aws for the retail industry, webinar, september 2012

AWS for the Retail Industry

Ryan Shuttleworth – Technical Evangelist @ryanAWS

Adam Bidwell – eCommerce Manager, Kurt Geiger

Agenda

Amazon Web Services Background

Utility computing & Elasticity

AWS & Retail

Security & compliance

Highly available customer facing systems

Core platforms

Customer analytics

Kurt Geiger – Customer Story

Your feedback is important

Tell us:

What’s good, what’s not

What you want to see at these events

What you want AWS to deliver for

you

background

Consumer Business

Tens of millions of active customer

accounts

Eight countries: US, UK, Germany,

Japan, France, Canada, China, Italy

Seller Business

Sell on Amazon websites

Use Amazon technology for your own retail website

Leverage Amazon’s massive fulfillment

center network

IT Infrastructure Business

Cloud computing infrastructure for hosting web-scale

solutions

Hundreds of thousands of

registered customers in over 190 countries

Deep experience in building

and operating global web

scale systems

About Amazon Web Services

?

…get into cloud computing?

How did Amazon…

Over 10 years in the making

Enablement of sellers on Amazon

Internal need for scalable deployment environment

Early forays proved developers were hungry for more

AWS Mission

Enable businesses and developers to use web services* to build scalable,

sophisticated applications.

*What people now call “the cloud”

Each day AWS adds the equivalent server capacity to power Amazon when it was a global, $2.76B

enterprise

(circa 2000)

0.000

250.000

500.000

750.000

1000.000

1 Trillion

750k+ peak transactions per second

Objects in S3

Utility computing

Utility computing

On demand Pay as you go

Uniform Available


Uniform Available

Utility computing

Utility computing

Compute

Storage

Security Scaling

Database

Networking Monitoring

Messaging

Workflow

DNS

Load Balancing

Backup CDN


Uniform Available

Utility computing

On a global footprint

Region

US-WEST (N. California) EU-WEST (Ireland)

ASIA PAC (Tokyo)

ASIA PAC (Singapore)

US-WEST (Oregon)

SOUTH AMERICA (Sao Paulo)

US-EAST (Virginia)

GOV CLOUD

Availability Zone


Edge Locations

Dallas(2)

St.Louis

Miami

Jacksonville Los Angeles (2)

Palo Alto

Seattle

Ashburn(2)

Newark

New York (2)

Dublin

London(2)

Amsterdam

Stockholm

Frankfurt(2)

Paris(2)

Singapore(2)

Hong Kong

Tokyo

Sao Paulo

South Bend

San Jose

Osaka Milan

Sydney


Elasticity

Traditional IT

capacity

Elastic capacity

Capacity

Time Your IT needs

On and Off Fast Growth

Variable peaks Predictable peaks

Elastic capacity

On and Off Fast Growth

Predictable peaks Variable peaks

WASTE

CUSTOMER DISSATISFACTION

Elastic capacity

Elastic cloud capacity

Traditional

IT capacity

Your IT needs

Time

Capacity

Elastic capacity

Fast Growth On and Off

Predictable peaks Variable peaks

Elastic capacity

503 Service Temporarily Unavailable

The server is temporarily unable to service

your request due to maintenance downtime or

capacity problems. Please try again later.

From one instance…

…to thousands

And back again…

Num

ber

of E

C2 I

nsta

nces

4/12/2008 4/14/2008 4/15/2008 4/16/2008 4/18/2008 4/19/2008 4/20/2008 4/17/2008 4/13/2008

40 servers to 5000 in 3 days

EC2 scaled to peak of 5000 instances

“Techcrunched”

Launch of Facebook modification

Steady state of ~40 instances

Security you can rely upon

Foundation Services

Compute Storage Database Networking

AWS Global Infrastructure Regions

Availability Zones

Edge Locations Am

azo

n

Shared responsibility

Foundation Services



Availability Zones

Edge Locations Am

azo

n


Sarbanes-Oxley (SOX)

ISO 27001 Certification

Payment Card Industry Data Security

Standard (PCI DSS) Level 1 Compliant

SAS70(SOC 1) Type II Audit

FISMA A&As Multiple NIST Low Approvals to Operate (ATO) NIST Moderate, GSA issued ATO FedRAMP

