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Xen and the Art of
Rails Deployment
Who am I?

• Ezra Zygmuntowicz
• Rubyist for 4 years
• Engine Yard Founder and Architect
• Blog: http://brainspl.at
Deploying Rails

• Details have changed rapidly over the years
• Many different webservers have come and
  gone
• Basics remain the same
Full Stack Request/Response Life-Cycle


•   Request comes into gateway
    server


•   Rewrite rules are evaluated and
    request gets served directly if it’s
    a static asset


•   Dynamic requests are proxied to
    one Mongrel in the Mongrel
    Cluster


•   Mongrel dispatches request
    through Rails and returns
    response to client
History Lesson
 •   CGI

 •   Apache1.3.x/mod_fastcgi

 •   Lighttpd/fcgi

 •   Apache2.x/mod_fcgid

 •   Lighttpd/SCGI

 •   Lightspeed
Enough Already




X
  •   CGI

  •   Apache1.3.x/mod_fastcgi

  •   Lighttpd/fcgi

  •   Apache2.x/mod_fcgid

  •   Lighttpd/SCGI

  •   Lightspeed
Enter Mongrel

The year of the Dog
What is Mongrel?
Mongrel is an HTTP Server
 Library written by Zed Shaw

• Fast HTTP Parser written in Ragel + C
• Fast URI Classifier written in C
• Stackable Request Handlers
• Flexible Configuration
• Secure and RFC Compliant HTTP Parser
Ragel State Machine
Defined HTTP Parser
Why is Mongrel better?

• HTTP is a well known and well tooled
  protocol
• Mongrel is way easier to setup and use
• Transparent wire protocol
But Rails isn’t Thread Safe!

• Giant Mutex Lock around Rails Dispatch
• Only one request served at a time by one
  mongrel
• Use mongrel_cluster to scale with multiple
  processes
Rails Internal Request/Response Life-Cycle
•   Mongrel Locks Mutex

•   Rails Dispatcher is invoked with
    request/response objects

•   Routing is invoked and returns
    the proper Controller object or
    404 if no route found

•   Filter chain is invoked

•   Controller’s Action is called,
    manipulates Models

•   View is rendered and any after
    filters are called

•   Mongrel Unlocks Mutex

•   Final response or error page
    returned to client
New dog seeking old
          tricks
•   Wide array of options for HTTP tools to front mongrel
    clusters

•   Pen, Pound, Balance, Haproxy ( No static file serving, just
    proxies)

•   Lightspeed can serve static files and proxy to mongrel

•   Apache2.2.x/mod_proxy_balancer can do the same
On the prowl for the
       perfect stack
•   Pen(no ssl support, no connection rate limiting)

•   Pound(Falls down under high load, no connection rate limiting)

•   Haproxy(supports conn rate limits, very high perf, no static files
    so more moving parts in a full stack)

•   Lightspeed(free version is crippled)

•   Apache2.2.x(Does work but.. bloat, bloat, bloat...)
Nginx:
From Russia, with Love
•   Seriously bent on performance

•   Super small resource footprint

•   Stands up under the heaviest loads without leaking memory

•   Killer rewrite and proxy modules

•   Approachable author and growing community
Nginx + Mongrel
•   This is *the* stack to be on

•   Only keep apache around for mod_dav_svn

•   Flexible nginx.conf syntax allows for serving static files and
    rails caches and proxying dynamic requests to mongrel

•   Fast, fast, fast

•   Did I say it’s fast yet?
A few gotchas


•   Nginx buffers file uploads, so no mongrel_upload_progress. This
    will be addressed soon

•   No connection rate limiting for proxy module yet, this too shall
    pass
A bright future for nginx

•   mod_rewrite is going away

•   To be replaced with http_script_module

•   This will embed the NekoVM(http://nekovm.org/) directly in
    nginx so customizing behavior for rewriting and proxying will
    become infinitley flexible
Perfect Simple Stack

    •   Linux

    •   Nginx

    •   Mongrel(mongrel_cluster)

    •   Monit
Swiftiply:
Teaching the Dog new tricks
      http://swiftiply.swiftcore.org
Swiftiply: Evented Mongrel
 •   Hot patch to Mongrel

 •   Removes Ruby’s Thread’s and Socket handling from Mongrel
     Core

 •   Replace with EventMachine event loop

 •   Mongrel becomes Single threaded, event driven

 •   Noticable Speed and IO throughtput increase

 •   Stands up much better under higher concurrent load without
     starting to slow down or leak memory
But how does a single threaded
event driven mongrel outperform
    a multithreaded mongrel?
•   Ruby’s green threads have a lot of overhead in context switching
    and have to copy a lot of state context for each thread

