A Silicon Valley-like startup... in Spain :)
J. Javier Maestro – jjmaestro@tuenti.com
Backend Engineer – Core & Scalability Team
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Tuenti is...
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Now, seriously...
* the TV, Rockband and Paintball team building are real, though! :)
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2006
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Today
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+200 employees
65% engineers
18 nationalities
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Back to the
Future?
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Tuenti Facts
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BIG Numbers
+10 million users
+150 million daily chat messages
+4 million daily uploaded photos
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BIG Numbers
+30 billion monthly page views
+27k web requests/second
+12Gbps peaks (including CDNs)
+4Gbps just the datacenter
+1000 servers
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BIG Numbers
50% of users on site daily, averaging
3 sessions per day
82 minutes per day
20% of users use mobile features
daily
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La palabra más buscada en Google España
(Google Zeitgeist 2009 y 2010 YTD)
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“The Spanish friendship map” by Barcelona Media
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Viral
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Tech Teams
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Frontend
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Mobile
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Architecture
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Dev Tools
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Testing
Framework
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QA
Quality Assurance
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Systems
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IT (crowd :)
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Design & UX
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Backend
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+much more!
User Support
Sales, Marketing
Law, Finance
Office Staff
Cleaning Staff
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Magic stuff...
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In the beginning…
One or few servers for the
entire application
Monolithic structure
Bottleneck: Database reads
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Cache
Switch out heavy DB reads
for light cache reads
Significant reduction in DB
load
Typical page load has
under 2 or 3 queries, and
up to hundreds of cache
reads
Bottleneck remains the
same as before
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Replication
Master / Slave
architecture
Split up reads and
writes
Optimized
configurations
Bottleneck: dataset
size
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Data Separation
Divide your schema into
logical blocks
One cluster per data type
More complicated to
manage in code.
Bottleneck: Overload on a
given data type
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Data Partitioning
Divide a single table into
parts and spread them
over several clusters
Almost limitless
scalability
Not free – Code
complexity increases
significantly
Bottleneck: dataset size
(again)
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Cache Partitioning
Partitioning does not
need to be limited to
databases
Partitioned
Memcached and
frontend farms
Improves internal
network usage
Cross partitioning
scheme between
cache and database
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Archiving
Storing less-frequently-
used data in alternative
storage
Keeps main table size
within known limits
Flexibility when
choosing alternative
storage
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Client-side routing
Use browser logic to load balance over
frontend farms
Reduce server load
Remove a potential SPOF
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Content Delivery Networks
Static content
Optimized for massive scaling
Everything has a price – choose your
optimizations wisely