DIACAP MAC III Sensitive IATO Customers have deployed various compliant applications such as HIPAA (healthcare)

Foundation Services



Availability Zones

Edge Locations

Client-side Data Encryption & Data Integrity Authentication

Server-side Encryption (File System and/or Data)

Network Traffic Protection (Encryption/Integrity/Identity)

Platform, Applications, Identity & Access Management

Operating System, Network & Firewall Configuration

Customer Data

Am

azo

n

You


AWS and Retail

Customer facing infrastructure

1

DNS Application Data

Rule 1: Service all web requests

a) Make sure requests get to your ‘front door’

DNS Application Data Request




…then this is irrelevant

Clients can’t resolve you?




“100% Available”

SLA


Route53

Feature Details

Global Supported from AWS global edge locations for fast and reliable domain name resolution

Scalable Automatically scales based upon query volumes

Latency based routing Supports resolution of endpoints based upon latency, enabling multi-region application delivery

Integrated Integrates with other AWS services allowing Route 53 to front load balancers, S3 and EC2

Secure Integrates with IAM giving fine grained control over DNS record access

http://aws.amazon.com/route53/sla




a) Make sure requests get to your ‘front door’ b) Make sure you open the door when they arrive

Route53

Region



Elastic Load

Balancer Region

Availability Zone

Availability Zone

Availability Zone

Availability Zone

Route53

a) Make sure requests get to your ‘front door’ b) Make sure you open the door when they arrive

Elastic load balancing Multi-availability zone Multi-region

Region



Region

a) Make sure requests get to your ‘front door’ b) Make sure you open the door when they arrive c) Have the data to form a response

Elastic Load

Balancer Region

Availability Zone

Availability Zone

Availability Zone

Availability Zone

Route53

Region



Region

Elastic Load

Balancer

Route53

Region

Availability Zone

Availability Zone

Availability Zone

Availability Zone

a) Make sure requests get to your ‘front door’ b) Make sure you open the door when they arrive c) Have the data to form a response

Multi-AZ RDS

(Master-slave)

Inter-region replication

Read-replicas

Rule 2: Service requests as fast as possible


a) Choose the fastest route

Region A

Route53

Region B

Request



Region A

Route53

Region B

16ms 92ms

Request


Region A

Route53

Region B

16ms

Request

Region A DNS entry



a) Choose the fastest route b) Offload your application servers

London

Paris

NY

Served from S3

/images/*

3

Served from EC2

*.php

2

Single CNAME

www.mysite.com

1

CloudFront World-wide content distribution network

Easily distribute content to end users with low

latency, high data transfer speeds, and no

commitments.

Without CloudFront

EC2 webservers/app servers loaded by user

requests



With CloudFront

Load of user requests pushed into

CloudFront, EC2 cluster can scale

down

Offload Scale Down




Res

po

nse

Tim

e

Serv

er L

oad

Res

po

nse

Tim

e

Serv

er

Load

Res

po

nse

Tim

e

Serv

er

Load

No CDN CDN for

Static

Content

CDN for

Static &

Dynamic

Content

Offload Scale Down


Rule 3: Handle requests at any scale

a) Scale up

Vertical Scaling

From $0.02/hr

Basic unit of compute capacity

Range of CPU, memory & local disk options

14 Instance types available, from micro through cluster

compute to SSD backed

Scale up with Elastic Compute Cloud (EC2)


a) Scale up b) Scale out

Trigger

auto-scaling

policy

as-create-auto-scaling-group MyGroup

--launch-configuration MyConfig

--availability-zones eu-west-1a

--min-size 4

--max-size 200

Auto-scaling Automatic re-sizing of compute clusters based upon demand

Manually

Send an API call or use CLI to launch/terminate instances – Only need

to specify capacity change (+/-)

By Schedule

Scale up/down based on date and time


By Policy

Scale in response to changing conditions, based on user configured real-time

monitoring and alerts

Auto-Rebalance

Instances are automatically launched/terminated to ensure the

application is balanced across multiple Azs


Manually

Send an API call or use CLI to launch/terminate instances – Only need

to specify capacity change (+/-)

