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Google Cloud Platform
Getting Started with Google's Infrastructure and Platform
!
!
+ColinSu
Developer Expert, Google Cloud Platform
Software Architect, Tagtoo
A Tour of Google Cloud Platform
Google Cloud Platform
Slides are available on slideshare.net
goo.gl/ARRyaq
Google Cloud Platform
> Overview of Google Cloud Platform
> Google App Engine - Platform-as-a-Service in Google Cloud
> App Services in Google Cloud Platform
> Google Compute Engine - Infrastructure-as-a-Service in Google Cloud
> BigData Lab - What we did in GCDC 2013?
Outlines
Google Cloud Platform
Overview
Google Cloud Platform
Google Cloud Platform
Why do we need Cloud?
Google Cloud Platform
> Why
+ too much data that your PC/servers couldn't store
+ too much computation your PC/servers couldn't deal with
+ your PC/servers are hard to scale
> Why not
+ need a website
+ it sounds cool
Google Cloud Platform
Why should we use Google Cloud Platform?
Google Cloud Platform
> Access Control

public, private networks

block storage
> Encryption

all block storages will be encrypted on the
cloud, no worries about leaks
> Encapsulation

all instances, virtual machines, networks or
any resources will be encapsulated to
prevent any other ones take over your
precious stuffs
Highly Secured Cloud
by Google
Google Cloud Platform
> You will be using Google's Infrastructure

Virtual Machines

Networks

Storage
> And be placed in a safe place

Google's Data Center
> And Google will do those for you

Scaling

Migrating

Maintenance

Take over anything you don't wanna do

Powered by Google
Google Cloud Platform
> The best way how Google share their
+ Cloud Infrastructure
+ Cloud Knowledge
+ Cloud Engineers
> Your own data center, with minimum cost
as possible as it could be
So What is Google Cloud Platform
Google Cloud Platform
Google Cloud Family
Computing
Compute Engine
App Engine
Storage
Cloud SQL
Datastore
Cloud Storage
App Services
Cloud Endpoints
Big Query
Google Cloud Platform
> Manage all API services on Google
Cloud 

(e.g. Translation API, Prediction API, Maps API...)
> Compose equivalent commands for:

Command-line tools (Google Cloud SDK)

RESTful API
> Dashboard for monitoring all
resources on Google Cloud Platform
Cloud Developer Console
Google Cloud Platform
> Install/uninstall/upgrade all
command-line tools related to Google
Cloud Platform
> Notification for new release of any
Cloud SDK component
> Automatization
Google Cloud SDK
Google Cloud Platform
Storage
Storage Services in Google Cloud Platform
Google Cloud Platform
> It's MySQL, but managed by Google
> Relational Data Storage on Google Cloud
> Use Cases
+ LAMP Applications
+ Google App Engine
Cloud SQL
Google Cloud Platform
> Non-relational database (NoSQL)
> Schema-less data
> Use Cases
+ Highly scalable application
Cloud Datastore
Google Cloud Platform
> Protected

Your data is protected at multiple physical locations
> Strong, configurable security

OAuth or simple access control on your data
> Multiple usages
+ Serve static objects directly
+ Use with other Google Cloud products (Bridge)
Cloud Storage
Google Cloud Platform
App Services
Power Up Your Applications in Google Cloud Platform
Google Cloud Platform
> Data Analysis Tool
+ BigQuery
+ Google Prediction API
> Cloud Endpoints
> Google Cloud DNS
App Services in Google Cloud Platform
Google Cloud Platform
> Analyze terabytes of data, just a click of a button
> Super-fast, SQL-like queries
> Convenient import/export mechanism
Big Query
RUN QUERY
Google Cloud Platform
> Previewing of data
> Statistics of tables
> History/Cached Result
> Save query result as another
BigQuery table
BigQuery Browser Tool
Google Cloud Platform
Popular Languages on Github
!
SELECT repository.language, COUNT(repository.language) as num
FROM [publicdata:samples.github_nested]
GROUP BY repository.language
ORDER BY num DESC
LIMIT 10
BIGQUERY
1.6s elapsed, 12.8 MB processed
Google Cloud Platform
> Command-line Tool

a full-featured command-line tool is included in Google Cloud SDK, called bq
> RESTful API

a set of APIs is ready for helping you to control all components and data on your BigQuery
> BigQuery Connector for Excel

