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AWS Customer Presentation - Share This
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AWS Customer Presentation - Share This



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  • 1. ShareThis on AWS
    • Paco Nathan, Data Insights
    AWS Start-Up Tour 2009-06-16
  • 2. What Does ShareThis Do? AWS Start-Up Tour 2009-06-16
    • “ Make it simple to share any online content”
    • Social content sharing platform
    • ESPN, FOX, CS Monitor, HuffPost, CBS Marketwatch, Wired, TechCrunch, ThinkGeek, etc.
    • When a news story goes viral on a major publisher, our sharing services must scale-out to keep pace
  • 3. AWS Start-Up Tour 2009-06-16
  • 4. Why Our Company Uses AWS AWS Start-Up Tour 2009-06-16
    • >10^6 publishers, >10^9 users, >10^10 urls
    • Early stage start-up, < 25 people, “wearing lots of hats”, ultra fast-paced R&D
    • Spikes in popular stories impose demands throughout the architecture: API services, loggers, DW, BI, etc.
    • How can this level of service be built 100% in the cloud?
  • 5. AWS Start-Up Tour 2009-06-16
  • 6. System Architecture AWS Start-Up Tour 2009-06-16
    • Each service designed for cost-effective, horizontal scale-out
    • API served by cluster of LAMP stack + cluster of NginX
    • AsterData : nCluster infrastructure “hub-and-spoke” pattern
    • Cascading : abstraction layer for tying together components
    • Batch jobs on Elastic MapReduce , AsterData SQL/MR
    • SQS , EBS , SimpleDB , MTurk , plus other AWS services
  • 7. AWS Start-Up Tour 2009-06-16
  • 8. Key Learnings AWS Start-Up Tour 2009-06-16
    • Capability to scale-out horizontally without having to recode, rebuild, etc. — add new EC2 nodes to clusters
    • Authoritative data + backups in S3, great approach for DR
    • Wide range of use cases implemented: widget API, log clean-up, vertical search, business intelligence, etc.
    • Developers launch their own sandbox instances — makes dev/test/debug cycles more efficient
    • Staff enabled to “wear even more hats” with less risk
  • 9. Cascading + Elastic MapReduce AWS Start-Up Tour 2009-06-16
  • 10. Cascading + Elastic MapReduce AWS Start-Up Tour 2009-06-16
    • “ Syntax is for humans, APIs are for software”
    • Defines apps as set operations applied to data flows
    • Engineers & data scientists don’t think in terms of MapReduce primitives, key/value pairs, etc.
    • Integrates Hadoop API + other APIs (S3, SQS, JDBC)
    • Expresses end-points as Java design patterns, compiled code — not just a scramble of scripts
  • 11. Cascading + Elastic MapReduce AWS Start-Up Tour 2009-06-16
    • Highly scalable, fault-tolerate framework for batch jobs
    • Dramatically reduced need for Ops overhead
    • Excellent command line tools make the dev/test/debug cycle very efficient with “Big Data”
    • Highly expert staff, very responsive and helpful in forums
    • Cascading example code in developer resources: “LogAnalyzer for CloudFront” and “Multitool”
  • 12. Hadoop Book / Case Study AWS Start-Up Tour 2009-06-16 ShareThis case study, &quot;Cascading&quot; by Chris K Wensel, in…
  • 13. Contacts @pacoid on Twitter AWS Start-Up Tour 2009-06-16