailand, Laos, and Pakistan. They find the majority of their diet in trees, feeding on fruits, seeds, and insects among other organisms. They are also known to eat the eggs and young of other birds.
Weight ranges are generally between 90-130 grams for both males and females. They have dark-colored heads that almost look black, but bright, orangish bodies. The eyes are a deep red color.
The rufous treepie is know to be a noisy bird with many calls. Some of these calls have been named by locals, such as the "bob-o-link" or "ko-tree." They're not shy, and will take food from strangers depending on their exposure to co-existing with humans. They have been known to be aggressive in getting food if they see an opportunity.
Many of the animals on O'Reilly covers are endangered; all of them are important to the world. To learn more about how you can help, go to animals.oreilly.com.
The cover image is from Wood's Animate Creation. The cover fonts are URW Typewriter and Guardian Sans. The text font is Adobe Minion Pro; the heading font is Adobe Myriad Condensed; and the code font is Dalton Maag's Ubuntu Mono.
It does a good job with the console, but I would like to see more. For example, the section on Cloud Datastore on page 112 has a title of "Creating and Retrieving Entities Programmatically from a VM"
It only shows how to create a VM (which didn't work because google has changed the commands) and to use google-api-python-client (which doesn't install due to permissions errors and I had to work around with a virtual environment inside the console).
It shows the data was loaded by the python script, but doesn't show how to query the data (there was only a short mention of GQL on page 109). No examples here.
Then it says you can bring your own database, but provides no further examples. Only a mention of cassandra on github.
Hope the errors can get cleaned up and that some more meat to the data options and ways to query that data (not just load it).
Bottom Line Yes, I would recommend this to a friend
The book is detailed and accurate and helps you get up and running fast. Of course it is difficult to review a book in mid-writing but if the quality and depth of the final sections is as good as the first, then there is a place for this in or on a system administrator's book shelf.
All the examples I tried worked and though you can find much of this in Google's own documentation, this is a bit easier to read, follow and search.
Bottom Line Yes, I would recommend this to a friend