AWS Customer Presentation - Share This


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AWS Customer Presentation - Share This

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