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The Economies of Scaling Software - Josh Long and Abdelmonaim Remani

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JAX London presentation 2014

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The Economies of Scaling Software - Josh Long and Abdelmonaim Remani

  1. 1. SCALING WITH Josh Long (⻰龙之春) @starbuxman jlong@pivotal.io github.com/joshlong SPRING
  2. 2. Spring Developer Advocate @Starbuxman Josh Long (⻰龙之春) @starbuxman | jlong@pivotal.io Jean Claude van Damme! Java mascot Duke some thing’s I’ve authored...
  3. 3. @Starbuxman
  4. 4. BUILDING ADAPTIVE APPLICATIONS IS HARD built WHY on Cloud SCALE? Foundry code will be open sourced.
  5. 5. Moore’s Law no longer works @Starbuxman § processing can’t scale up § concurrent, horizontal architectures are easier to scale § “process”-style concurrency is easy to scale still Moore's law is the observation that, over the history of computing hardware, the number of transistors in a dense integrated circuit doubles approximately every two years. The law is named after Gordon E. Moore, co-founder of the Intel Corporation, who described the trend in his 1965 paper. http://en.wikipedia.org/wiki/Moore's_law
  6. 6. data @Starbuxman data production is expected to be : 44000% larger in 2020 than 2009
  7. 7. systems are increasingly complex @Starbuxman § a complex system today has a lot of moving parts § security § multiple clients (iOS, Android, Windows Mobile, etc.) § multiple (business) domains § integration between systems § requires more people working on the same problem
  8. 8. mobile More than 1.5 MILLION activations daily * @Starbuxman * http://www.androidcentral.com/larry-page-15-million-android-devices-activated-every-day
  9. 9. social: a connected world in 60 seconds @Starbuxman 1090 visitors 700k messages sent 2000 checkins 175k tweets 7610 searches 2MM videos viewed 3125 photos uploaded 7630 messages sent * source: visual.ly/60-seconds-social-media
  10. 10. the internet of things @Starbuxman “In five years, by 2018, Earth will be home to 7.6 billion people, says the United Nations. By contrast, some 25 billion devices will be connected by 2015, and 50 billion by 2020, says Cisco.” http://www.businessinsider.com/what-you-need-to-know-about-the-internet- of-things-2013-3?op=1#ixzz3FxCafwWe § IPv6 gives us more addresses § devices are getting smaller, more ubiquitous § “devices” include homes appliances (refrigerators, washers, coffee machines, dryers), roads, air pollution monitors, (human) body monitors, etc
  11. 11. how to think about scale? @Starbuxman Chris Richardson (http://microservices.io/articles/scalecube.html) introduced me to this “scale cube” from The Art of Scaling Software
  12. 12. BUILDING ADAPTIVE APPLICATIONS IS HARD X-AXIS HORIZONTAL DUPLICATION built on Cloud Foundry code will be open sourced.
  13. 13. STATELESS APPS SCALE
  14. 14. no state and lots of gain @Starbuxman § obvious: no state means no sharing § no sharing means that applications can be scaled horizontally easily § requires very little: § HTTP load balancers are ubiquitous. § message queues (like RabbitMQ) make effective load balancers
  15. 15. DEMO RABBITMQ PING PONG
  16. 16. WHAT IF I HAVE SOME STATE?
  17. 17. http sessions? @Starbuxman § Spring Session § useful in a PaaS § useful when you need state § useful when you need durable, replicated state § pluggable: Redis out-of-the-box, but feel free to bring your own
  18. 18. DEMO REDIS-BACKED HTTP SESSIONS
  19. 19. PAAS: PLATFORM-AS-A-SERVICE
  20. 20. why PaaS? @Starbuxman “ ” Imagine if architects had to be the janitor for every building they designed. This is how the development team felt prior to moving to Windows Azure. Duncan Mackenzie Nov 07, 2011 http://www.infoq.com/articles/Channel-9-Azure
  21. 21. The Impact of the Cloud @Starbuxman § Spring Boot makes it dead simple to stand up services. (Where do they live? Who runs them?) § Things get Distributed REALLY quickly! CF provides a way to simplify > cf push hystrix.jar > cf push … § Manifests are are the ultimate installer. (cf push an entire distributed system!) § Spring Cloud PaaS connectors simplify service-consumption
  22. 22. DEMO SIMPLE SCALING ON THE CLOUD
  23. 23. BUILDING ADAPTIVE APPLICATIONS IS HARD Z-AXIS DATA PARTITIONING built on Cloud Foundry code will be open sourced.