Microsoft Excel? No problem, we have an extension for your excel to query over your excel data
> Third-party Tools
> Make your own
More Ways To Use BigQuery
Google Cloud Platform
> generate APIs and client libraries from an App
Engine application
> make it easier to share web backend for mobile
applications
Cloud Endpoints
Google Cloud Platform
Cloud Endpoints Architecture
iOS

Objective-C Client Library
Android

Java Client Library
Web Browser

JavaScript Client Library
Google Cloud Endpoints
Google App Engine

API Backend Instances
Google Cloud Platform
> Website

solid integration, define APIs in Google App Engine
application and generate JavaScript client library with
Endpoints, no more handmade AJAX
> API Server

define APIs with Endpoints API, then it will be a RESTful API
service immediately
> Mobile Applications

Backend-as-a-Service

define reusable APIs with GAE various services, then
generate client libraries for iOS, Android and web browser to
share the resources you have
Use Cases
Google Cloud Platform
> Machine Learning
+ Categorical
+ Regression
> Pattern-matching
> Simple API Interface
Prediction API
Google Cloud Platform
> Recommendation System

Predict what will be liked by your users
> Filtering spams

Categorizes messages as spam or non-spam
> Semantic Analysis

Know how your users feel, given your comments
What can you do with Prediction API
Google Cloud Platform
> Language Identifier
> Tag Categorizer
> Sentiment Predictor
Prediction Model Gallery
Google Cloud Platform
Try Prediction
Google Cloud Platform
Google App Engine
Platform-as-a-Service in Google Cloud Platform
Google Cloud Platform
How did you build a full-functional web service?
a scalable, high-performance, fault-tolerant service
Google Cloud Platform
> LAMP
+ Linux
+ Apache
+ MySQL
+ Programming Languages
> Failed: not scalable
Traditional Way: LAMP
Apache
MySQL
Google Cloud Platform
> Power up Apache2 army!
> Failed: database is alone, too busy
You Need Load Balancing
Apache
MySQL
Apache Apache
Google Cloud Platform
> Replication (Master/Slave)
> Failed: Master may die
Now Scale Database
Apache
MySQL
Apache Apache
MySQL
Master

Read/Write
Slave

Read
Replication
Google Cloud Platform
Life is good, don't waste it
Google Cloud Platform
> You should care
+ Application code
+ Automated Scaling
> You should not care
+ Server management (networking, cores, memory, disks...)
+ Bootstrapping
+ Deployment
Platform-as-a-Service
Google Cloud Platform
> Application code gets executed (Runtime)
> Static Content gets served (CDN)
> Data gets stored (Database)
> Server gets secured (Sandbox)
> Service gets scaled (and automatically)
How PaaS Work
Google Cloud Platform
Application

Code
Front End
Load Balancer
Routing
Security
DNS Setting
Storage
SQL/NoSQL
Memcache
Static Content
Block Storage
Service Support
Mail
Authentication
Socket
Auto Scaling
Cron Job
Queue
Your Responsibility
Google's Responsibility
Google Cloud Platform
> Sandboxed containers with various runtimes
> Easy to build

All you need to do is preparing your application code
> Easy to run

Deploy with a single command, and it works
> Easy to scale

scale on GAE is automated and easy to configure
Google App Engine
Google Cloud Platform
> Java

Java Servlets interface

Support for standard interfaces to App Engine scalable services such as JDO, JPA, JavaMail and JCache
> Python

Python 2.7 and full support for any pure Python libraries, tools and frameworks

Built-in Compiled C-extension libraries are good to go
> PHP

Currently in "Preview" stage

But enough for your "Wordpress"
> Go

Currently in "Experimental" stage

automated build service included, no need to rebuild when code changed

and interface similar to the standard Go http package

Languages and Runtimes
Google Cloud Platform
Workflow of Google App Engine
Create a
GAE Project
Programming
Testing
Production
Google Cloud Platform
> Datastore

schema-less, scalable object data storage

rich data modeling API

SQL-like query language, GQL (Google Query Language)
> Cloud Storage

strong, flexible, distributed storage service for serving or storing static files
> Search

Google-like search on structured data, such as full text, numbers, dates and geographic locations
> Memcache

a distributed, in-memory data cache to greatly improve your applications
> Logs

programmatic access to logging system

a full functional control panel in Cloud Console, better than a gzip file
> Migration/Backup Tools
Data on Google App Engine
Google Cloud Platform
> Channel

