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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
Proxy Love
Myth: Slow Frameworks “ Rails, Django, Seaside, Scala…” cant scale.
The Proxy Solution
The “More” Proxy Solution
Transparent, Cut-Through Proxy Transparent
Transparent Proxy = Scalability Power Tool 90% use case
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?
Staging fail. Profile of queries has changed Fail Load on production has changed Fail Parallel environment Fail Slower release cycle Fail
Replay  log data,  rinse, repeat github.com/igrigorik/autoperf
Benchmarking Proxy flash of the obvious Real (production) traffic Duplex Ruby Proxy, FTW!
Transparent Duplex Proxy, FTW
Same response, different turnaround time Different response body!
github.com/igrigorik/em-proxy Duplex Ruby Proxy, FTW!
EM-Proxy Workflow 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
Duplex incoming data
Forward Production Response Analyze Results
Open connection to application server
Buffer until connected
Pass response to Duplex Notify when done
Analyze Time, Response…
Analyze Time, Response… Response Time
Cute, right? but so what…
%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
Beanstalkd  Math ~ 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!
Extending Beanstalkd 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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Ruby Proxies for Scale, Performance, and Monitoring - GoGaRuCo - igvita.com

Editor's Notes

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