By Marc Cohen, Kathryin Hurley, Paul Newson
How to run large-scale, data-intensive workloads with Compute Engine, Google’s cloud platform. Written by means of Google engineers, this educational walks you thru the main points of this Infrastructure as a carrier by means of displaying you ways to enhance a venture with it from starting to finish. You’ll research top practices for utilizing Compute Engine, with a spotlight on fixing sensible problems.
With programming examples written in Python and JavaScript, you’ll additionally methods to use Compute Engine with Docker packing containers and different structures, frameworks, instruments, and prone. detect how this IaaS is helping you achieve unheard of functionality and scalability with Google’s complicated garage and computing technologies.
- 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 strategies: continual disk, Cloud garage, Cloud SQL (MySQL within the cloud), or Cloud Datastore NoSQL service
- Use a number of deepest networks, and a number of circumstances on each one network
- construct, set up, and attempt an easy yet entire cloud computing program step-by-step
- Use Compute Engine with Docker, Node.js, ZeroMQ, internet Starter equipment, AngularJS, WebSocket, and D3.js
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Extra info for Google Compute Engine: Managing Secure and Scalable Cloud Computing
Example text
Json file to the same directory. com/GoogleCloudPlatform/gce-oreilly. zip. 0 authorization is required for your application to gain access to your user’s Compute Engine resources. json file. 0 information # for this application, including client_id and client_secret. json') # Set up a Flow object to be used for authentication. PLEASE ONLY # ADD THE SCOPES YOU NEED. com/compute/docs/api/how-tos/authorization>. dat: # If the credentials don't exist or are invalid run through the native client # flow.
Along with a JSON document (BODY) which uses the configura‐ tion variables to specify our instance-creation request. insert()) referencing our project ID, desired zone, and the JSON document containing details of our instance-creation request. Because our request is asynchronous, we then enter a polling loop, repeatedly checking the results of our request for status DONE, which tells us our request has completed. py command. py Waiting for operation to complete. ] Waiting for operation to complete.
4 An instance resource dictionary, encoded in JSON, is being sent as the request body. py, we need to install the Google Python client library on our test-vm instance, which, in turn, requires us to install pip, a Python packagemanagement utility. whl (533kB): 533kB downloaded Installing collected packages: pip, setuptools Successfully installed pip setuptools Cleaning up... ] The following example shows the code you downloaded. ) to suit your needs: """Retrieve project information using the Compute Engine API.
