Mandy Waite, Warszawa marzec 2013


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Mandy Waite, Warszawa marzec 2013

  1. 1. Introduction to the Google Cloud PlatformMandy Waite, Google Developer Relations @tekgrrl
  2. 2. Google Cloud Platform Google Google Google BigQuery App Engine Compute Engine Interactive analysis of massive datasets at speed Scalable application Virtual machines development and execution environment Google Cloud SQL Run arbitrary workloads at scale Performant and scalable service for storing NoSQL Datastore and accessing data (e.g. Hadoop, scientific computing) Auto-scaling Frontends Long-lived Backends Task Queues Google Cloud Storage MySQL-based, fully managed service
  3. 3. Google App Engine
  4. 4. Opinionated web framework and deployment platform Easy to build Easy to scale Easy to maintain
  5. 5. Get up and running quickly - NO ServersSDK Python, Java, Go runtimes Local development server, EclipseGoogle Infrastructure Auto-scalesAdmin Console Easy management Logs
  6. 6. And growing: by the numbers Google App Engine passed 7.5B+ daily hits 2012 Google Google Cloud SQL Storage Storage GA Announce Announce Out ofPython Runtime Java Runtime Task Queues High Backends, Preview BigQuery Replication Pull Queues SLA Cloud SQL Announce Datastore Support GA BigQuery GA
  7. 7. A month in the life of Google App Engine: 1,000,000 active applications 2 Trillion datastore operationshalf of active world IP addresses touch GAE
  8. 8. Google App Engine HighlightsFully managed SQL & NoSQL servicesRich APIs and Services: Task Queues, Memcache, Search, Users, Cloud Endpoints, Socket, Image, Files...Flexible pricing: free to get started, SLA from $9/moRange of support packages:
  9. 9. Google App Engine European Data CentersCompliance and Locality Application Hosting in EU Data replicated within EU
  10. 10. “ With Google App Engine, we dont need a system administrator or anyone dedicated to deploying our app, so 99% of our time is working on our application.. ”Ben Kamens, Lead EngineerKahn Academy
  11. 11. Google Cloud EndpointsAPIs for Mobile and Web Backends Made Easy(Experimental) Storage (Datastore, SQL, Drive, etc) Endpoints Business Logic Web APIs
  12. 12. Search API(Experimental)Add Google-like full-text search toyour application ● Custom scoring and snippeting ● GeoSearch
  13. 13. Development Stack
  14. 14. Google Compute Engine
  15. 15. Introducing Google Compute EngineCompute Faster Scale Efficiently Save MoreVitrtual machines running on Rapidly scale to tens of thousands Benefit from low total cost ofGoogle environmentally friendly of cores on infrastructure designed ownership. Save more withInfrastructure. Ideal for: for large-scale computing Google Compute Engine. ● large scale data analysis ● Batch processing ● Variable size workloads.
  16. 16. Introducing Google Compute Engine Compute Network Storage ToolingLaunch Linux Virtual Machines Connect your VMs together to Store on persistent disk, local Control your VMs via REST API on demand form powerful clusters disk or Cloud Storage or command line Adding Virtual Machines to the Google Cloud Platform
  17. 17. Architecture
  18. 18. Whats in a VMLinux VMs ● Root access ● Debian-based Linux or CentOS ● Many hardware configurations ○ 1, 2, 4, or 8 CPUs ○ Up to 52GB of RAM
  19. 19. API Basics ● JSON over HTTP ● Main Resources (Nouns) ○ Projects ○ Instances ○ Networks and Firewalls ○ Disks and Snapshots ○ Zones ○ Actions (Verbs): ● GET, POST (create) and DELETE ○ Custom ‘verbs’ for updates ○ Auth via OAuth2
  20. 20. Clients and Libraries ● gcutil: command line utility ● Web UI: Built on GAE ● Libraries ● Partners and ecosystem
  21. 21. Flexible Storage Options Persistent Disk Ephemeral Disk Google Cloud Storage Fast, consistent performance Used to boot VM Seamless Authentication Network Connected, Replicated Lives and dies with VM Secure Access Snapshots for backup and restore Encrypted at Rest EU datacenter option Shareable Encrypted at Rest
  22. 22. i can haz Compute Engine? Right now: ● Limited preview ● Focused on compute intensive and batch workloads ● SLA and support available to commercial customers ● Apply: ● Talk to us! Were happy to discuss your use caseCC Image courtesy of London looks
  23. 23. Storing Data
  24. 24. Storage Systems at Google
  25. 25. Structured Data: NoSQL + SQL Schemaless Familiar MySQL Queries, Atomic Transactions Fully Managed Best for Internet Scale, Best for Bounded Scale, highly denormalizable DataSets structured DataSets Think Differently ... No Joins Experimental
  26. 26. Unstructured: Google Cloud Storage
  27. 27. Google BigQuery
  28. 28. Big Data at Google 72 hours 100 million gigabytes 425 million users
  29. 29. BigQuery gives you this power Store data with reliability, redundancy and consistency Go from data to meaning At scale ... Quickly!
  30. 30. How are developers using it? Game and social media analytics Infrastructure monitoring Advertising campaign optimization Sensor data analysis
  31. 31. Regular expressions on 15.7 billion rows...
  32. 32. Upload your Data Google Cloud BigQuery Storage
  33. 33. Google Spreadsheets via Apps Script
  34. 34. Google Spreadsheets via Apps Script
  35. 35. Libraries● Java● Python● .NET● PHP● JavaScript● Apps Script● ... more ...
  36. 36. Its a RESTful API
  37. 37. Wrap Up
  38. 38. Questions?
  39. 39. Thank you!