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Faster on Rails
This document discusses ways to improve the speed of Rails applications. It covers topics like web servers, Rack web servers, the backend, and the frontend. It analyzes how small delays can negatively impact users and recommends measuring site speed, analyzing bottlenecks, and optimizing performance. Specific technologies mentioned include Nginx, Unicorn, SPDY, database queries, and client-side optimizations. The overall message is that scaling a Rails application is challenging but important for providing a good user experience.
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Faster on Rails
- 1. Faster on Rails DavidPaluy May 28, 2012
- 2. Me Co-Founder, Startup. Previously, Co-FounderAlgoTrading Startup Working with Ruby, since 2007 dpaluy dpaluy davidpaluy IsraelRb @LinkedIn
- 3. Agenda Usability Web Servers Rack WebServers Back-end Front-end Note: Links
- 4. CNN Example Source WebPage Test by Google
- 5. Usability Delay User Reaction 0-100 ms Instant 0-300 ms Feels sluggish 100-1000ms Machine is working... 1s + Mental context switch 10s + I'll come back later... Source
- 6. Usability Delay User Reaction 0-100 ms Instant 0-300 ms Feels sluggish 100-1000ms Machine is working... 1s + Mental context switch We're here!!! (on average...) 10s + I'll come back later... Source
- 7. Navigation Timing (W3C) Source Measuring Site Speed with Navigation Timing – Ilya Grigorik
- 8. WebPageTest NY Times- test
- 9. Best Practice: Measure Analyze Optimize
- 10. Scaling Rails View 21ScreenCasts by Gregg Pollack
- 11. Web Servers Process-Based Server Event-Based Server
- 12. Web Servers: Apachevs Nginx Source
- 13. Web Servers: Apachevs Nginx Source The main advantage of the asynchronous approach is scalability!
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- 15. Rack Web Serverby Source
- 16. Rack Web Serverby Source
- 17. Rack Web Server VS Read more about Unicorn here Don't use Unicorn without NGINX!
- 18. Unicorn sucks at: 3rd-partyAPIs OpenID consumers Reverse proxy implementations with editing/censoring HTTP server push Long polling Reverse AJAX Real-time upload processing
- 19. Rainbows! - Unicornfor sleepy apps and slow clients Rainbows ThreadPool Application Source Read more about Rainbows here and Github
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- 21.
- 22. SPDY – byGoogle Allows client and server to compress request and response headers Allows multiple, simultaneously multiplexed requests over a single connection Allows the server to actively push resources to the client that it knows the client will need (e.g. JavaScript and CSS files) SPDY on Rails by Roman Shterenzon
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- 25. Tidbits: Automatic QueryExplains (Rails 3.2) Log slow queries: Console: Source
- 26. Tidbits: Giant queriesloading everything into memory Source
- 27. Tidbits: Kill LongRunning Requests
- 28. Tidbits: Favicons and404 Errors Avoid
- 29. Tidbits: Linux Server ulimit-n memcached -t x // x – CPU cores Monitor everything (StatsD with Graphite, Munin, NewRelic, UnionStation)
- 30. Client Side YSlow PageSpeed byGoogle HAML vs ERB (Source) How to make your JavaScript Fast
- 31. Wish you FasterBrowsing! Scaling = replacing all components of a car while driving it at 100 mph (Mike Krieger, Instagram)
- 32. References WebPage Test byGoogle PageSpeed by Google SPDY by Google How to scale a Ruby Web Service Scaling Instagram Measuring Site Speed with Navigation Timing
- 33.
Editor's Notes
- #12 - In a process-based server, each simultaneous connection requires a thread which incurs significant overhead. - An asynchronous server is event-driven and handles requests in a single (or at least, very few) threads.
- #25 Hot Standby - A method of redundancy in which the primary and secondary (i.e., backup) systems run simultaneously. The data is mirrored to the secondary server in real time so that both systems contain identical information. Warm Standby - A method of redundancy in which the secondary (i.e., backup) system runs in the background of the primary system. Data is mirrored to the secondary server at regular intervals, which means that there are times when both servers do not contain the exact same data. Cold Standby - A method of redundancy in which the secondary system is only called upon when the primary system fails. The system on cold standby receives scheduled data backups, but less frequently than a warm standby. Used for non-critical applications or in cases where data is changed infrequently.