How to scale your web app

How to scale (with ruby on rails) George Palmer [email_address] 3dogsbark.com

Overview
One server
Two servers
Scaling the database
Scaling the web server
User clusters
Final architecture
Caching
Cached architecture
Links
Questions

How you start out
Shared Hosting
One web server and DB on same machine
Application designed for one machine
Volume of traffic will depend on host
DB Web Server Shared Hosting

Two servers
Possibly still shared hosting
Web server and DB on different machine
Minimal changes to code
Volume of traffic will depend on whether made it to dedicated machines
DB Web Server

Scaling the database (1)
DB setup more suited to read intensive applications (MySQL replication)
Should be on dedicated hosts
Master DB Web Server Slave Slave Slave

Scaling the database (2)
DB setup more suited to equal read/write applications (MySQL cluster)
Should be on dedicated hosts
Master DB Web Server Master DB MySQL Cluster

Scaling the web server
Web Server comprises of “Worker threads” that process work as it comes in
DB Farm Worker thread Worker thread Worker thread Worker thread Web Server

Load balancing
App Server depends:
Rails (Mongrel, FastCGI)
PHP
J2EE
Some changes to code will be required
DB Farm App Server App Server App Server Load balancer

The story so far…
App servers continue to scale but the database side is somewhat limited…
App Server App Server App Server Load balancer Master DB Slave Slave Slave

User Clusters
For each user registered on the service add a entry to a master database detailing where their user data is stored
UserID
DB Cluster
Basic authorisation details such as username, password, any NLS settings

User Clusters (2) App Server Master DB User Cluster 1 User Cluster 2 User clusters are themselves one of the two database setups outlined earlier SELECT * FROM users WHERE username=‘Bob’ AND … user_id=91732db_cluster=2

User Clusters (3)
ID management becomes an issue
Best to use master DB id as user_id in user cluster
If let cluster allocate then make sure use offset and increment (not auto_increment)
Other DBs such as session must reference a user by id and DB cluster
Serious code changes may be required
Will want to have ability to move use users between clusters

The final architecture
As number of app servers grow it’s a good idea to add a database connection manager (eg SQLRelay)
Extract out session, search, translation databases onto own machines
Use MySQL cluster (or equivalent) for any critical database
In replication setup can make a slave a backup master
Add a NFS/SAN for static files

The final architecture (2) Load balancer Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN

Issues
Load balancer and database connection manager are single point of failure
Easy solved
2PC needed for some operations. For example a user wants to be removed from search database
2PC not supported in rails
Rails doesn’t support database switching for a given model
Can do explicitly on each request but expensive due to connection establishment overhead
Can get round if using connection manager but a proper solution is required (I may write a gem to do this)

Making the most of your assets
In a lot of web applications a huge % of the hits are read only. Hence the need for caching:
Squid
A reverse-proxy (or webserver accelerator)
Memcached
Distributed memory caching solution

Squid
Lookup of pages is in memory, storing of files is on disk
Can act also act as a load balancer
Pages can be expired by sending DELETE request to proxy
Squid App Server 1 App Server 2 NFS/SAN In cache Not in cache …

Memcached
Location of data is irrespective of physical machine
A really nice simple API
SET
GET
DELETE
In rails only a fews LOC will make a model cached
Also useful for tracking cross machine information – eg dodge user behaviour
App Server DB Farm Memcached Physical Machine App Server Memcached Physical Machine (Not in memcached)

Cached Architecture
Introduce Squid
Acts as load balancer (note there are higher performing load balancers)
Introduce memcached
Can go on every machine that has spare memory
Best suited to application servers which have high CPU usage but low memory requirements

Cached architecture Squid Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN M C M C M C MC=memcached

Cached architecture
Wikipedia quote a cache hit rate of 78% for squid and 7% for memcached
So only 15% of hits actually get to the DB!!
Performance is a whole new ball game but we recently gained 15-20% by optimising our rails configuration
But don’t get carried away - at some point the time you spend exceeds the money saved

Cached architecture – 1 machine Squid Master DB App Server 1 App Server 2 App Server 5 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave User Cluster 1 NFS/SAN Memcached Physical Machine

How far can it go?
For a truly global application, with millions of users - In order of ease:
Have a cache on each continent
Make user clusters based on user location
Distribute the clusters physically around the world
Introduce app servers on each continent
If you must replicate your site globally then use transaction replication software, eg GoldenGate

Useful Links
http://www.squid-cache.org/
http://www.danga.com/memcached/
http://sqlrelay.sourceforge.net/
http://railsexpress.de/blog/

Questions?

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How to scale your web app

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