Improving The Performance of Your Web App

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Information about Improving The Performance of Your Web App

Published on February 29, 2008

Author: joestump

Source: slideshare.net

Description

These are the slides from my FOWA workshop on how to scale your web apps.

Improving the Performance of your Web Application Joe Stump, Lead Architect, Digg.com

Introductions

“Web 2.0 sucks (for scaling).” Joe Stump, Lead Architect, Digg.com Users want access to all of their crap at all times. I, personally, don’t find your dog funny or cute, but I’ll be damned if I’m the one who’ll stand in the way of you posting it and others consuming it.

Backend Considerations Language considerations Scaling out Caching strategies Content storage and delivery Parallel data requests Near time data processing Partitioning data

Frontend Considerations Reduce HTTP requests Avoid inline JavaScript and CSS Compression and Minification Learn to love HTTP/1.1

“PHP doesn’t scale.” Cal Henderson, Director of Development, Flickr.com Languages don’t scale Bytecode caching (PHP, Python, etc) Robust library & driver support Active developer communities

Discussion! What language do you use? Why? Does it help you or hurt to use it?

Your mom lied; don’t share. Decentralize data, storage, processing, etc. Increased redundancy Scaling becomes simple; add more boxes

Scaling Up

Scaling Up

Scaling Up

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

Scaling Out

How do I scale easily? 1.Caching 2.Caching 3.Caching!

What are my options? Disk based caching (e.g. Cache_Lite) In memory caching (e.g. APC, Memcached) Cloud caching (e.g. MogileFS, S3)

Disk based caching Stupid simple Cheap Fairly easy to scale out Dynamic images Slower than others Use fast disks! RAM disks are faster

APC (PHP) Bytecode caching In memory user cache Insanely fast Not centralized or shared

Memcache If you’re not using this you’re crazy Easy to set up and use Insanely fast over the network Scales to insane heights Failover, widely supported, etc. Centralized and shared across site

Mogile FS File and data store Runs over WebDAV Scales out infinitely (in theory) Serialize data, store in file Centralized and shared across site

Amazon S3 File and data store Runs over HTTP Scales out infinitely (in theory) Serialize data, store in file Centralized and shared across site Costs money Widely supported in all languages Check out ThruDB

Discussion! Are you using caching? Why not? If so, what’s your strategy?

Content Storage/Delivery What are your storage needs? Is it critical YOU store them? How costly is it to store in-house? Can you do it for free? (YAY! Mooching!)

i can has free storage? YouTube for video Scribd for documents Flickr for images

Cloud Services (S3) Simple to get up and running No hardware maintenance Costs money, but not as much as you think

NFS Simple to set up and get running Costs money, requires colocation, etc. Does. Not. Scale. Did I mention it doesn’t scale? Stop gap solution at best

Mogile FS Somewhat complicated to set up Costs money, requires colocation, etc. Scales exceptionally well Used at Digg, LiveJournal, others Check out File_Mogile by Digg (PEAR)

Roll Your Own File storage IS your business Highly specialized and customized Costs money, requires colocation, etc. Last resort

CDN Completely outsource it Costs a ton of money Out of your control Scales and scales and scales

Discussion! What are you using for storage? What’s worked for you? What’s failed epically?

Parallel Data Requests Access your data in parallel Make data access asynchronous (WHAT?!) Loosely couple your data access layer All for the low, low price of FREE!* *Offer only available for hardcore nerds looking for street cred.

HTTP Parallel Asynchronous Non-blocking Loosely coupled Free foot massages!

HTTP

Gearman Parallel Asynchronous Scales well

Discussion! Which format to use for exchange? Anyone doing this already? Amazon, Google,Yahoo!

Near time processing Does this need to be done NOW? Offload to background processes Offloading must be a no op Feeds, Facebook, crawling, etc.

Cron Run every minute or two Simple Great for batch jobs Not decentralized, locking issues

Gearman Fire and forget Simple Scales well Digg Images Nearly instant Decentralized No guarantees

Queues Grid Engine by Sun Starling by Twitter Others?

Amzon’s EC2 http://open.blogs.nytimes.com/2007/11/01/self-service-prorated-super-computing-fun/ Near limitless computing resources Remember; don’t share Awesome for bots, crawling, etc.

Discussion! What’s low(er) priority? Where would you implement this?

Partitioning Data Horizontal v.Vertical Not all data lives in a single place Hash records to partitions App smart / logical sharding

Horizontal 192.168.0.1 192.168.0.2 192.168.0.3 Users Users Users id int(11) id int(11) id int(11) username char(15) username char(15) username char(15) password char(15) password char(15) password char(15) email char(45) email char(45) email char(45)

Hashing your data oh hai! were’s mai dataz?!

How? Put 10,000 users per partition Partition users alphabetically Partition home listings by zip code Partition products by SKU

Vertical 192.168.0.1 192.168.0.2 192.168.0.3 Users UsersPrf UsersStg id int(11) id int(11) id int(11) username char(15) fname char(50) cmts_pg tinyint(2) password char(15) lname char(50) cmts_lvl tinyint(1) email char(45) url char(255) cmts_prf tinyint(1)

Why? Avoid altering large tables Save time during insert Many small tables v. one large table Lazy loading of rarely used data

Discussion! Natural partitions in your data? How would you hash your data?

Reduce HTTP Requests Bundle JavaScript and CSS Use sprites for images Reduce images / outside objects

Reduce HTTP Requests Bundle JavaScript and CSS Use sprites for images Reduce images / outside objects

Avoid inline JS/CSS External = Cached Inline = Not Cached

Compression / Minify Enable Gzip compression sitewide Use minification software on JS jQuery/Prototype Minified

Learn to Love HTTP/1.1 Cache-Control: public/private Connection: close Expires: Thu, 28 Feb 2008 16:00:00 GMT

Conclusions Share nothing, decentralize, redundancy Caching, caching, caching, caching Reduce, recycle and reuse

Resources High Performance Web Sites Essential Knowledge for Front-End Engineers by Steve Souders Serving JavaScript Fast http://www.thinkvitamin.com/features/webapps/serving-javascript-fast by Cal Henderson, Director of Development, Flickr.com

Questions?!

Contact/Flame Me Joe Stump joe@digg.com http://joestump.net

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