Create a persistent connection between your application and Google servers

Send messages to JavaScript clients in real-time
> Mail

send email messages on behalf of admin or Google account users

receive mails at various custom email addresses
> URL Fetch

Efficiently issue HTTP or HTTPS requests on your web application
> Outbound Socket

Socket support without requiring any special App Engine libs or any special App Engine ( import socket in Python)
> XMPP

Enable you application to send and receive chat messages to/from any XMPP-compatible messaging service (e.g. Facebook
Chat, previous Google talks...)
Communication
Google Cloud Platform
> Task Queue

allow your application to asynchronize user requests, and organize them to be executed later
> Scheduled Task (Cron Job)

configure regular tasks at scheduled times or regular intervals
Process Management
Google Cloud Platform
> Modules

Create instances for exempting from request deadlines and request more memory and CPI resources for computing
> MapReduce

optimized adaptation of the MapReduce computing model for efficient distributing computation on large data sets
> Images API

Manipulate, combine and enhance images

Convert images between formats

Query metadata of images (height/width, colors)
Computation
Google Cloud Platform
Related Projects & Libraries
Extend Your App Engine to Work on Large-scale Computation
Google Cloud Platform
> Connects together complex, time-consuming workflows
> Asynchronize tasks
> Built-in pipelines or implement your own pipelines
Pipeline
Google Cloud Platform
Create a Pipeline
from pipeline import common
!
class CountReport(pipeline.Pipeline):
!
def run(self, email_address, entity_kind, property_name, *value_list):
split_counts = yield SplitCount(entity_kind, property_name, *value_list) # pipeline to gain
count result
yield common.Log.info('SplitCount result = %s', split_counts)
!
with pipeline.After(split_counts):
with pipeline.InOrder():
yield common.Delay(seconds=1)
yield common.Log.info('Done waiting')
yield EmailCountReport(email_address, split_counts) # another sending mail pipeline
PYTHON
Google Cloud Platform
Pipeline Console
Google Cloud Platform
> Programming model for processing large data sets in a parallel and
distributed algorithms on a cluster
> differ from map/reduce, one of functional programming conception, but has
the same idea, "divide and conquer"
> Proposed by Google
> Hadoop-free
MapReduce Library
https://developers.google.com/appengine/docs/python/dataprocessing/mapreduce_library
Google Cloud Platform
> map()/reduce() in Python
> map(func(elem), list) -> list
> reduce(func(elem1, elem2), list) -> elem
MapReduce in Functional Programming
>>> map(lambda x: x*2, [1,2,3,4])
[2,4,6,8]
!
>>> reduce(lambda x,y: x+y, [1,2,3,4])
10
!
PYTHON
Google Cloud Platform
> Map
> Shuffle
> Reduce
MapReduce: Stages
Google Cloud Platform
Configure a MapReduce Pipeline
class WordCountPipeline(base_handler.PipelineBase):
!
def run(self, filekey, blobkey):
output = yield mapreduce_pipeline.MapreducePipeline(
"word_count", # name of mapreduce job
"main.word_count_map", # mapper function
"main.word_count_reduce", # reducer function
"mapreduce.input_readers.BlobstoreZipInputReader", # input reader
"mapreduce.output_writers.FileOutputWriter", # output writer
mapper_params={ # parameters to supply to the input reader
"input_reader": {
"blob_key": blobkey,
},
},
reducer_params={ # parameters to supply to the output writer
"output_writer": {
"mime_type": "text/plain",
"output_sharding": "input",
"filesystem": "blobstore",
},
},
shards=16) # number of shards
yield StoreOutput("WordCount", filekey, output)
PYTHON
Google Cloud Platform
MapReduce Monitoring
Google Cloud Platform
Google Compute Engine
Infrastructure-as-a-Service in Google Cloud Platform
Google Cloud Platform
> Google has resources
+ CPU Cores
+ Memory
+ Networking
+ Persistency (Disks, Snapshot, Cloud Storage...)
+ Well-trained engineering monkeys
> You have business and be busy
Infrastucture-as-a-Service
Google Cloud Platform
> High-performance virtual machines

from micro-VM to large instance
> Powered by Google's global network

you could build a large cluster with strong and consistent bandwidth, provided by
Google
> Load Balancing

spread incoming traffic across instances
> Fast Bullet Reloading

quick deployment of large VMs

command-line interface

web-based console
> Highly secured

All data written to disk in Compute Engine will be encrypted by high-class
encryption algorithm
Google Compute Engine
Google Cloud Platform
> KVM-based Virtual machines
> Fast booting time

