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Introduction to Amazon Web Services and cloud computing and how it supports the Digital Marketing industry. AdRoll CEO, Aaron Bell, describes their success story on AWS using DynamoDB for retargeting. In today's world, consumer habits change fast and marketing decisions need to be made within seconds, not days. Delivering engaging advertising experiences requires real time, high performing architectures that provide digital advertisers the ability to measure and improve the performance of their campaigns and tie them more closely to corporate goals. The insights gleaned from the massive amounts of data collected can then be used to dynamically adjust media spend and creative execution for optimal performance. The AWS Cloud enables you to deliver marketing content and advertisements with the levels of availability, performance, and personalization that your customers expect. Plus, AWS lowers your costs. Join us to learn about how big data and low latency / high performing architectures are changing the game for digital advertising.
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October 3, 2013
The Future of Digital Advertising with Cloud Computing
Ben Butler, Sr. Mgr,. Big Data, AWS
Why Companies Use AWS
• Business o Fast time to market
o Iterate features faster because you’re not building/managing undifferentiated
“plumbing”. Very important in the rapidly changing digital advertising ecosystem.
• Operational o Add new datacenters in minutes or hours (e.g. burst or geographic expansion)
o Locality: Many companies in the Real Time Bidding ecosystem are on AWS
• Financial o Pay only for what you use, when you use it
o Avoid large Capex expense for geographic or local expansion
Use Cases on AWS
Ad Serving
Infrastructure
Ad Servers
Exchanges, DSPs, SSPs
Data Management Platforms
Interactive Campaigns
and Microsites
Product web sites
Social networking campaigns
Games and contests
High Performance
Computing & Big Data
Ad analytics
Ad server log processing
Business Intelligence
AWS Global Infrastructure
9 Regions
25 Availability Zones
42+ Edge Locations
Continuous Expansion
Solving Problems for Organizations Around the World
Gartner Magic Quadrant for Cloud IaaS
Gartner “Magic Quadrant for Cloud Infrastructure as a Service,” Lydia Leong,
Douglas Toombs, Bob Gill, Gregor Petri, Tiny Haynes, August 19, 2013. This Magic
Quadrant graphic was published by Gartner, Inc. as part of a larger research note
and should be evaluated in the context of the entire report.. The Gartner report is
available upon request from Steven Armstrong ([email protected]). Gartner
does not endorse any vendor, product or service depicted in its research
publications, and does not advise technology users to select only those vendors
with the highest ratings. Gartner research publications consist of the opinions of
Gartner's research organization and should not be construed as statements of fact.
Gartner disclaims all warranties, expressed or implied, with respect to this research,
including any warranties of merchantability or fitness for a particular purpose.
AWS Service Overview
AWS Global Infrastructure
Application Services
Networking
Deployment & Administration
Database Storage Compute
Compute Services
Amazon EC2 Auto Scaling Elastic Load
Balancing
Actual
EC2
Elastic Virtual servers
in the cloud
Dynamic traffic
distribution
Automated scaling
of EC2 capacity
Big Data Services
Amazon EMR
(Elastic Map Reduce)
Amazon Redshift AWS Data Pipeline
Hosted Hadoop
framework
Petabyte-scale data
warehouse service Move data among AWS
services and on-
premises data sources
Database and Application Services
Amazon CloudFront
CDN
Amazon RDS Amazon Dynamo
DB
distribute content
globally, fast
Managed relational
database service Managed NoSQL
database service
DBA
Amazon
CloudSearch
Managed search
engine service
Storage Services
Amazon EBS
EBS
Block storage for use
with Amazon EC2
Amazon S3
Images
Videos
Files
Binaries
Snapshots
Internet scale
storage via API
AWS Storage Gateway
S3,
Glacier
Integrates on-premises
IT and AWS storage
Amazon Glacier
Images
Videos
Files
Binaries
Snapshots
Storage for archiving
and backup
Digital Advertising Companies using AWS
Kantar Media Uses AWS to Scale Quickly
Need to scale to
45M+ beacon calls per day
EDGE SERVERS RUNNING ON EC2
INGEST THE DATA, USE SQS TO LET
WORKERS KNOW THAT DATA IS
AVAILABLE
WORKERS PRE-PROCESS THE DATA
AND PUT IT INTO S3
EMR THEN PROCESSES THAT DATA,
OUTPUTTING REPORTS AND RESULTS
INTO ANOTHER S3 BUCKET
Amazon Elastic Compute
Cloud (EC2)
Elastic
Load
Balancer
Edge
Servers Workers
Logs Reports
HDFS
Cluster
Amazon Elastic
MapReduce
Amazon Simple Queue
Service (SQS)
Amazon Simple Storage
Service (S3)
Razorfish Uses AWS for Big Data Processing
Processing time reduced to
8 hours from 2+ days
S3 Hadoop Cluster
100 machine cluster created on demand
3.5 billion records per day
71 million unique cookies
per day
1.7 Million targeted ads per
day
Increased client Return On
Ad Spend by 500%
Lamborghini uses AWS for Dynamic Webapps
Reduced
infrastructure
costs by 50%
Reduced time to
market to near Zero
Samsung Improved their Product Experience with AWS
Saved $34 Million 85% savings versus
traditional hosting
Affine uses AWS for Contextual Targeting
OUR CUSTOMERS BID ON VIDEO AD INVENTORY IN REAL TIME AND OUR SYSTEM MUST EVALUATE THE CONTENT THEY'RE SPONSORING AND RESPOND WITH A DECISION IN LESS THAN 50MS. ROUTE 53’S LATENCY BASED ROUTING LETS US EASILY RUN MULTIPLE STACKS OF OUR WHOLE TARGETING PLATFORM IN EACH AWS REGION SO WE CAN MEET OUR CUSTOMERS LATENCY NEEDS.
