Scaling Rails Applications In The Cloud

Scaling Rails Applications in the Cloud

100 new users in < 2 hours

The hashtag for this talk is: #SX09-573

The Inevitable Mass Adoption of Our Product

A Typical Case Study

32 Public Beta

8 Techcrunch50 Me, Josh, and a few other people

Friends & Family

4

Private Beta

The Inexorable March of Time

I’m Mike Subelsky @subelsky / @otherinbox

What is Cloud Computing?

Solving problems across a flexible grid of nodes

...which you consume as a utility

The nodes are elastic

The nodes are loosely coupled Tasking System

Computing Instance

Computing Instance

Computing Instance

Permanent Storage

Computing Instance

The nodes are distributed

The nodes are ephemeral

The nodes are disposable

What are the benefits?

Lower cost Greater efficiency Greater flexibility

You want flexibility

Heady, Viral, Asymptomtotic Growth of Userbase

My Cloud Grows With Me!

32 Public Beta

8 Techcrunch50 Me, Josh, and a few other people

Friends & Family

4 The Blink of an Eye

Private Beta

What are the costs?

Some loss of control Potential for lock-in Greater complexity

You chose a language that sublimates complexity

aws-S3 RightAWS Ruby/EventMachine

Ruby Shines Here Hpricot memcache-client ActiveSupport

Capistrano Chef Rubber PoolParty Scalr Roll Your Own

What do you need to get started?

Tasking System

Computing Instance

Computing Instance

Computing Instance

Computing Instance

Permanent Storage

Bonus: Non-RDBMS

Our Sky SMTP

Sync

Staging Staging Staging Staging Staging Staging

Processing

Master DB

Staging Staging Staging Staging Staging Experiment

Workers

Web

Web Cloud Mongrels & Memcached

JSON

HTML

Apache

Atom

HAProxy

Mongrels & Memcached

Mongrels & Memcached

Message Bodies

Master DB

Mailbox Export Requests, Domain Registration

SQS

S3

Staging & Experiments

Sync Cloud

Autoscaling

SMTP Cloud o

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What It Looks Like

Processing Cloud MessageParser h

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ck a allb e c m ord lena c Re 3 fi e S ctiv

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Message Created

MessageParsing Queue MessageClassfier Queue AnyFeatureWeWant Queue

Tasks MessageClassifier

AnyFeatureWorker

Workers • • • •

MessageExporter DailyUpdateSender RegistrationWorker BackupWorker

The Database Is a Single Point of Failure

How We Cope EBS Volume

Master DB

Hourly Snapshots

Weekly Dumps

Expensive Queries Memcached

A Dark But Illustrative Tale with QuickTime

Manual Stuff mkdir /vol mount /vol /dev/sdj sudo god start mysqld

Manual Stuff change database.yml by hand (yuck) queue mail to redeliver

(Wasted) Troubleshooting: 15 mins

Provisioning new database: 15 mins

If there was a next time...

(standard programmer optimism applies) < 10 minutes

Replication? Sharding?

Key-Value? Columns?

Logging gem

Splunk

Logging Good ol’ fashion tail

Hoptoad Dash

Zenoss

Slow query log

Monitoring RightScale Alertra

New Relic

Questions? [email protected] @subelsky @otherinbox

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