routinely takes less than 30 secs
> Various OS support
> Various machine types
Instances on GCE
http://gce-demos.appspot.com
Google Cloud Platform
Operating Systems
Google Cloud Platform
Operating Systems
Premier Only
Google Cloud Platform
> a unit of CPU capacity used to describe the compute power of instance
types
> 2.75 GCEUs = 1 minimum power of 1 logical core on Sandy Bridge platform
Google Compute Engine Units (GCEUs)
=
Google Cloud Platform
Machine Types (Shared-Core)
f1-micro
Shared Core
0.6 GB Memory
g1-small
1 Core
1.7 GB Memory
1.38 GCEUs
Google Cloud Platform
Machine Types (Standard)
n1-standard-n
Starts from 1 Core
Start from 3.75 GB Memory
n Virtual CPUs Memory GCEUs
1 1 3.75 GB 2.75
2 2 7.50 GB 5.50
4 4 15 GB 11
8 8 30 GB 30
16 16 60 GB 60
Google Cloud Platform
Machine Types (High Memory)
n1-highmem-n
Starts from 2 Core
Start from 13 GB Memory
n Virtual CPUs Memory GCEUs
2 2 13 GB 5.50
4 4 26 GB 11
8 8 52 GB 22
16 16 104 GB 44
Google Cloud Platform
Machine Types (High CPU)
n1-highcpu-n
Starts from 2 Core
Start from 1.8 GB Memory
n Virtual CPUs Memory GCEUs
2 2 1.8 GB 5.50
4 4 3.6 GB 11
8 8 7.2 GB 22
16 16 14.4 GB 44
Google Cloud Platform
Regions & Zones
us-central1-a

us-central1-b
europe-west1-a

europe-west1-b
Singapore?
Taiwan?
Google Cloud Platform
> Transparent Maintenance
> Auto restart instances shutdown by system events
> During transparent maintenance, you could set GCE to handle your
instance in two ways:
+ Live migrate

affect performance in some degree

but remain your instances online (no downtime)
+ Terminate and reboot
Live Migration
Google Cloud Platform
> Virtual SCSI device
> Block Storage
> Persistent until deleted
> Hot-plug to GCE instances (attach/deattach)
Persistent Disk
Google Cloud Platform
> Primary Disk: OS boot volume
Persistent Disk Mode
GCE Virtual Machine
Root
Stateful Root Volume
Google Cloud Platform
> Additional Disk: Read/Write Mode for user managed data volume
Persistent Disk Mode
GCE Virtual Machine
Root
Stateful Root Volume
RW Data
Stateful Data Volume
Google Cloud Platform
> Distribution Disk: Instant distribution of static content
Persistent Disk Mode
GCE Virtual Machine
RO Data
Read-Only Data Volume
GCE Virtual MachineGCE Virtual Machine
Google Cloud Platform
> Target Pools
> Health Checking
> Forwarding Rules

iptables for target pools
Load Balancing
Google Cloud Platform
> CGE reserved IP for instance, won't change with the reboot of VMs
> You can promote ephemeral IP to persistent IP
> no DNS changing anymore
Persistent IP Addresses
Google Cloud Platform
> Networking is first-class object on GCE

which means you could apply/unapply it anytime easily
> pre-defined networks before the first instance started
Integrated Networking
Google Cloud Platform
> Those resources are global resources
+ Images (OS Images)
+ Snapshots
+ Network
+ Firewalls
+ Routes
> And they're also first-class object in GCE
Multi-Region Resources
Google Cloud Platform
> Scalr
> Right Scale
Services Host GCE
Google Cloud Platform
BigData Lab
One of the finalists in Google Cloud Developer Challenge 2013
Google Cloud Platform
> http://www.google.com/events/gcdc2013/
> developers in 6 regions envolved
> goals
+ effective use of Google App Engine
+ originality of concept
+ integration and creative use of Google Products
Google Cloud Developer Challenge
Google Cloud Platform
> Provide a simple web interface to perform 4 big data
operations:
+ Storing (Data Source)
+ MapReduce
+ Prediction (Machine Learning)
+ Visualization
BigData Lab
Google Cloud Platform
> Google App Engine & Google Compute Engine
> Cloud Endpoints
> Google Cloud Storage
> MapReduce Module for Google App Engine
> Pipeline Module for Google App Engine
> Prediction API
> BigQuery
What Are We Using?
Google Cloud Platform
Demo
Google Cloud Platform
EOF


Thanks For Listening

+GDGTaipei
Google Cloud Platform
Questions?