By Schedule

Scale up/down based on date and time Preemptive manual scaling of capacity

e.g. before a marketing event add 10 more instances

Regular scaling up and down of instances

e.g. scale from 0 to 2 to process SQS messages every night or double capacity

on a Friday night


By Policy

Scale in response to changing conditions, based on user configured real-time

monitoring and alerts

Auto-Rebalance

Instances are automatically launched/terminated to ensure the

application is balanced across multiple Azs


Dynamic scale based upon custom metrics

e.g. SQS queue depth, Average CPU load, ELB latency

Maintain capacity across availability zones

e.g. Instance availability maintained in event of AZ becoming unavailable


a) Scale up b) Scale out c) Dial it up

Elastic Block Store Provisioned IOPS up to 1000 per EBS

volume

Predictable performance for

demanding workloads such as

databases

DynamoDB Provisioned read/write performance per

table

Predictable high performance scaled via

console or API

Relational Database Service Database-as-a-Service

No need to install or manage database instances

Scalable and fault tolerant configurations

DynamoDB Provisioned throughput NoSQL database

Fast, predictable performance

Fully distributed, fault tolerant architecture

Use RDS for databases

Use DynamoDB for high performance key-

value DB

Rule 4: Simplify architecture with services

Amazon SQS

Processing

task/processing

trigger

Processing results

Amazon SQS Reliable, highly scalable, queue service

for storing messages as they travel

between instances

Task A

Task B

(Auto-scaling)

Task C

2

3

1

Simple Workflow Reliably coordinate processing steps

across applications

Integrate AWS and non-AWS resources

Manage distributed state in complex

systems

Push inter-process workflows into the cloud with SWF

Reliable message queuing without

additional software


Cloud Search Elastic search engine based upon

Amazon A9 search engine

Fully managed service with

sophisticated feature set

Scales automatically

Document Server

Results

Search Server

Don’t install search software, use CloudSearch

Process large volumes of data cost effectively

with EMR

Elastic MapReduce Elastic Hadoop cluster

Integrates with S3 & DynamoDB

Leverage Hive & Pig analytics scripts

Integrates with instance types such as

spot


“Amazon CloudSearch is a game-changing product that has allowed us to deliver powerful

new search capabilities. Our customers can now find what they are looking for faster and more

easily than ever before…

….We saved many months of re-architecture and development time by going with Amazon

CloudSearch”

Don MacAskill CEO & Chief Geek

SmugMug

10 Million records 44 GB collection more than 2,000 operations per second Order volumes increase substantially during the holidays necessitating elasticity

Core platforms

2

Certification of SAP BusinessObjects business intelligence solutions and SAP Rapid Deployment Solutions (RDS) on

Linux & Windows Server 2008 R2

Certification of SAP Business All-in-One on Linux & Windows Server 2008 R2

Certified database engines for production SAP deployments: MaxDB, DB2, MS SQL Server 2008 R2

Non production systems

(dev, test, staging)

Backup, archive and recovery

(databases, AMIs)

http://aws.amazon.com/sap/

Production systems

(Analytics, branch etc)

Relational Database Service Database-as-a-Service

No need to install or manage database instances

Scalable and fault tolerant configurations

Feature Details

Platform support Create MySQL, SQL Server and Oracle RDBMS

Preconfigured Get started instantly with sensible default settings

Automated patching Keep your database platform up to date automatically

Backups Automatic backups and point in time recovery and full DB backups

Backups Volumes can be snapshotted for point in time restore

Failover Automated failover to slave hosts in event of a failure

Replication Easily create read-replicas of your data and seamlessly replicate data across availability zones

Disaster recovery in AWS

Pilot light architecture

Build resources around

replicated dataset

Keep ‘pilot light’ on by replicating core

databases

Build AWS resources around dataset and

leave in stopped state



replicated dataset


databases



Scale resources in AWS in

response to a DR event

Start up pool of resources in AWS when

events dictate

Match current production capacity through

auto-scaling polcies




replicated dataset


databases



Scale resources in AWS in

response to a DR event

Start up pool of resources in AWS when

events dictate

Match current production capacity through

auto-scaling policies

Switch-over to system in AWS


Customer analytics

3

We can collect more

Big Data

There is more

Big Data

And data has gravity…

Big Data

Data App App

http://blog.mccrory.me/2010/12/07/data-gravity-in-the-clouds/

Data has gravity

Compute Storage Big Data

Data


…and inertia at volume…


Data


…easier to move applications to the data


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Very large dataset seeks strong &

consistent compute for

short term relationship,

possibly longer. GSOH a

plus aws.amazon.com

Personal

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Bring compute capacity to the data


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Cloud has the power to process

From one instance…


…to thousands


and back again…


The revolution

have data

can store

have data

can store can analyse

have data

economically

Who is your customer really?