•   Mutual exclusion locks are expensive

•   One process can only do so much IO

•   Event driven means running in a tight loop and firing callbacks in
    response to network ‘events’

•   Since there is no context switching between threads, a single
    process has less overhead to deal with which allows for higher
    throughput and faster networking IO
Mongrel VS Evented Mongrel
       in a Hello World dogfight
  Mongrel:
1 concurrent
    user


   Evented
  Mongrel:
1 concurrent
     user
Mongrel:
100 concurrent
     users




Evented Mongrel:
 100 concurrent
      users
Swiftiply Proxy

•   Event driven proxy, small memory footprint(7-10Mb)

•   Faster then Haproxy

•   Did I mention Fast?
How it differs from a
               normal proxy
Standard proxy must know about the        With swiftiply, the backends connect to the proxy. So
ports of all backends. Usually requires   all mongrels get started on the same port and then
    restart to add more backends            they open a persistent connection to the proxy
This means you can start and stop as many
        mongrels as you want and they get auto
               configured in the proxy!




This opens the door for scaling the number of mongrels
 automatically in response to increased load on the fly!
The Zen of Xen
Monolithic Linux VS
      Modularized Linux
•   Old way of thinking is dedicated boxes running all services in
    one big hodgepodge on one kernel

•   New school is sharply targeted virtualized linux with each VM
    running a single tier or service
We all strive for code
    modularization right?
•   Why not do the same thing with our servers?

•   Each VM runs one or two related services

•   Simplifies deployment and scaling

•   Even if you only have one box you absolutely should run
    Xen on it from the start
Old VS New
What happens when you need to
 scale to more then one box?
Old School
•   Get another box and move mysql on there

•   Get another box to run some of the other services

•   Lots of setup required, downtime to migrate

•   Complex Linux installs with many services running are harder
    to debug when performance problems happen

•   This *can* scale but is way less flexible
New School
•   Add another box with Xen installed

•   Pick a few services that need more resources and migrate
    them *live* to the other machine

•   Each VM runs one thing and runs it well

•   Easy to target performance problems

•   Scales much better
Advanced Clustering
•   Virtualized compute nodes that boot Xen dom0 off of USB
    thumb drives

•   SAN storage for all Xen domU(VPS’s)

•   Red Hat Clustering Suite for fencing and cluster quorems

•   GFS for 100% posix compliant clustered filesystem(no shitty
    NFS)

•   Hardware load balancers or dedicated boxes running Ultra
    Monkey or just straight LVS
Fabric of Compute and
        Storage
•   When a compute node fails just swap it out for a new one and
    plug in the thumbdrive and you’re back in business

•   Move hot VM’s to less loaded nodes easily as they are not tied
    to a single machine

•   Deploy your app code to one node and then bounce the
    mongrels on all nodes with a clustered filesystem like GFS

•   Fragment and page caching consistency across all nodes
    instantly

•   Scale from one or 2 VM’s to as many as traffic requires *and*
    back down again once traffic subsides.
RAM RAM RAM

•   Most Rails apps are RAM bound way before they are CPU
    bound

•   Average mongrel size on 64bit EngineYard is 70-120Mb *per*
    mongrel. Slightly less on 32 bit systems

•   Rmagick and :include the worst culprits

•   95% of Rails apps will leak memory at one point or another
Rails eats Database
resources for breakfast
•   Majority of app in the wild have *no* indexes in their
    databases

•   Learn when and where to apply indexes, it will save your
    ass

•   ActiveRecord insulates developers from SQL to the point
    of massive ineficiencies. Look at your logs and see what
    SQL is being generated. Do not fear the SQL and don’t
    think you can get away without some denormalization and
    custom SQL if you plan on your app having a chance of
    scaling
Other tips & tricks
•   *Don’t* use filesystem sessions, AR or SQLSession or
    memcached if you don’t need persistance

•   script/runner is massively ineficient. Try as hard as possible
    to not load all of rails in your background processes. Use
    the raw Mysql library and plain ruby if you can and your
    servers will thank you for it

•   *Do not* use script runner to process incoming email.
    Run a daemon in a loop and poll a mail server with net/
    pop2 or net/imap. Forking a whole rails process for each
    incoming email will never work in a production
    environment period
Rails is great for the
           80/20 rule
•   But you are on your own when you need the last 20%

•   Learn how to write custom mongrel handlers for perf critical
    sections of your app

•   When is optimization not premature?