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A Tour of Google Cloud Platform

  • 1. Google Cloud Platform Getting Started with Google's Infrastructure and Platform ! ! +ColinSu Developer Expert, Google Cloud Platform Software Architect, Tagtoo A Tour of Google Cloud Platform
  • 2. Google Cloud Platform Slides are available on slideshare.net goo.gl/ARRyaq
  • 3. Google Cloud Platform > Overview of Google Cloud Platform > Google App Engine - Platform-as-a-Service in Google Cloud > App Services in Google Cloud Platform > Google Compute Engine - Infrastructure-as-a-Service in Google Cloud > BigData Lab - What we did in GCDC 2013? Outlines
  • 5. Google Cloud Platform Why do we need Cloud?
  • 6. Google Cloud Platform > Why + too much data that your PC/servers couldn't store + too much computation your PC/servers couldn't deal with + your PC/servers are hard to scale > Why not + need a website + it sounds cool
  • 7. Google Cloud Platform Why should we use Google Cloud Platform?
  • 8. Google Cloud Platform > Access Control
 public, private networks
 block storage > Encryption
 all block storages will be encrypted on the cloud, no worries about leaks > Encapsulation
 all instances, virtual machines, networks or any resources will be encapsulated to prevent any other ones take over your precious stuffs Highly Secured Cloud by Google
  • 9. Google Cloud Platform > You will be using Google's Infrastructure
 Virtual Machines
 Networks
 Storage > And be placed in a safe place
 Google's Data Center > And Google will do those for you
 Scaling
 Migrating
 Maintenance
 Take over anything you don't wanna do
 Powered by Google
  • 10. Google Cloud Platform > The best way how Google share their + Cloud Infrastructure + Cloud Knowledge + Cloud Engineers > Your own data center, with minimum cost as possible as it could be So What is Google Cloud Platform
  • 11. Google Cloud Platform Google Cloud Family Computing Compute Engine App Engine Storage Cloud SQL Datastore Cloud Storage App Services Cloud Endpoints Big Query
  • 12. Google Cloud Platform > Manage all API services on Google Cloud 
 (e.g. Translation API, Prediction API, Maps API...) > Compose equivalent commands for:
 Command-line tools (Google Cloud SDK)
 RESTful API > Dashboard for monitoring all resources on Google Cloud Platform Cloud Developer Console
  • 13. Google Cloud Platform > Install/uninstall/upgrade all command-line tools related to Google Cloud Platform > Notification for new release of any Cloud SDK component > Automatization Google Cloud SDK
  • 14. Google Cloud Platform Storage Storage Services in Google Cloud Platform
  • 15. Google Cloud Platform > It's MySQL, but managed by Google > Relational Data Storage on Google Cloud > Use Cases + LAMP Applications + Google App Engine Cloud SQL
  • 16. Google Cloud Platform > Non-relational database (NoSQL) > Schema-less data > Use Cases + Highly scalable application Cloud Datastore
  • 17. Google Cloud Platform > Protected
 Your data is protected at multiple physical locations > Strong, configurable security
 OAuth or simple access control on your data > Multiple usages + Serve static objects directly + Use with other Google Cloud products (Bridge) Cloud Storage
  • 18. Google Cloud Platform App Services Power Up Your Applications in Google Cloud Platform
  • 19. Google Cloud Platform > Data Analysis Tool + BigQuery + Google Prediction API > Cloud Endpoints > Google Cloud DNS App Services in Google Cloud Platform
  • 20. Google Cloud Platform > Analyze terabytes of data, just a click of a button > Super-fast, SQL-like queries > Convenient import/export mechanism Big Query RUN QUERY
  • 21. Google Cloud Platform > Previewing of data > Statistics of tables > History/Cached Result > Save query result as another BigQuery table BigQuery Browser Tool
  • 22. Google Cloud Platform Popular Languages on Github ! SELECT repository.language, COUNT(repository.language) as num FROM [publicdata:samples.github_nested] GROUP BY repository.language ORDER BY num DESC LIMIT 10 BIGQUERY 1.6s elapsed, 12.8 MB processed
  • 23. Google Cloud Platform > Command-line Tool
 a full-featured command-line tool is included in Google Cloud SDK, called bq > RESTful API
 a set of APIs is ready for helping you to control all components and data on your BigQuery > BigQuery Connector for Excel