What do people really like?

What is happening socially with your products?

How do people really use your products?

Lesson 1: don’t leave your Amazon account logged in at home

Lesson 2: use the data you have to

drive proactive processes

1 instance for 100 hours =

100 instances for 1 hour

Small instance = $8

Amazon Elastic MapReduce

Elastic MapReduce Managed, elastic Hadoop cluster

Integrates with S3 & DynamoDB

Leverage Hive & Pig analytics scripts

Integrates with instance types such as spot

Feature Details

Scalable Use as many or as few compute instances running Hadoop as you want. Modify the number of instances while your job flow is running

Integrated with other services Works seamlessly with S3 as origin and output. Integrates with DynamoDB

Comprehensive Supports languages such as Hive and Pig for defining analytics, and allows complex definitions in Cascading, Java, Ruby, Perl, Python, PHP, R, or C++

Cost effective Works with Spot instance types

Monitoring Monitor job flows from with the management console

But what is it?

A framework Splits data into pieces Lets processing occur

Gathers the results

Elastic MapReduce

Code Name node

Output S3 + SimpleDB

S3 + DynamoDB

Elastic cluster

HDFS Queries

+ BI Via JDBC, Pig, Hive

Input data

Very large click log (e.g TBs)


Lots of actions by John Smith



Split the log into

many small pieces



Split the log into

many small pieces

Process in an EMR cluster



Split the log into

many small pieces


Aggregate the results

from all the nodes


What John Smith

did


Split the log into

many small pieces


Aggregate the results

from all the nodes

What John Smith

did

Very large click log (e.g TBs) Insight in a fraction of the time

1 instance for 100 hours =

100 instances for 1 hour

Small instance = $8

1 instance for 1,000 hours =

1,000 instances for 1 hour

Small instance = $80

Features powered by Amazon Elastic MapReduce:

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200 Elastic MapReduce jobs per day Processing 3TB of data

“With AWS, our developers can now do things they couldn’t before…

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challenges.”

Dave Marin Search and data-mining engineer

Elastic MapReduce Web log analysis and recommendation algorithms

Adam Bidwell eCommerce Manager

Overview of Kurt Geiger

Kurt Geiger are responsible for the operation of three retail websites: • Kurtgeiger.com • Shoeaholics.com • Ninewest.co.uk In total serving upwards of a half-million page views a day.

Our interest in Amazon, is to host:

• Frontend systems - three Magento installations which the stores are built on.

• Administration systems – backend tasks, such

as product enrichment and reporting. • Testing – load-testing systems, and other

‘sandpit’ tasks • Research/Development – one-off installations for

investigation purposes.

Challenges faced by Kurt Geiger:

• Rapidly changing business needs – fast pace

makes it difficult to predict long-term requirements

• Marketing activity – drives large traffic spikes

Why Amazon?

• Unique model – we’ve used several cloud providers

Amazon offer a wide range of network/server infrastructure and services.

• Self-service – 24/7 help yourself approach, suits us to take what we need when we need it

Future

• Larger capacity architectures

• More API based “pop-up” systems on demand

• Reserved instances - further cost savings

Benefits

• Hourly billing – the cost adapts with our current set

up, no tie-in

• Large capacity – Whether capacity will be there is not a consideration, it just is

• Trusted provider – architecture still requires planning for good reliability, but AWS has robust infrastructure to build on

aws.amazon.com/free

aws for the retail industry, webinar, september 2012

Technology

web requestsa

make sure requests

data encryption data

elastic capacity traditional

capacity problems

elastic capacity waste

available customer

equivalent server capacity