Google App Engine APIs Overview Feb March 2010

Google App Engine APIs : Overview Feb – March, 2010 Patrick Chanezon Developer Advocate Google Developer Relations chanezon@google. com 1

Agenda - App Engine introduction - Why build it? - App Engine tour - What's different? - Wrap up - Questions 2

What is cloud computing? Saa S Paa. S Iaa. S Place Postage Here 3

Iaa. S value proposition… 4

Google App Engine “We wear pagers so you don’t have to” 5

Google App Engine - Easy to build - Easy to maintain - Easy to scale 7

By the numbers - Built 100 K apps - Maintained by 250 K developers - Scaled to 250 M pageviews daily semi-transparent collage of apps 8

gigya Socialize 9

Gigya Socialize - traffic 10

App Engine 11

Why build it? 12

It's just too difficult 13

Hosting means hidden costs • Idle capacity • Software patches & upgrades • License fees • Lots of maintenance • Traffic & utilization forecasting • Upgrades 14

Cloud development in a box • SDK & “The Cloud” • Hardware • Networking • Operating system • Application runtime Java, Python Static file serving Services Fault tolerance Load balancing o • • 15

Easy to deploy & scale 1 2 http: //yourapp. bestbuy. com 16

Google App Engine Leveraging Google's platform to better serve your customers 17

Distributed Meme: Divide & Conquer Specialized services Memcache Datastore URL Fetch Mail XMPP Task Queue Images Blobstore User Service 18

Language runtimes Duke, the Java mascot Copyright © Sun Microsystems Inc. , all rights reserved. 19

Ensuring portability 20

Complete Java development stack 21

Google Plugin for Eclipse 22

Google Apps + your apps Our Google Apps Your custom applications Google's scalable serving architecture 23

Google Apps integration http: //appid. appspot. com/ http: //yourapp. yourdomain. com/ 24

Google Apps + App Engine 25

Federate your on-premise data 26

Secure Data Connector (SDC) 27

Secure Data Connector and 50+ more. . . 28

Your application's health 29

App Engine's health history 30

Distributed datastore http: //labs. google. com/papers/bigtable. html 31

Bigtable : A distributed, sharded, sorted array Row key Row data Shard 1 Shard 2 . . Shard n 32

Datastore design - Distributed - Bigtable + entity groups - ACID transactions - Optimistic concurrency - Entities + indexes - Protobuf encoded entities 33

Datastore properties - Core value types - List properties - Text & binary blobs - Reference 34

What's different? 35

Datastore - what's new - Distributed - Scales to 'internet scale' - No deadlocks - Predictable query performance 36

Datastore - what's different - No inner/outer/natural joins - Dense index scans - Per entity metadata - Soft schema - No more DDL 37

An evolving platform 38

23 months in review Apr 2008 May 2008 Jul 2008 Aug 2008 Oct 2008 Dec 2008 Feb 2009 Apr 2009 May 2009 Jun 2009 Aug 2009 Sep 2009 Oct 2009 Dec 2009 Feb 2010 Python launch Memcache, Images API Logs export Batch write/delete HTTPS support Status dashboard, quota details Billing, larger files Java launch, DB import, cron support, SDC Key-only queries Task queues Kindless queries XMPP Incoming email Blobstore Datastore cursors, Async Urlfetch 39

App Engine Roadmap - Support for mapping operations across datasets. Alerting system for exceptions in your application. Datastore dump and restore facility 40

Wrap up 41

Always free to get started ~5 M pageviews/month • 6. 5 CPU hrs/day • 1 GB storage • 650 K URL Fetch calls/day • 2, 000 recipients emailed • 1 GB/day bandwidth • 100, 000 tasks enqueued • 650 K XMPP messages/day 42

Purchase additional resources * * free monthly quota of ~5 million page views still in full effect 43

Thank you Read more http: //code. google. com/appengine/ Contact info Patrick Chanezon Developer Advocate chanezon@google. com http: //twitter. com/chanezon Questions ? 44

Thanks To Alon Levi, Fred Sauer, Brett Slatkin and others for their slides