By Marc Cohen, Kathryin Hurley, Paul Newson
Easy methods to run large-scale, data-intensive workloads with Compute Engine, Google’s cloud platform. Written by way of Google engineers, this instructional walks you thru the main points of this Infrastructure as a provider by way of exhibiting you ways to improve a undertaking with it from starting to finish. You’ll examine most sensible practices for utilizing Compute Engine, with a spotlight on fixing functional problems.
- entry and deal with Compute Engine assets with an internet UI, command-line interface, or RESTful interface
- Configure, customise, and paintings with Linux VM instances
- discover garage ideas: chronic disk, Cloud garage, Cloud SQL (MySQL within the cloud), or Cloud Datastore NoSQL service
- Use a number of inner most networks, and a number of situations on every one network
- construct, set up, and try an easy yet entire cloud computing software step-by-step
- Use Compute Engine with Docker, Node.js, ZeroMQ, internet Starter package, AngularJS, WebSocket, and D3.js
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Extra info for Google Compute Engine: Managing Secure and Scalable Cloud Computing
Py to substitute your project ID for the string your-project-id. py. We’ve changed the instance name (to avoid trying to create a VM with the same name as the one on which we’re running this exercise). json file containing sensitive authentication data. py command.
To suit your needs: """Retrieve project information using the Compute Engine API. com/compute/docs/api/getting-started. Creating an Instance Programmatically | 45 import httplib2 import os import sys from from from from apiclient import discovery oauth2client import file oauth2client import client oauth2client import tools # Parser for command-line arguments. 0 information # for this application, including client_id and client_secret. json') # Set up a Flow object to be used for authentication.