 Microsoft Excel? No problem, we have an extension for your excel to query over your excel data > Third-party Tools > Make your own More Ways To Use BigQuery
  • 24. Google Cloud Platform > generate APIs and client libraries from an App Engine application > make it easier to share web backend for mobile applications Cloud Endpoints
  • 25. Google Cloud Platform Cloud Endpoints Architecture iOS
 Objective-C Client Library Android
 Java Client Library Web Browser
 JavaScript Client Library Google Cloud Endpoints Google App Engine
 API Backend Instances
  • 26. Google Cloud Platform > Website
 solid integration, define APIs in Google App Engine application and generate JavaScript client library with Endpoints, no more handmade AJAX > API Server
 define APIs with Endpoints API, then it will be a RESTful API service immediately > Mobile Applications
 Backend-as-a-Service
 define reusable APIs with GAE various services, then generate client libraries for iOS, Android and web browser to share the resources you have Use Cases
  • 27. Google Cloud Platform > Machine Learning + Categorical + Regression > Pattern-matching > Simple API Interface Prediction API
  • 28. Google Cloud Platform > Recommendation System
 Predict what will be liked by your users > Filtering spams
 Categorizes messages as spam or non-spam > Semantic Analysis
 Know how your users feel, given your comments What can you do with Prediction API
  • 29. Google Cloud Platform > Language Identifier > Tag Categorizer > Sentiment Predictor Prediction Model Gallery
  • 31. Google Cloud Platform Google App Engine Platform-as-a-Service in Google Cloud Platform
  • 32. Google Cloud Platform How did you build a full-functional web service? a scalable, high-performance, fault-tolerant service
  • 33. Google Cloud Platform > LAMP + Linux + Apache + MySQL + Programming Languages > Failed: not scalable Traditional Way: LAMP Apache MySQL
  • 34. Google Cloud Platform > Power up Apache2 army! > Failed: database is alone, too busy You Need Load Balancing Apache MySQL Apache Apache
  • 35. Google Cloud Platform > Replication (Master/Slave) > Failed: Master may die Now Scale Database Apache MySQL Apache Apache MySQL Master
 Read/Write Slave
 Read Replication
  • 36. Google Cloud Platform Life is good, don't waste it
  • 37. Google Cloud Platform > You should care + Application code + Automated Scaling > You should not care + Server management (networking, cores, memory, disks...) + Bootstrapping + Deployment Platform-as-a-Service
  • 38. Google Cloud Platform > Application code gets executed (Runtime) > Static Content gets served (CDN) > Data gets stored (Database) > Server gets secured (Sandbox) > Service gets scaled (and automatically) How PaaS Work
  • 39. Google Cloud Platform Application
 Code Front End Load Balancer Routing Security DNS Setting Storage SQL/NoSQL Memcache Static Content Block Storage Service Support Mail Authentication Socket Auto Scaling Cron Job Queue Your Responsibility Google's Responsibility
  • 40. Google Cloud Platform > Sandboxed containers with various runtimes > Easy to build
 All you need to do is preparing your application code > Easy to run
 Deploy with a single command, and it works > Easy to scale
 scale on GAE is automated and easy to configure Google App Engine
  • 41. Google Cloud Platform > Java
 Java Servlets interface
 Support for standard interfaces to App Engine scalable services such as JDO, JPA, JavaMail and JCache > Python
 Python 2.7 and full support for any pure Python libraries, tools and frameworks
 Built-in Compiled C-extension libraries are good to go > PHP
 Currently in "Preview" stage
 But enough for your "Wordpress" > Go
 Currently in "Experimental" stage
 automated build service included, no need to rebuild when code changed
 and interface similar to the standard Go http package
 Languages and Runtimes
  • 42. Google Cloud Platform Workflow of Google App Engine Create a GAE Project Programming Testing Production
  • 43. Google Cloud Platform > Datastore
 schema-less, scalable object data storage
 rich data modeling API
 SQL-like query language, GQL (Google Query Language) > Cloud Storage
 strong, flexible, distributed storage service for serving or storing static files > Search
 Google-like search on structured data, such as full text, numbers, dates and geographic locations > Memcache
 a distributed, in-memory data cache to greatly improve your applications > Logs
