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GlassFish Story by Makito Hashiyama/Rakuten

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GlassFish story presented by Makito Hashiyama/Rakuten at JavaOne 2013 Sunday GlassFish Community Event.

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GlassFish Story by Makito Hashiyama/Rakuten

  1. 1. GlassFish Community Feedback GlassFish usage in Rakuten Inc.
  2. 2. About me  Name: Makito Hashiyama(@capyogu)  Age: 29  Role: Team manager / In charge of APIs for Rakuten Ichiba  Like: GlassFish, Tomcat, KVS(memcached, Coherence), GAE, Android…  E-mail: makito.hashiyama@mail.rakuten.com, hashiyaman@gmail.com
  3. 3. What is Rakuten?  E-commerce and Internet company based in Tokyo, Japan  B2B2C e-commerce platform Head Office E-Commerce eBook Travel Other services & businesses Rakuten Institute of Technology Development center Head Office / Regional Headquarters
  4. 4. How We Are Using GlassFish  Usage  One of core API service for Rakuten Ichiba  Require high availability External APIs  Environment  Use on production environment  GlassFish version 3.1.2.2 SOAP/ REST Client side Our API GlassFish Clusters Oracle Coherence
  5. 5. Benefits gleaned from Glassfish  Reference implementation of Java EE  Only GlassFish supported JAX-WS as standard in 2007  It was an advantage to evaluate new features earlier  Easy to manage with low cost  We need to manage huge cluster without stopping  Cost saving(Weblogic -> GlassFish)
  6. 6. What Worked with GlassFish  Community support(create patches)  https://java.net/jira/browse/GLASSFISH-5200 (If use jvmRoute JSESSIONID cookie is not secure even in HTTPS)  https://java.net/jira/browse/GRIZZLY-1333 (NetworkAddressValidator will fail when passed property substitution values) We have contributed patched to GlassFish community.
  7. 7. Improvement to handle a huge traffic  Rakuten Super Sale  Biggest online sales in Japan  A lot of doorbuster deals(It causes a huge amount of traffic)  Performance bottleneck  External APIs called by our API were slow down  We needed to improve the system at the peek time Client side delay Slow down Our API External APIs
  8. 8. Improvement to handle a huge traffic Worker Thread Worker Thread Request Client side Task Queue Worker Thread Worker Thread Worker Thread GlassFish CPU load was high delay delay delay delay delay External APIs
  9. 9. Improvement to handle a huge traffic Worker Thread Request Client side Task Queue Worker Thread External APIs Worker Thread GlassFish (1)According to vmstat, ‘run queue’ was very high (2)Decrease worker threads to keep ‘run queue’ low (3)As a result, latency increased but throughput was improved
  10. 10. Improvement to handle a huge traffic  As a result…  Our API could process over 12,000 transactions / minute  The result showed the high reliability and availability of GlassFish
  11. 11. Resolve issues & challenge to upper goal  Some issues  Instance down due to the full of task queue  Unknown exception on server.log org.glassfish.flashlight.impl.client.ReflectiveClientInvoker java.lang.reflect.InvocationTargetException CAUSE: java.lang.NullPointerException id=101 target=org.glassfish.web.admin.monitor.HttpServiceStatsProvider@193e1fc method=public void org.glassfish.web.admin.monitor.HttpServiceStatsProvider. connectionAcceptedEvent(java.lang.String,int,java.lang.String) paramNames=[listenerName, connection, address] probeIndices=[0, 1, 2] useProbeArgs=true hasComputedParams=false  Challenge to upper goal

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