Leveraging the power of Google Cloud Platform

This talk was delivered by Somsubhra Bairi in our very first GDG Campus Roadshow held at Ahmedabad University.

Transcript

1. Somsubhra Bairi Leveraging the power of
2. What is Cloud Computing?
3. cloud computing noun “the practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer”
4. Why has there been a sudden explosion in the cloud?
5. Before we move on, let's have a look at types of Cloud services available...
6. Infrastructure as a Service(IaaS)
7. Platform as a Service(PaaS)
8. Software as a Service(SaaS)
9. I want to write a cloud service but do I have enough resources?
11. provides you IaaS, PaaS and SaaS to develop your own cloud service
14. Google Cloud Platform
15. Yes, it can power ALL that!
17. Launching 100 Virtual Machines
18. • Flexible and familiar infrastructure. • High data security. • Load balancing and advanced networking. • Sub hour billing. Compute Engine
19. App Engine • Fully managed platform. • Popular programming language support. • Flexible and scalable application storage. • Auto scaling. • Versioning and traffic scaling. • Local developer tools. • Support for third party frameworks.
20. Getting started... https://developers.google.com/appengine/downloads
21. Guestbook example Every Appengine project has an app.yaml file
22. To run the application locally google_appengine/dev_appserver.py guestbook/
23. The local admin panel
24. To upload the application • Create an application at appengine.google.com • Upload the application using appcfg.py update guestbook/
25. Automatic scaling
26. View entire app logs
27. Mobile support with mobile backend starter
28. Cloud storage • Store application data. • API to easily access the stored data.
29. Cloud Datastore • A managed, NoSQL, schemaless database for storing non-relational data. • Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
30. Datastore comes with great administration tools
31. Datastore comes with great administration tools
32. Cloud SQL • Store and manage data using a fully- managed, relational MySQL database. • Google handles replication, patch management and database management to ensure availability and performance.
33. Google Cloud has a lot to offer for data crunchers too...
34. Google Prediction API Google's prediction engine in the cloud.
35. • Google's sophisticated machine learning technology • Available as an on-demand RESTful HTTP web service
36. Endless number of interesting applications...
37. How does it work? Step 1: Train The Prediction API finds relevant features in the sample data during training.
38. How does it work? Step 2: Predict The Prediction API later searches for those features during prediction.
39. An example: Determine application recommendations on Marketplace
40. • Goal: Increase relevancy on the Apps Marketplace via recommendations. • Customers: Businesses of various sizes and industries using Google Apps around the world. • Data: Sampling of previous installs of applications. • • Outcome: Predict applications which would be appropriate for a new customer visiting the site
41. Using Prediction API
42. Step 1: Upload • Training data: outputs and input features • Data format: comma separated value format (CSV), result in first column Upload to Google Storage
43. Step 2: Train Create a new model by training on data To train a model: Training runs asynchronously. To see if it has finished:
44. Step 3: Predict Apply the trained model to make predictions on new data
45. Google BigQuery Interactive analysis of large datasets in Google's cloud
46. • Google's large data adhoc analysis technology • Analyze massive amounts of data in seconds • Simple SQL-like query language • Flexible access • REST APIs, JSON-RPC, Google Apps Script
47. Use cases
48. Key capabilities of BigQuery • Scalable: Billions of rows • Fast: Response in seconds • Simple: Queries in SQL
49. Using BigQuery
50. Writing queries Common functions Additional statistical approximations
51. BigQuery via REST
52. Example: Wikipedia revision history
53. Other services...
54. Cloud Endpoints • Create RESTful services and make them accessible to iOS, Android and Javascript clients. • Automatically generate client libraries to make wiring up the frontend easy. • Built-in features include denial-of-service protection, OAuth 2.0 support and client key management.
55. Translate API Quickly and dynamically translate between thousands of available language pairs within your app, integrating with Google Translate.
56. Cloud DNS • Reliable, resilient, low-latency DNS serving from Google’s worldwide network of Anycast DNS servers. • Create DNS records with an easy to use command line interface, or program against a full featured RESTful API to customize the service to your specific needs.
57. Google Pub/Sub • Connect your services with reliable, many- to-many, asynchronous messaging hosted on Google's infrastructure. • Cloud Pub/Sub automatically scales as you need it and provides a foundation for building your own robust, global services.
58. https://developers.google.com/products/
59. Why Google Cloud Platform?
60. Run on the same infrastructure powering Google's products.
63. Focus on your product rather than administration, configuration, etc.
64. Scale to millions of users
65. Mix and match services
66. Performance you can count on
67. Excellent tech support
68. So who uses Google Cloud Platform?
69. Used by over 5 million applications
70. Identify this logo
71. Starter pack https://cloud.google.com/developers/starterpack/
72. Useful links https://cloud.google.com