Ruby Proxies for Scale, Performance, and Monitoring - GoGaRuCo - igvita.com

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A high-performance proxy server is less than a hundred lines of Ruby code and it is an indispensable tool for anyone who knows how to use it. In this session we will first walk through the basics of event-driven architectures and high-performance network programming in Ruby using the EventMachine framework.

Technologie

Ruby Proxies for Scale, Performance and Monitoring Ilya Grigorik CTO / AideRSS Event-Driven Architectures @igrigorik #meshu #eda http://bit.ly/eda

postrank.com/topic/ruby The slides… Twitter My blog

[object Object],“ Rails, Django, Seaside, Scala…” cant scale.

Proxies for Monitoring, Performance and Scale welcome to the wonderful world of intercepting, caching, … , proxy servers

Problem: Staging Environment Production Simulated User

“ Representative Load / Staging” Duplication Simulating traffic?

Replay log data, rinse, repeat github.com/igrigorik/autoperf

[object Object],[object Object],Real (production) traffic Duplex Ruby Proxy, FTW!

Same response, different turnaround time Different response body!

[object Object],1. Accept connection - Connect & Forward to Production - Connect & Forward to Staging 2. Stream response to client from Production - Buffer response from Staging 3. Run “Processor / Analyzer” once both return

Ruby EventMachine crash course EM::Connection #receive_data - new data ready for processing #unbind - connection terminated #connection_completed - connected

Forward Production Response Analyze Results

Pass response to Duplex Notify when done

%w[ <Transparent> Intercepting Caching … ] solution for every problem

Validating Proxy easy, real-time diagnostics Woops!

Who said you’re not allowed to touch the data? Intercepting Proxy for those hard-to-reach spots

SMTP / Mail: inject SPAM detection De(encrypt): stream data MySQL: inject sharding logic Intercepting Proxy for those hard-to-reach spots

@PostRank: Beanstalkd + Ruby Proxy because RAM is still expensive

[object Object],~ 93 Bytes of overhead per job ~300 Bytes of data / job x 80,000,000 jobs in memory ~ 30 GB of RAM = 2 X-Large EC2 instances Oi, expensive!

[object Object],Observations: 1. Each job is rescheduled several times 2. > 95% are scheduled for > 3 hours into the future 3. Beanstalkd does not have overflow page-to-disk Memory is wasted… We’ll add it ourselves!

@PostRank: “Chronos Scheduler” 1 “Medium” EC2 Instance Intercepting Proxy

Extend the protocol Chronos Scheduler Beanstalkd persistence Process incoming data Buffer “SCHEDULE” requests, otherwise forward

Archive to MySQL Chronos Scheduler Beanstalkd persistence Buffer “SCHEDULE”

@PostRank: “Chronos Scheduler” Extend the protocol ARCHIVE RESERVE, … 10 line patch to client: queue.archive(job)

@PostRank: “Chronos Scheduler” ~79,000,000 jobs, 4GB RAM ARCHIVE RESERVE, … Upcoming jobs: ~ 1M 400% cheaper + extensible! 1 Proxy, 1 Beanstalkd, 1 MySQL = 200 req/s

%w[ Transparent <Intercepting> Auth Cache … ] easy to make & a powerful hammer

Cheers. Questions? The slides… Twitter My blog

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Writing highly scalable WebSocket using the Atmosphere Framework and Scalajfarcand

Websockets on the JVM: Atmosphere to the rescue!jfarcand

The HTML5 WebSocket APIDavid Lindkvist

Asynchronous Web Programming with HTML5 WebSockets and JavaJames Falkner

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Reverse ajax in 2014Nenad Pecanac

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Introduction to performance tuning perl web applicationsPerrin Harkins

Building Real-Time Applications with Android and WebSocketsSergi Almar i Graupera

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WebSockets wiith Scala and Play! FrameworkFabio Tiriticco

Going Live! with CometSimon Willison

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The Atmosphere Framework

GWT Web Socket and data serialization

WebSockets with Spring 4

Concurrent Ruby Application Servers

Communication in Python and the C10k problem

Writing highly scalable WebSocket using the Atmosphere Framework and Scala

Websockets on the JVM: Atmosphere to the rescue!

The HTML5 WebSocket API

Asynchronous Web Programming with HTML5 WebSockets and Java

Web sockets in Java

Reverse ajax in 2014

Writing Portable WebSockets in Java

Realtime web application with java

Introduction to WAMP, a protocol enabling PUB/SUB and RPC over Websocket

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Ruby Proxies for Scale, Performance, and Monitoring - GoGaRuCo - igvita.com

1. Ruby Proxies for Scale, Performance and Monitoring Ilya Grigorik CTO / AideRSS Event-Driven Architectures @igrigorik #meshu #eda http://bit.ly/eda

2. postrank.com/topic/ruby The slides… Twitter My blog

9. Proxies for Monitoring, Performance and Scale welcome to the wonderful world of intercepting, caching, … , proxy servers

10. Problem: Staging Environment Production Simulated User

11. “ Representative Load / Staging” Duplication Simulating traffic?

12. Staging fail. Profile of queries has changed Fail Load on production has changed Fail Parallel environment Fail Slower release cycle Fail

13. Replay log data, rinse, repeat github.com/igrigorik/autoperf

14.

15. Transparent Duplex Proxy, FTW

16. Same response, different turnaround time Different response body!

17.

18.

19. Ruby EventMachine crash course EM::Connection #receive_data - new data ready for processing #unbind - connection terminated #connection_completed - connected

20. Duplex incoming data

21. Forward Production Response Analyze Results

22. Open connection to application server

23. Buffer until connected

24. Pass response to Duplex Notify when done

25. Analyze Time, Response…

26. Analyze Time, Response… Response Time

27. Cute, right? but so what…

28. %w[ <Transparent> Intercepting Caching … ] solution for every problem

29. Validating Proxy easy, real-time diagnostics Woops!

30. Who said you’re not allowed to touch the data? Intercepting Proxy for those hard-to-reach spots

31. SMTP / Mail: inject SPAM detection De(encrypt): stream data MySQL: inject sharding logic Intercepting Proxy for those hard-to-reach spots

32. @PostRank: Beanstalkd + Ruby Proxy because RAM is still expensive

33.

34.

35. @PostRank: “Chronos Scheduler” 1 “Medium” EC2 Instance Intercepting Proxy

36. Extend the protocol Chronos Scheduler Beanstalkd persistence Process incoming data Buffer “SCHEDULE” requests, otherwise forward

37. Archive to MySQL Chronos Scheduler Beanstalkd persistence Buffer “SCHEDULE”

38. @PostRank: “Chronos Scheduler” Extend the protocol ARCHIVE RESERVE, … 10 line patch to client: queue.archive(job)

39. @PostRank: “Chronos Scheduler” ~79,000,000 jobs, 4GB RAM ARCHIVE RESERVE, … Upcoming jobs: ~ 1M 400% cheaper + extensible! 1 Proxy, 1 Beanstalkd, 1 MySQL = 200 req/s

40. %w[ Transparent <Intercepting> Auth Cache … ] easy to make & a powerful hammer

41. Cheers. Questions? The slides… Twitter My blog

Notes de l'éditeur

Wonderful, wonderful world in the context of building and using Ruby proxy servers for scale, performance and monitoring.