 programmatic access to logging system
 a full functional control panel in Cloud Console, better than a gzip file > Migration/Backup Tools Data on Google App Engine
  • 44. Google Cloud Platform > Channel
 Create a persistent connection between your application and Google servers
 Send messages to JavaScript clients in real-time > Mail
 send email messages on behalf of admin or Google account users
 receive mails at various custom email addresses > URL Fetch
 Efficiently issue HTTP or HTTPS requests on your web application > Outbound Socket
 Socket support without requiring any special App Engine libs or any special App Engine ( import socket in Python) > XMPP
 Enable you application to send and receive chat messages to/from any XMPP-compatible messaging service (e.g. Facebook Chat, previous Google talks...) Communication
  • 45. Google Cloud Platform > Task Queue
 allow your application to asynchronize user requests, and organize them to be executed later > Scheduled Task (Cron Job)
 configure regular tasks at scheduled times or regular intervals Process Management
  • 46. Google Cloud Platform > Modules
 Create instances for exempting from request deadlines and request more memory and CPI resources for computing > MapReduce
 optimized adaptation of the MapReduce computing model for efficient distributing computation on large data sets > Images API
 Manipulate, combine and enhance images
 Convert images between formats
 Query metadata of images (height/width, colors) Computation
  • 47. Google Cloud Platform Related Projects & Libraries Extend Your App Engine to Work on Large-scale Computation
  • 48. Google Cloud Platform > Connects together complex, time-consuming workflows > Asynchronize tasks > Built-in pipelines or implement your own pipelines Pipeline
  • 49. Google Cloud Platform Create a Pipeline from pipeline import common ! class CountReport(pipeline.Pipeline): ! def run(self, email_address, entity_kind, property_name, *value_list): split_counts = yield SplitCount(entity_kind, property_name, *value_list) # pipeline to gain count result yield common.Log.info('SplitCount result = %s', split_counts) ! with pipeline.After(split_counts): with pipeline.InOrder(): yield common.Delay(seconds=1) yield common.Log.info('Done waiting') yield EmailCountReport(email_address, split_counts) # another sending mail pipeline PYTHON
  • 51. Google Cloud Platform > Programming model for processing large data sets in a parallel and distributed algorithms on a cluster > differ from map/reduce, one of functional programming conception, but has the same idea, "divide and conquer" > Proposed by Google > Hadoop-free MapReduce Library https://developers.google.com/appengine/docs/python/dataprocessing/mapreduce_library
  • 52. Google Cloud Platform > map()/reduce() in Python > map(func(elem), list) -> list > reduce(func(elem1, elem2), list) -> elem MapReduce in Functional Programming >>> map(lambda x: x*2, [1,2,3,4]) [2,4,6,8] ! >>> reduce(lambda x,y: x+y, [1,2,3,4]) 10 ! PYTHON
  • 53. Google Cloud Platform > Map > Shuffle > Reduce MapReduce: Stages
  • 54. Google Cloud Platform Configure a MapReduce Pipeline class WordCountPipeline(base_handler.PipelineBase): ! def run(self, filekey, blobkey): output = yield mapreduce_pipeline.MapreducePipeline( "word_count", # name of mapreduce job "main.word_count_map", # mapper function "main.word_count_reduce", # reducer function "mapreduce.input_readers.BlobstoreZipInputReader", # input reader "mapreduce.output_writers.FileOutputWriter", # output writer mapper_params={ # parameters to supply to the input reader "input_reader": { "blob_key": blobkey, }, }, reducer_params={ # parameters to supply to the output writer "output_writer": { "mime_type": "text/plain", "output_sharding": "input", "filesystem": "blobstore", }, }, shards=16) # number of shards yield StoreOutput("WordCount", filekey, output) PYTHON
  • 56. Google Cloud Platform Google Compute Engine Infrastructure-as-a-Service in Google Cloud Platform
  • 57. Google Cloud Platform > Google has resources + CPU Cores + Memory + Networking + Persistency (Disks, Snapshot, Cloud Storage...) + Well-trained engineering monkeys > You have business and be busy Infrastucture-as-a-Service
  • 58. Google Cloud Platform > High-performance virtual machines
 from micro-VM to large instance > Powered by Google's global network