•   Ruby is plenty fast, it’s rails that tends to be on the slow side

•   Cache, cache, cache. It doesnt get much faster then service
    cached static html files
Parting Thought

•   Don’t take what I or anyone else says about this stuff as
    gospel

•   Test it and benchmark it for yourself to be sure

•   Trust but verify and you will stay in good shape
Questions?

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  • 1. Xen and the Art of Rails Deployment
  • 2. Who am I? • Ezra Zygmuntowicz • Rubyist for 4 years • Engine Yard Founder and Architect • Blog: http://brainspl.at
  • 3. Deploying Rails • Details have changed rapidly over the years • Many different webservers have come and gone • Basics remain the same
  • 4. Full Stack Request/Response Life-Cycle • Request comes into gateway server • Rewrite rules are evaluated and request gets served directly if it’s a static asset • Dynamic requests are proxied to one Mongrel in the Mongrel Cluster • Mongrel dispatches request through Rails and returns response to client
  • 5. History Lesson • CGI • Apache1.3.x/mod_fastcgi • Lighttpd/fcgi • Apache2.x/mod_fcgid • Lighttpd/SCGI • Lightspeed
  • 6. Enough Already X • CGI • Apache1.3.x/mod_fastcgi • Lighttpd/fcgi • Apache2.x/mod_fcgid • Lighttpd/SCGI • Lightspeed
  • 9. Mongrel is an HTTP Server Library written by Zed Shaw • Fast HTTP Parser written in Ragel + C • Fast URI Classifier written in C • Stackable Request Handlers • Flexible Configuration • Secure and RFC Compliant HTTP Parser
  • 11. Why is Mongrel better? • HTTP is a well known and well tooled protocol • Mongrel is way easier to setup and use • Transparent wire protocol
  • 12. But Rails isn’t Thread Safe! • Giant Mutex Lock around Rails Dispatch • Only one request served at a time by one mongrel • Use mongrel_cluster to scale with multiple processes
  • 13. Rails Internal Request/Response Life-Cycle • Mongrel Locks Mutex • Rails Dispatcher is invoked with request/response objects • Routing is invoked and returns the proper Controller object or 404 if no route found • Filter chain is invoked • Controller’s Action is called, manipulates Models • View is rendered and any after filters are called • Mongrel Unlocks Mutex • Final response or error page returned to client
  • 14. New dog seeking old tricks • Wide array of options for HTTP tools to front mongrel clusters • Pen, Pound, Balance, Haproxy ( No static file serving, just proxies) • Lightspeed can serve static files and proxy to mongrel • Apache2.2.x/mod_proxy_balancer can do the same
  • 15. On the prowl for the perfect stack • Pen(no ssl support, no connection rate limiting) • Pound(Falls down under high load, no connection rate limiting) • Haproxy(supports conn rate limits, very high perf, no static files so more moving parts in a full stack) • Lightspeed(free version is crippled) • Apache2.2.x(Does work but.. bloat, bloat, bloat...)
  • 16. Nginx: From Russia, with Love • Seriously bent on performance • Super small resource footprint • Stands up under the heaviest loads without leaking memory • Killer rewrite and proxy modules • Approachable author and growing community
  • 17. Nginx + Mongrel • This is *the* stack to be on • Only keep apache around for mod_dav_svn • Flexible nginx.conf syntax allows for serving static files and rails caches and proxying dynamic requests to mongrel • Fast, fast, fast • Did I say it’s fast yet?
  • 18. A few gotchas • Nginx buffers file uploads, so no mongrel_upload_progress. This will be addressed soon • No connection rate limiting for proxy module yet, this too shall pass
  • 19. A bright future for nginx • mod_rewrite is going away • To be replaced with http_script_module • This will embed the NekoVM(http://nekovm.org/) directly in nginx so customizing behavior for rewriting and proxying will become infinitley flexible
  • 20. Perfect Simple Stack • Linux • Nginx • Mongrel(mongrel_cluster) • Monit
  • 21. Swiftiply: Teaching the Dog new tricks http://swiftiply.swiftcore.org
  • 22. Swiftiply: Evented Mongrel • Hot patch to Mongrel • Removes Ruby’s Thread’s and Socket handling from Mongrel Core • Replace with EventMachine event loop • Mongrel becomes Single threaded, event driven • Noticable Speed and IO throughtput increase • Stands up much better under higher concurrent load without starting to slow down or leak memory
  • 23. But how does a single threaded event driven mongrel outperform a multithreaded mongrel? • Ruby’s green threads have a lot of overhead in context switching and have to copy a lot of state context for each thread • Mutual exclusion locks are expensive • One process can only do so much IO • Event driven means running in a tight loop and firing callbacks in response to network ‘events’ • Since there is no context switching between threads, a single process has less overhead to deal with which allows for higher throughput and faster networking IO