  24. 24. CAP & NOSQL
  25. 25. Brewer’s Conjecture (CAP) @Starbuxman Many datastores provide some of the following three characteristics: § Consistency § Availability § Partitionability clarification #1: in a system with no network partitions (such as a single-node RDBMS), then there's no need to sacrifice C & A. clarification #2: availability is a continuous value: 0-100%. there are many levels of consistency, and even partitions have nuances, including disagreement within the system about whether a partition exists.
  26. 26. choose the best store for the job @Starbuxman
  27. 27. NoSQL @Starbuxman
  28. 28. SPRING DATA REPOSITORIES
  29. 29. How it Works in Rails @Starbuxman class Car < ActiveRecord end # and then magic happens car = Car.new cars = car.find_cars_by_id(232) # where did this method come from?
  30. 30. Using Spring Data Repositories @Starbuxman •Spring Data Neo4J @EnableNeo4jRepositories •Spring Data JPA @EnableJpaRepositories •Spring Data MongoDB @EnableMongoRepositories •Spring Data GemFire @EnableGemfireRepositories @Configuration @EnableTransactionManagement @ComponentScan @EnableJpaRepositories( basePackageClasses = BlogRepository.class) public class ServiceConfiguration { @Bean public DataSource dataSource(){ .. } @Bean public PlatformTransactionManager transactionManager(){ .. } }
  31. 31. Custom Repository @Starbuxman Keyword Sample Resulting MongoDB Query * GreaterThan findByAgeGreaterThan(int age) {"age" : {"$gt" : age}} LessThan findByAgeLessThan(int age) {"age" : {"$lt" : age}} Between findByAgeBetween(int from, int to) {"age" : {"$gt" : from, "$lt" : NotNull findByFirstnameNotNull() t{o”fi}}rstname" : {"$ne" : null}} Null findByFirstnameNull() {”firstname" : null} Like findByFirstnameLike(String name) "firstname" : firstname} (regex)
  32. 32. MONGODB
  33. 33. Spring Data MongoDB @Starbuxman § GridFS integration § GIS integration § Document mapping
  34. 34. who’s using MongoDB? @Starbuxman § Mailbox.app: https://tech.dropbox.com/2013/09/scaling-mongodb-at-mailbox/ § eHarmony: https://www.mongodb.com/presentations/big-dating-eharmony-0? _ga=1.259505294.567221685.1413121358 § Expedia: https://www.mongodb.com/presentations/building-expedia %E2%80%99s-travel-graph-using-mongodb? _ga=1.26276665.567221685.1413121358
  35. 35. DEMO MONGODB GIS & FACEBOOK PLACES
  36. 36. REDIS
  37. 37. Spring Data Redis @Starbuxman § key/value store § data structures § sets § queues § lists § maps § CacheManager implementation § memcached client
  38. 38. who’s using Redis? @Starbuxman § Twitter: http://www.infoq.com/presentations/Real-Time-Delivery-Twitter § Sina Weibo http://www.xdata.me/?p=353 § GitHub https://github.com/blog/530-how-we-made-github-fast § Snapchat https://twitter.com/robustcloud/status/448503100056535040 § Pinterest http://engineering.pinterest.com/post/55272557617/building-a-follower-model- from-scratch
  39. 39. COUCHBASE
  40. 40. Spring Data Couchbase @Starbuxman § keyed document access § sort of like a mix of Redis and MongoDB § horizontally scalable @Configuration @EnableCouchbaseRepositories public class Application extends AbstractCouchbaseConfiguration { @Override protected List<String> bootstrapHosts() { return Arrays.asList( “127.0.0.1" ); } @Override protected String getBucketName() { return "default"; } @Override protected String getBucketPassword() { return ""; } }
  41. 41. who’s using Couchbase? @Starbuxman § AOL: http://www.couchbase.com/ad_platforms § Playtika: http://www.couchbase.com/social-gaming
  42. 42. NEO4J
  43. 43. complexity vs performance @Starbuxman
  44. 44. who’s using Neo4j? @Starbuxman
  45. 45. the evolution of search Pre-1999 WWW Indexing Atomic Data 1999 - 2012 Google Invents PageRank Simple Connected Data 2012-? Google Launches the Knowledge Graph Rich Connected Data @Starbuxman
  46. 46. Recommenda)ons @Starbuxman
  47. 47. Graph Search! @Starbuxman
  48. 48. What the Cypher Query Looks Like: @Starbuxman MATCH (person:Person)-[:IS_FRIEND_OF]->(friend), (friend)-[:LIKES]->(restaurant), (restaurant)-[:LOCATED_IN]->(loc:Location), (restaurant)-[:SERVES]->(type:Cuisine) WHERE person.name = 'Philip' AND loc.location='New York' AND type.cuisine='Sushi' RETURN restaurant.name * Cypher http://maxdemarzi.com/?s=facebook query language example
  49. 49. What the Search Looks Like: @Starbuxman
  50. 50. DEMO NEO4J TWITTER
  51. 51. HADOOP
  52. 52. spring for Surviving the Big Data Wild-West with Spring for Hadoop @Starbuxman
  53. 53. SPRING XD
  54. 54. @Starbuxman stream processing, data ingestion & integration But How Do You Process Data Realtime? @metamarkets founder Michael E. Driscoll:
  55. 55. stream processing, data ingestion & integration @Starbuxman Introducing Spring XD sources sinks
  56. 56. DEMO SPRING XD AND PIVOTAL HD
  57. 57. see spring xd + hawq video
  58. 58. BUILDING ADAPTIVE APPLICATIONS IS HARD Y-AXIS BOUNDED CONTEXTS built on Cloud Foundry code will be open sourced.
