As applications grow in popularity, or after successful marketing efforts, increased traffic can cause problems for application servers. Caching is a relatively inexpensive and quick solution to the problem however, if implemented badly, can easily become a new bottleneck or even a point of failure. This session will demonstrate how to design a caching layer that will enhance scalability rather than fetter it.

1. Enhancing Scalability
With Intelligent Caching
By Eric Ritchie (eric@zend.com)
© All rights reserved. Zend Technologies, Inc.

2. Eric Ritchie bids you welcome!
• Senior Technical Consultant and Trainer
at Zend Technologies
• Zend Framework and PHP 5.3 ZCE
• Eighteen years of system administration experience
• Twelve years of PHP (3,4 & 5) and five years Zend
Framework development experience
• Hobbies: Sampling good wines/whiskies
(gifts welcome)
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3. Why am I here?
• Most caching is badly implemented
• Allow me to explain...
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4. Hey, it works!
• A new website is born...
Internet
LAMP Server
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5. ...or at least it used to work.
• the smoke begins...
Internet
LAMP Server
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6. No simple solutions
• Migrating to web clusters:
 Classical horizontal scaling
 Complicates and imbalances application architecture
 Moves bottlenecks over to the DB (usually)
• Scaling DB architecture:
 Potentially expensive
 Or complicates the application (sharding)
 And/or replication issues
• Let‘s just cache something... That‘ll work
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7. Page Caching
• Dramatic reduction in page delivery time
 Reduces the need for expansive server farms
 Quick and inexpensive (perhaps)
• But...
 Custom data is problematic one way or the other
 Complicates the application
 Risk of delivering stale content
 Dependency on caching usually a recipe for disaster
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8. Page Caching
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9. Data caching
• Protects the data layer:
 Classical vertical scaling
 Far easier than scaling the database
• But...
 Requires code changes
 Custom data is still problematic
 Risk of delivering stale content
 De-caching can bring down the database
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10. Let‘s get controversial...
• Caching is a divisive topic
• Let me share my experience of...
 Providing a highly available cache
 Providing a truly scalable cache
 Providing a high performance cache
 Preventing a run on the database
 Ensuring fresh data resides in cache
• Remember, don‘t kill me!
 This is not the only way 
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11. One common architecture
• Network data cache
e.g. Memcache
Internet DB Server(s)
LB
Cache
Server
Web Farm
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12. Network data cache
• Some advantages
 Only one cache to update/invalidate
 Most effective way of protecting the data source
• Many disadvantages...
 Single point of failure (or uncertainty when in distributed mode)
 Limits scalability
 Performance bottleneck
 Slower
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13. A different approach
• Shared memory cache Cache
e.g. Zend Data Cache, APC
Cache
Internet DB Server(s)
X
LB Cache
Cache
Server
Web Farm
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14. Shared memory cache
• Many advantages
 Completely scalable (copy/paste architecture)
 No single point of failure
 Does not require TCP/IP
 Very fast
• Some disadvantages...
 Not the path of least resistance
 More work for the data source and the developer
 Your colleagues may laugh at you (but they would be wrong)
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15. Demo...
The Great Cache Performance
Head to Head
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16. Shared memory cache
• Taming the disadvantages
 True, we need to work a little, but...
• We can use Zend Server‘s Job Queue to perform remote
cache maintenance
• We can get a list of active servers from the Web API
provided by Zend Server
• Really, we don‘t have to code much ourselves
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17. Distributed de-caching
• With Zend Server‘s Job Queue
• ...and the job itself
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18. Shared memory cache on steroids
• Don‘t decache, update
 Regenerate the data and insert into the cache
 At a minimum do this for all components of the index page
 Reduces data source load
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19. So long...
• …and thanks for all the fish.
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20. Enhancing Scalability
With Intelligent Caching
By Eric Ritchie (eric@zend.com)
© All rights reserved. Zend Technologies, Inc.