-- Jonathan Dodson VP Engineering
Respond in
less than 50ms
Delivers certainty to
Advertisers and Agencies
Architecture Templates for Common Patterns
aws.amazon.com/architecture
On-premise On-instance Object level Long term
Locally
accessible
file systems
Workloads
with local
data
Use case journey
On-premise On-instance Object level Long term
Locally
accessible
file systems
Workloads
with local
data
Use case journey
AWS
On-premise On-instance Object level Long term
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Data
distribution
Durable
media
storage
System
images
Database
backups
Data
archives
Use case journey
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
Getting
data into
the
cloud
AWS Direct Connect Dedicated bandwidth between you
site and AWS
Amazon Storage Gateway Shrink-wrapped gateway for volume
synchronization
AWS Import/Export Physical transfer of media into and
out of AWS
Direct connect, import/export and storage gateway
Getting data into the cloud
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
Getting
data into
the
cloud
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2 Getting
data into
the
cloud
Disks
and data
Elastic Block Store, S3 and Glacier
Fundamental Storage Options
Simple Storage Service Highly scalable object storage
1 byte to 5TB in size
99.999999999% durability
Elastic Block Store High performance block storage device
1GB to 1TB in size
Mount as drives to instances with
snapshot/cloning functionalities
Glacier Long term object archive
Extremely low cost per gigabyte
99.999999999% durability
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2 Getting
data into
the
cloud
Disks
and data
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2
3
Getting
data into
the
cloud
Disks
and data
Database
as a
service
Relational Database
Service Fully managed database
(MySQL, Oracle, MSSQL)
DynamoDB NoSQL, Schemaless,
Provisioned throughput
database
Redshift Data Warehouse
As a Service
RDS, Redshift, DynamoDB
Database services
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2
3
Getting
data into
the
cloud
Disks
and data
Database
as a
service
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2
3
4 Getting
data into
the
cloud
Disks
and data
Database
as a
service
Object
serving
and
storage
Elastic Block Store, S3 and Glacier
Fundamental Storage Options
Simple Storage Service Highly scalable object storage
1 byte to 5TB in size
99.999999999% durability
Elastic Block Store High performance block storage device
1GB to 1TB in size
Mount as drives to instances with
snapshot/cloning functionalities
Glacier Long term object archive
Extremely low cost per gigabyte
99.999999999% durability
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2
3
4 Getting
data into
the
cloud
Disks
and data
Database
as a
service
Object
serving
and
storage
On-premise
High IO
performance
High network
performance
On-instance Object level Long term
High IO
performance
Provisioned IOPS
Backup & Restore
Locally
accessible
file systems
Workloads
with local
data
EC2 based
applications
DR
deployments
Good
performance
High durability
Scalability
Data
distribution
Durable
media
storage
Very low price
High durability
Slow access
System
images
Database
backups
Data
archives
Use case journey
1
2
3
4 5 Getting
data into
the
cloud
Disks
and data
Database
as a
service
Object
serving
and
storage
Cold
storage &
archiving
Elastic Block Store, S3 and Glacier
Fundamental Storage Options
Simple Storage Service Highly scalable object storage
1 byte to 5TB in size
99.999999999% durability
Elastic Block Store High performance block storage device
1GB to 1TB in size
Mount as drives to instances with
snapshot/cloning functionalities
Glacier Long term object archive
Extremely low cost per gigabyte
99.999999999% durability
October 3, 2013
The Future of Digital Advertising with Cloud Computing
Ben Butler, Sr. Mgr,. Big Data, AWS | @bensbutler
AWS From Ad Bust
To Ad Boom October 3, 2013
Advertising budgets cut in the recession
Top 5 benefits to a nimble, scrappy ad
tech startup finding their way
1. No upfront infrastructural costs
2. Leverage services so we can focus on core
value prop with small core team (no ops!)
S3
ELB
Cloudfront
3. Instantly global
4. Rapidly test/benchmark new tech
5. Experiment quickly to find product/market
fit
Pixel
Ad Exchange
RTB
Auction
Ad
server
Bidder
Cookie Store
Data Warehouse
Predictive
Algorithms
They said it couldn’t be done…
2013: Day In The Life
► 10,000 customers in 100 countries
► Bidding on 10B+ events each day; avg. response time < 50ms
► 10TB processed in real-time each day
► Cutting edge tech: Kafka, Storm, HBase
► Running 200 -> 700 servers at any one time
► Running in 6 AWS data centers, soon to be 8 (Brazil & Tokyo)
► 99.99% ad server uptime (next slide)
Top 5 benefits to an established ad tech
company
1. (Auto-)provision servers to meet peak
demand
2. Instantly provision 100s or 1000s of
servers. (Eg, for attribution modeling.)
3. Lower TCO
4. Plug into awesome services (that would be
hard to built in-house)
5. Rapidly experiment and validate new
algorithms and product extensions
“Want to increase innovation? Lower
the cost of failure” - Joi Ito, Dir MIT Media Lab
Labs
