In today's world, consumer habits change fast and marketing decisions need to be made within -seconds, not days. Delivering engaging marketing experiences requires real-time, high performing architectures that provide marketers the ability to measure and improve the performance of their campaigns and tie them more closely to corporate goals. The AWS Cloud enables you to deliver marketing content and campaigns with the levels of availability, performance, and personalization that your customers expect while lowering your costs. Please join us for this webinar, where AWS will showcase the benefits and business case for running digital marketing solutions on the AWS Cloud. We will also highlight several customer success stories and how to engage with AWS or an AWS partner on next steps.

1. Power your Digital Marketing
Strategy with AWS
Ben Butler, Sr. Mgr,. Big Data, AWS
@bensbutler
Dec 11, 2013

2. Digital Marketing on AWS
Overview of AWS and Digital Marketing workloads
Amazon DynamoDB
Amazon Redshift
Ad Serving and Real Time Bidding
• Use cases
• Architectures
Digital Marketing Customer Success Stories

3. Why Companies Use AWS
•
•
•
Business
o Faster 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

4. What Digital Marketing Companies Use AWS for
Ad Serving
Infrastructure
Ad Servers
Exchanges, DSPs, SSPs
Data Management Platforms
Interactive Campaigns
and Microsites
Product websites
Social networking campaigns
Games and contests
High Performance
Computing & Big Data
Ad analytics
Ad server log processing
Business Intelligence

5. AWS Global Infrastructure
9 Regions
25 Availability Zones
42+ Edge Locations
Continuous Expansion

6. Solving Problems for Organizations Around the World

7. AWS Service Overview
Deployment & Administration
Application Services
Compute
Storage
Networking
AWS Global Infrastructure
Database

8. Compute Services
Amazon EC2
Auto Scaling
Elastic Load
Balancing
Elastic Virtual servers
in the cloud
Automated scaling
of EC2 capacity
Dynamic traffic
distribution
EC2
Actual

9. 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 onpremises data sources

10. Database and Application Services
Amazon RDS
Amazon
DynamoDB
Amazon CloudFront
CDN
Amazon
CloudSearch
Managed relational
database service
Managed NoSQL
database service
distribute content
globally, fast
Managed search
engine service
DBA

11. Storage Services
Amazon EBS
Amazon S3
Amazon Glacier
AWS Storage Gateway
Block storage for use
with Amazon EC2
Internet scale
storage via API
Storage for archiving
and backup
Integrates on-premises
IT and AWS storage
S3,
Glacier
EBS
Images
Videos
Files
Binaries
Snapshots
Images
Videos
Files
Binaries
Snapshots

12. Digital Advertising Companies using AWS

13. Amazon
DynamoDB

14. NoSQL Database
Predictable performance
Amazon
DynamoDB
Seamless & massive scalability
Fully managed; zero admin

15. Amazon’s Path to DynamoDB
DynamoDB
RDBMS

16. Amazon
DynamoDB
DEVS
OPS
USERS

17. Amazon
DynamoDB
DEVS
OPS
USERS
Fast Application
Development
Time to Build
New Applications
•
•
•
•
Flexible data models
Simple API
High-scale queries
Laptop development

18. Amazon
DynamoDB
DEVS
OPS
USERS
Admin-Free
(at any scale)

19. Provisioned Throughput
request-based capacity provisioning model
Throughput is declared and updated via the API or the console
CreateTable (foo, reads/sec = 100, writes/sec = 150)
UpdateTable (foo, reads/sec=10000, writes/sec=4500)
DynamoDB handles the rest
Capacity is reserved and available when needed
Scaling-up triggers repartitioning and reallocation
No impact to performance or availability

20. Amazon
DynamoDB
DEVS
OPS
USERS
Durable
Low Latency

21. WRITES
Replicated continuously to 3 AZ’s
Persisted to disk (custom SSD)
READS
Strongly or eventually consistent
No latency trade-off

22. Amazon
Redshift

23. Data Warehousing the AWS way
Deploy
Easy to provision
Pay as you go, no up front costs
Fast, cheap, easy to use
SQL

24. Digital marketing and advertising use cases
•
Customer acquisition
–
–
Ad spend
Traffic sources
JDBC/ODBC
DynamoDB
•
Customer behavior
–
–
–
•
Clickstream
Referrals, sharing
Actions taken
Lifetime value
–
–
Conversions
Churn rate
Amazon
Redshift
Amazon S3
Amazon RDS
Amazon EMR

25. Amazon Redshift architecture
•
–
–
–
•
SQL endpoint
Stores metadata
Coordinates query execution
10 GigE
(HPC)
Compute Nodes
–
–
–
–
•
JDBC/ODBC
Leader Node
Local, columnar storage
Execute queries in parallel
Load, backup, restore via Amazon S3
Parallel load from Amazon DynamoDB
Single node version available
Ingestion
Backup
Restore

26. Amazon Redshift runs on optimized hardware
HS1.8XL: 128 GB RAM, 16 Cores, 24 Spindles, 16 TB compressed user storage, 2 GB/sec scan rate
HS1.XL: 16 GB RAM, 2 Cores, 3 Spindles, 2 TB compressed customer storage
•
Optimized for I/O intensive workloads
•
High disk density
•
Runs in HPC - fast network
•
HS1.8XL available on Amazon EC2

27. Amazon Redshift parallelizes and distributes everything
•
•
•
•
Query
Load
Backup/Restore
Resize

28. Amazon Redshift parallelizes and distributes everything
•
•
•
•
Query
Load
Backup/Restore
Resize
•
Load in parallel from Amazon S3 or
Amazon DynamoDB
•
Columnar storage, automatic
compression
•
Data automatically distributed and
sorted according to DDL
•
Scales linearly with number of nodes