 you could build a large cluster with strong and consistent bandwidth, provided by Google > Load Balancing
 spread incoming traffic across instances > Fast Bullet Reloading
 quick deployment of large VMs
 command-line interface
 web-based console > Highly secured
 All data written to disk in Compute Engine will be encrypted by high-class encryption algorithm Google Compute Engine
  • 59. Google Cloud Platform > KVM-based Virtual machines > Fast booting time
 routinely takes less than 30 secs > Various OS support > Various machine types Instances on GCE http://gce-demos.appspot.com
  • 61. Google Cloud Platform Operating Systems Premier Only
  • 62. Google Cloud Platform > a unit of CPU capacity used to describe the compute power of instance types > 2.75 GCEUs = 1 minimum power of 1 logical core on Sandy Bridge platform Google Compute Engine Units (GCEUs) =
  • 63. Google Cloud Platform Machine Types (Shared-Core) f1-micro Shared Core 0.6 GB Memory g1-small 1 Core 1.7 GB Memory 1.38 GCEUs
  • 64. Google Cloud Platform Machine Types (Standard) n1-standard-n Starts from 1 Core Start from 3.75 GB Memory n Virtual CPUs Memory GCEUs 1 1 3.75 GB 2.75 2 2 7.50 GB 5.50 4 4 15 GB 11 8 8 30 GB 30 16 16 60 GB 60
  • 65. Google Cloud Platform Machine Types (High Memory) n1-highmem-n Starts from 2 Core Start from 13 GB Memory n Virtual CPUs Memory GCEUs 2 2 13 GB 5.50 4 4 26 GB 11 8 8 52 GB 22 16 16 104 GB 44
  • 66. Google Cloud Platform Machine Types (High CPU) n1-highcpu-n Starts from 2 Core Start from 1.8 GB Memory n Virtual CPUs Memory GCEUs 2 2 1.8 GB 5.50 4 4 3.6 GB 11 8 8 7.2 GB 22 16 16 14.4 GB 44
  • 67. Google Cloud Platform Regions & Zones us-central1-a
 us-central1-b europe-west1-a
 europe-west1-b Singapore? Taiwan?
  • 68. Google Cloud Platform > Transparent Maintenance > Auto restart instances shutdown by system events > During transparent maintenance, you could set GCE to handle your instance in two ways: + Live migrate
 affect performance in some degree
 but remain your instances online (no downtime) + Terminate and reboot Live Migration
  • 69. Google Cloud Platform > Virtual SCSI device > Block Storage > Persistent until deleted > Hot-plug to GCE instances (attach/deattach) Persistent Disk
  • 70. Google Cloud Platform > Primary Disk: OS boot volume Persistent Disk Mode GCE Virtual Machine Root Stateful Root Volume
  • 71. Google Cloud Platform > Additional Disk: Read/Write Mode for user managed data volume Persistent Disk Mode GCE Virtual Machine Root Stateful Root Volume RW Data Stateful Data Volume
  • 72. Google Cloud Platform > Distribution Disk: Instant distribution of static content Persistent Disk Mode GCE Virtual Machine RO Data Read-Only Data Volume GCE Virtual MachineGCE Virtual Machine
  • 73. Google Cloud Platform > Target Pools > Health Checking > Forwarding Rules
 iptables for target pools Load Balancing
  • 74. Google Cloud Platform > CGE reserved IP for instance, won't change with the reboot of VMs > You can promote ephemeral IP to persistent IP > no DNS changing anymore Persistent IP Addresses
  • 75. Google Cloud Platform > Networking is first-class object on GCE
 which means you could apply/unapply it anytime easily > pre-defined networks before the first instance started Integrated Networking
  • 76. Google Cloud Platform > Those resources are global resources + Images (OS Images) + Snapshots + Network + Firewalls + Routes > And they're also first-class object in GCE Multi-Region Resources
  • 77. Google Cloud Platform > Scalr > Right Scale Services Host GCE
  • 78. Google Cloud Platform BigData Lab One of the finalists in Google Cloud Developer Challenge 2013
  • 79. Google Cloud Platform > http://www.google.com/events/gcdc2013/ > developers in 6 regions envolved > goals + effective use of Google App Engine + originality of concept + integration and creative use of Google Products Google Cloud Developer Challenge
  • 80. Google Cloud Platform > Provide a simple web interface to perform 4 big data operations: + Storing (Data Source) + MapReduce + Prediction (Machine Learning) + Visualization BigData Lab
  • 81. Google Cloud Platform > Google App Engine & Google Compute Engine > Cloud Endpoints > Google Cloud Storage > MapReduce Module for Google App Engine > Pipeline Module for Google App Engine > Prediction API > BigQuery What Are We Using?
  • 83. Google Cloud Platform EOF 
 Thanks For Listening
 +GDGTaipei