  59. 59. micro- vs. monolith… is not a new discussion @Starbuxman From: kt4@prism.gatech.EDU (Ken Thompson) Subject: Re: LINUX is obsolete Date: 3 Feb 92 23:07:54 GMT Organization: Georgia Institute of Technology I would generally agree that microkernels are probably the wave of the future. However, it is in my opinion easier to implement a monolithic kernel. It is also easier for it to turn into a mess in a hurry as it is modified. Regards, Ken
  60. 60. hold on a tick.. @Starbuxman …didn’t the monolith win?
  61. 61. so what’s so bad about a monolith? @Starbuxman (does your monolith drive you to drink?)
  62. 62. boardroom agility pushes tech agility @Starbuxman § boardroom agility manifest in technology: • 2-pizza box teams are a result of eschewing organizational norms § easier to scale (in development teams, and at runtime) § shorter iterations: • small services > continuous integration > shorter release cycles > deployment automation
  63. 63. the elegant microservice @Starbuxman
  64. 64. problems with microservices @Starbuxman § hard to deploy (devops!) § hard to tease into separate deployable modules (Boot!) § lots of moving parts introduces complexity (PaaS & Spring Cloud!)
  65. 65. WHY BOOT
  66. 66. harder to tease into separate microservices? …No. @Starbuxman import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.EnableAutoConfiguration; import org.springframework.context.annotation.Configuration; import org.springframework.web.bind.annotation.* // assumes org.springframework.boot:spring-boot-starter-web on CLASSPATH @Configuration @RestController @EnableAutoConfiguration public class GreetingsController { @RequestMapping("/hi/{name}") String hello(@PathVariable String name) { return "Hello, " + name + "!"; } public static void main(String[] args) { SpringApplication.run(GreetingsController.class, args); } }
  67. 67. managing many processes with a PaaS @Starbuxman § services are explicit about what they bundle § services are attached resources (locally or remote, who cares) § configuration is external § scaling is easy § isolation is provided at the process level
  68. 68. emergent patterns of microservices @Starbuxman § distributed / versioned configuration § service registration + discovery § client-side routing, service-to-service calls § load-balancing § minimizing failure cascades § proxies
  69. 69. Standing on the Shoulders of Spring & @Starbuxman
  70. 70. CONFIG-SERVER
  71. 71. REFRESH-ABLE CONFIGURATION
  72. 72. SERVICE REGISTRATION & DISCOVERY WITH EUREKA http://techblog.netflix.com/2012/09/eureka.html
  73. 73. MANAGING FAILURES WITH HYSTRIX http://techblog.netflix.com/2012/11/hystrix.html
  74. 74. DYNAMIC ROUTING WITH ZUUL http://techblog.netflix.com/2012/11/hystrix.html
  75. 75. Bookmark.. @Starbuxman § The Netflix Techblog http://techblog.netflix.com § Fred Georges on Programmer Anarchy http://www.infoq.com/news/2012/02/programmer-anarchy § Matt Stine’s CF + Microservices: a Mutualistic Symbiotic Relationship http://www.youtube.com/watch?v=RGZefc92tZs § Martin Fowler’s article - http://martinfowler.com/articles/microservices.html
  76. 76. Bookmark.. @Starbuxman § Former Netflix DevOps Guru Adrian Cockroft on DevOps + MS http://www.infoq.com/interviews/adrian-cockcroft-microservices-devops § Bootiful Applications with Spring Boot http://http://www.youtube.com/watch?v=eCos5VTtZoI § Chris Richardson’s http://microservices.io site and his Decomposing Applications for Scalability talks § github.com/joshlong/scaling-software-talk
  77. 77. References spring.io/guides github.com/spring-cloud/ github.com/spring-cloud-samples/ github.com/joshlong/spring-doge github.com/joshlong/spring-doge-microservice docs.spring.io/spring-boot/ Questions? Josh Long (⻰龙之春) @starbuxman jlong@pivotal.io github.com/joshlong

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