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AWS Webcast - Power your Digital Marketing Strategy with Amazon Web Services


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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.

Published in: Technology

AWS Webcast - Power your Digital Marketing Strategy with Amazon Web Services

  1. 1. Power your Digital Marketing Strategy with AWS Ben Butler, Sr. Mgr,. Big Data, AWS @bensbutler Dec 11, 2013
  2. 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. 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. 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. 5. AWS Global Infrastructure 9 Regions 25 Availability Zones 42+ Edge Locations Continuous Expansion
  6. 6. Solving Problems for Organizations Around the World
  7. 7. AWS Service Overview Deployment & Administration Application Services Compute Storage Networking AWS Global Infrastructure Database
  8. 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. 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. 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. 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. 12. Digital Advertising Companies using AWS
  13. 13. Amazon DynamoDB
  14. 14. NoSQL Database Predictable performance Amazon DynamoDB Seamless & massive scalability Fully managed; zero admin
  15. 15. Amazon’s Path to DynamoDB DynamoDB RDBMS
  16. 16. Amazon DynamoDB DEVS OPS USERS
  17. 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. 18. Amazon DynamoDB DEVS OPS USERS Admin-Free (at any scale)
  19. 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. 20. Amazon DynamoDB DEVS OPS USERS Durable Low Latency
  21. 21. WRITES Replicated continuously to 3 AZ’s Persisted to disk (custom SSD) READS Strongly or eventually consistent No latency trade-off
  22. 22. Amazon Redshift
  23. 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. 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. 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. 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. 27. Amazon Redshift parallelizes and distributes everything • • • • Query Load Backup/Restore Resize
  28. 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. 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. 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. 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. 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. 33. Amazon Redshift is easy to use • Provision in minutes • Monitor query performance • Point and click resize • Built in security • Automatic backups
  34. 34. Ad Serving
  35. 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. 36. Ad Servers Profiles Database EC2 DynamoDB Real Time Bidding
  37. 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. 38. Ad Servers Profiles Database EC2 DynamoDB ad request ad url visitor
  39. 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. 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. 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. 42. Analysis
  43. 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. 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. 45. Architecture Templates for Common Patterns
  47. 47. Lamborghini uses AWS for Dynamic Webapps Reduced time to market to near Zero Reduced infrastructure costs by 50%
  48. 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. 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. 50. Thank you! Ben Butler, Sr. Mgr,. Big Data, AWS @bensbutler Dec 11, 2013