  • 24. Mongrel VS Evented Mongrel in a Hello World dogfight Mongrel: 1 concurrent user Evented Mongrel: 1 concurrent user
  • 25. Mongrel: 100 concurrent users Evented Mongrel: 100 concurrent users
  • 26. Swiftiply Proxy • Event driven proxy, small memory footprint(7-10Mb) • Faster then Haproxy • Did I mention Fast?
  • 27. How it differs from a normal proxy Standard proxy must know about the With swiftiply, the backends connect to the proxy. So ports of all backends. Usually requires all mongrels get started on the same port and then restart to add more backends they open a persistent connection to the proxy
  • 28. This means you can start and stop as many mongrels as you want and they get auto configured in the proxy! This opens the door for scaling the number of mongrels automatically in response to increased load on the fly!
  • 29. The Zen of Xen
  • 30. Monolithic Linux VS Modularized Linux • Old way of thinking is dedicated boxes running all services in one big hodgepodge on one kernel • New school is sharply targeted virtualized linux with each VM running a single tier or service
  • 31. We all strive for code modularization right? • Why not do the same thing with our servers? • Each VM runs one or two related services • Simplifies deployment and scaling • Even if you only have one box you absolutely should run Xen on it from the start
  • 33. What happens when you need to scale to more then one box?
  • 34. Old School • Get another box and move mysql on there • Get another box to run some of the other services • Lots of setup required, downtime to migrate • Complex Linux installs with many services running are harder to debug when performance problems happen • This *can* scale but is way less flexible
  • 35. New School • Add another box with Xen installed • Pick a few services that need more resources and migrate them *live* to the other machine • Each VM runs one thing and runs it well • Easy to target performance problems • Scales much better
  • 36. Advanced Clustering • Virtualized compute nodes that boot Xen dom0 off of USB thumb drives • SAN storage for all Xen domU(VPS’s) • Red Hat Clustering Suite for fencing and cluster quorems • GFS for 100% posix compliant clustered filesystem(no shitty NFS) • Hardware load balancers or dedicated boxes running Ultra Monkey or just straight LVS
  • 37. Fabric of Compute and Storage • When a compute node fails just swap it out for a new one and plug in the thumbdrive and you’re back in business • Move hot VM’s to less loaded nodes easily as they are not tied to a single machine • Deploy your app code to one node and then bounce the mongrels on all nodes with a clustered filesystem like GFS • Fragment and page caching consistency across all nodes instantly • Scale from one or 2 VM’s to as many as traffic requires *and* back down again once traffic subsides.
  • 38. RAM RAM RAM • Most Rails apps are RAM bound way before they are CPU bound • Average mongrel size on 64bit EngineYard is 70-120Mb *per* mongrel. Slightly less on 32 bit systems • Rmagick and :include the worst culprits • 95% of Rails apps will leak memory at one point or another
  • 39. Rails eats Database resources for breakfast • Majority of app in the wild have *no* indexes in their databases • Learn when and where to apply indexes, it will save your ass • ActiveRecord insulates developers from SQL to the point of massive ineficiencies. Look at your logs and see what SQL is being generated. Do not fear the SQL and don’t think you can get away without some denormalization and custom SQL if you plan on your app having a chance of scaling
  • 40. Other tips & tricks • *Don’t* use filesystem sessions, AR or SQLSession or memcached if you don’t need persistance • script/runner is massively ineficient. Try as hard as possible to not load all of rails in your background processes. Use the raw Mysql library and plain ruby if you can and your servers will thank you for it • *Do not* use script runner to process incoming email. Run a daemon in a loop and poll a mail server with net/ pop2 or net/imap. Forking a whole rails process for each incoming email will never work in a production environment period
  • 41. Rails is great for the 80/20 rule • But you are on your own when you need the last 20% • Learn how to write custom mongrel handlers for perf critical sections of your app • When is optimization not premature? • Ruby is plenty fast, it’s rails that tends to be on the slow side • Cache, cache, cache. It doesnt get much faster then service cached static html files
  • 42. Parting Thought • Don’t take what I or anyone else says about this stuff as gospel • Test it and benchmark it for yourself to be sure • Trust but verify and you will stay in good shape