Why I hate Caching. And the Things I'm Trying to do to Change it.

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WHY I HATE CACHING AND THE THINGS I'M TRYING TO DO TO CHANGE IT @nettofarah 1 / 65

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nettofarah github.com/nettofarah @nettofarah http://bit.ly/kashmir-netto 2 / 65

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Senior Product Engineer @ IFTTT 3 / 65

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IFTTT Connect the Apps you Love 4 / 65

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IFTTT Millions of Users Website (desktop & mobile) 8 Apps (IF & DO) Billions of Requests and Transactions every day 5 / 65

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Rails doesn't Scale Said someone in the Past. For whatever reason. 6 / 65

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Scaling Web (Rails) Apps You can do it! 7 / 65

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Background Jobs 8 / 65

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With a lot of Processes or With Threads 9 / 65

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Scaling Web (Rails) Apps with Rails.cache 10 / 65

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Easy and beautiful at ﬁrst 11 / 65

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Incredibly tricky after some time 12 / 65

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Caching is like Cocaine 13 / 65

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What is Caching Anyway? 14 / 65

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The 2 Hardest Problems in Computer Science 15 / 65

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Cache Invalidation and Naming Things 16 / 65

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Ok, so you're still not convinced 17 / 65

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Oops, we forgot to remove it from the cache 18 / 65

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Just ask them to clear the browser cache 19 / 65

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Oh, that number is off because of our cache 20 / 65

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No worries, our cache should be clear in about 4 hours 21 / 65

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Oh shoot! I forgot to add the line that removes it from the cache 22 / 65

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Which leads to frustration... 23 / 65

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class: fake-middle, no-logo, image background-image: url(images/cache1.png) 27 / 65

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And Some other design problems like 28 / 65

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Cache Invalidation in callback hooks 29 / 65

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Inconsistent TTLs 30 / 65

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Inconsistent Cache Keys 31 / 65

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Nested Caching 32 / 65

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N+1 Queries from cache 33 / 65

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Unrealistic Experience 34 / 65

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What happens if your cache box dies? 35 / 65

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I'm not saying you should abandon caching altogether But maybe there is a better way 36 / 65

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What if I told you That some times looking up memcached could be slower than performing a lookup in your database 37 / 65

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Step 0 Understand your bottlenecks 38 / 65

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Most performance challenges are IO bound 39 / 65

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That might not be true sometimes, though 40 / 65

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Step 1 Understand your Database 41 / 65

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EXPLAIN and SLOW LOG are your best friends 42 / 65

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Spend some time analyzing your indexes specially compound ones 43 / 65

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Search Engines (SOLR, ElasticSearch) Try and understand how indexes are constructed. When commit operations are performed, analyze your indexes at write and read time. 44 / 65

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Redis SLOWLOG can save you 45 / 65

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Step 2 Use the best tool for the job 46 / 65

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Still not convinced? 47 / 65

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How to Cache? 48 / 65

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HTTP Caching My favorite kind. If used wisely. Headers Varnish / Instart Logic 49 / 65

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Template Caching IMO, Doesn't sound like a great practice. 50 / 65

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Controller Caching Very tricky and when it comes to state. 51 / 65

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Model Caching Hard to design 52 / 65

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class Person include Kashmir def initialize(name, age) @name = name @age = age end representations do rep :name rep :age end end Person.new('Netto Farah', 27).represent(:name, :age) => {:name=>"Netto Farah", :age=>"27"} 54 / 65

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class Recipe < OpenStruct include Kashmir representations do rep(:title) rep(:chef) end end class Chef < OpenStruct include Kashmir representations do rep(:name) end end netto = Chef.new( name: 'Netto Farah' ) beef_stew = Recipe.new( title: 'Beef Stew', chef: netto ) beef_stew.represent( :title, { :chef => :name } ) => { :title => "Beef Stew", :chef => { :name => 'Netto Farah' } } 55 / 65

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And Many More Examples https://github.com/IFTTT/kashmir 56 / 65

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Cache Layers 57 / 65

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Database Query Planner Levarages ActiveRecord::Associations::Preloader 59 / 65

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Prevents N+1 Queries 60 / 65

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Chef.all.each do |chef| chef.recipes.to_a end SELECT * FROM chefs SELECT "recipes".* FROM "recipes" WHERE "recipes"."chef_id" = 1 SELECT "recipes".* FROM "recipes" WHERE "recipes"."chef_id" = 2 ... SELECT "recipes".* FROM "recipes" WHERE "recipes"."chef_id" = N 61 / 65

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Chef.all.represent([:recipes]) SELECT "chefs".* FROM "chefs" SELECT "recipes".* FROM "recipes" WHERE "recipes"."chef_id" IN (1, 2) 62 / 65