29. Amazon Redshift parallelizes and distributes everything
•
•
•
•
Query
Load
Backup/Restore
Resize
•
Backups to Amazon S3 are
automatic, continuous and
incremental
•
Configurable system snapshot
retention period
•
Take user snapshots on-demand
•
Streaming restores enable you to
resume querying faster

30. Amazon Redshift parallelizes and distributes everything
•
•
•
•
Query
Load
Backup/Restore
Resize
•
Resize while remaining online
•
Provision a new cluster in the
background
•
Copy data in parallel from
node to node
•
Only charged for source cluster

31. Amazon Redshift parallelizes and distributes everything
•
•
•
•
Query
Load
Backup/Restore
Resize
•
Automatic SQL endpoint
switchover via DNS
•
Decommission the source cluster
•
Simple operation via AWS Console
or API

32. Amazon Redshift lets you start small and grow big
Extra Large Node (HS1.XL)
3 spindles, 2 TB, 16 GB RAM, 2 cores
Single Node (2 TB)
Cluster 2-32 Nodes (4 TB – 64 TB)
Note: Nodes not to scale
Eight Extra Large Node (HS1.8XL)
24 spindles, 16 TB, 128 GB RAM, 16 cores, 10 GigE
Cluster 2-100 Nodes (32 TB – 1.6 PB)

33. Amazon Redshift is easy to use
• Provision in minutes
• Monitor query performance
• Point and click resize
• Built in security
• Automatic backups

34. Ad Serving

35. Ad Servers
Profiles Database
EC2
DynamoDB
ad request
ad url
visitor
1.
2.
3.
4.
Visitor loads a web page
Web page issues a request to ad servers on EC2
Query to DynamoDB returns the ad to display
Link is returned to visitor

36. Ad Servers
Profiles Database
EC2
DynamoDB
Real Time Bidding

37. Ad Servers
Profiles Database
EC2
DynamoDB
20 ms
Request network transit
bid request
bid response
Queues
and
Buffer
Ads
…
DynamoDB
Bidder
RTB
platform
Response network transit
20 ms
Profiles
Contingency
time buffer
Decision on best ad and bid price based on
optimization that needs multiple data look-ups
20 ms
40 ms

38. Ad Servers
Profiles Database
EC2
DynamoDB
ad request
ad url
visitor

39. Ad Servers
Profiles Database
ad request
ad url
Elastic Load
Balancing
EC2 (MAZ)
DynamoDB
Optimize for scale, elasticity, and availability
•
Multi-AZ: maintain EC2 capacity in multiple availability
zones
•
Auto Scaling: scale EC2 capacity to automatically
manage variations in workload
•
Elastic Load Balancing: automatically distribute
incoming traffic across multiple EC2 instances
visitor

40. Profiles Database
Ad Servers
ad request
ad url
Elastic Load
Balancing
EC2 (MAZ)
DynamoDB
Static Repository Files
advertisement
visitor
impression logs
CloudFront
Amazon S3
1. Ad files are downloaded from CloudFront
2. Impressions captured into logs on S3

41. Profiles Database
Ad Servers
ad request
ad url
Elastic Load
Balancing
EC2 (MAZ)
DynamoDB
Static Repository Files
advertisement
impression logs
visitor
click through
requests
CloudFront
Elastic Load
Balancing
Amazon S3
Click-through
Servers
click through
log files
EC2
(MAZ)
Click-through requests
are captured via EC2
into log files and
persisted on S3

42. Analysis

43. Profiles Database
Ad Servers
ad request
updated
profiles
ad url
Elastic Load
Balancing
EC2 (MAZ)
new
requests
DynamoDB
new
bids
Static Repository Files
Redshift
advertisement
impression logs
visitor
CloudFront
ETL
Amazon S3
unstructured
log files
click through
requests
Elastic Load
Balancing
Click-through
Servers
click through
log files
EC2
(MAZ)
Amazon EMR

44. Business Analytics using Redshift
Cost Optimization
Optimize return on
advertising expenditure
Bid Optimization
Drive qualified users to
advertiser’s sites
• Ad server logs
• 3rd party data
• Bid history
• User history
• Impressions
• 3rd party data
Amazon Redshift
• User history
• Enrichment

45. Architecture Templates for Common Patterns
aws.amazon.com/architecture

46. 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

47. Lamborghini uses AWS for Dynamic Webapps
Reduced time to
market to near Zero
Reduced
infrastructure
costs by 50%

48. Razorfish Uses AWS for Big Data Processing
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
S3
Processing time reduced to
8 hours from 2+ days
Hadoop Cluster
Increased client Return On
Ad Spend by 500%

49. Kantar Media Uses AWS to Scale Quickly
Amazon Simple Queue
Service (SQS)
EDGE
SERVERS RUNNING ON
INGEST THE DATA, USE
Amazon Simple Storage
Service (S3)
EC2
SQS TO LET
Logs
WORKERS KNOW THAT DATA IS
Reports
AVAILABLE
WORKERS
PRE-PROCESS THE DATA
AND PUT IT INTO
S3
EMR THEN PROCESSES
THAT DATA,
OUTPUTTING REPORTS AND RESULTS
INTO ANOTHER
Elastic
Load
Balancer
Edge
Servers
Workers
HDFS
Cluster
S3 BUCKET
Amazon Elastic Compute
Cloud (EC2)
Need to scale to
45M+ beacon calls per day
Amazon Elastic
MapReduce

50. Thank you!
Ben Butler, Sr. Mgr,. Big Data, AWS
@bensbutler
aws.amazon.com/digital-marketing
aws.amazon.com/big-data
Dec 11, 2013