The document discusses caching strategies for improving performance in software architecture, highlighting the importance of resource accessibility and different data types like static, pseudo-static, and context-specific data. It covers various caching solutions including open-source and proprietary options, cache management considerations, and factors such as TTL, memory availability, and session management. Notably, it mentions Memcached and Redis as popular in-memory caching solutions used for scalability and efficient data retrieval.

1. -Hariharan Anantharaman
Architect,Cognizant Technology Solutions
Founder, Hobbyshopindia.com
Hariharan.anantharaman@gmail.com

2.  Get/Access the resource or Data once, use
multiple times
 Frequently used strategy to improve
performance
 Approach is language independent
 Architecture and Design decision.
 Multiple options available at multiple layers
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4.  Serializable Java Objects
 Stored In-Memory or File based
 Key – Value Pairs
 Scale of the Application determines the
solution
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5.  Static Data
◦ State List
◦ Countries List
 Pseudo Static Data
◦ Catalog Data
◦ Exchange Rate
 Context Specific Data
◦ User Profile Data
◦ Session Specific Data
◦ Data From external Systems
Different Needs, Different
Solutions
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Determining Factors
• TTL (Time to Live)
• Frequency of Access
• Frequency of Update
• Deployment Architecture
• Scalability of the systems
• Object Size
• Heap Memory Availability

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7.  HashMaps
 Session Objects
 Localized On-Memory Cache
 Intra cluster Distributed Cache (Replicated Cache)
 Global Distributed Cache
 JSR 107 has been conceptualized and released on 18 March
2014 replicated cache
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Things to be Considered
• Clustered Environments
• Session Replication
• Distributed Servers
• Failover Scenarios
• Object Replication, Garbage Collection
• Effective Memory Utilization

8.  ICacheManager
 CaCheManagerImpl
 put(Key ,Value)
 get(Key )
 replace(Key ,Value)
 delete(Key )
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9.  Number of parallel sessions
 Available Heap memory
 Average Session Duration
 Number of Global objects to be stored in
Cache
 Number of transaction specific objects to be
stored in Cache
 Size of objects to be stored in Cache
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10.  Profiler Tool
 Java.lang.instrument.Instrumentation
Cache Population Strategies
 Eager Fetch
 Lazy Load
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11. Open Source/Free
 EhCache
 JCS
 JBossCache
 MemaCache
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Commercial/Properiatery Solutions
• TerraCotta BigMemorys
• IBM Dynacache(Shipped with Websphere)
• IBM Extreme Scale

12.  Maximum Memory
 Purge Strategy
 Reload
 Scheduled Cache Expiry
 Algorithm for removing item from
Cache(LRU,FIFO),MRU,Last Access Time etc
 Object size based cache Removal
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13.  High performance Distributed memory object caching system
 Memacache consists of two parts
◦ Memacache Server. Separate process running in same
machine as server or running in different machine
◦ Memacache Client. Used by Client applications. Langauage
specific client jars are available to work with Memacache
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15.  Predominantly based on Memacache
 Available with all major cloud providers
 Provides easy scalability, recovery etc
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16.  Based Upon Memache or
Redis
 Cache clusters consists of
multiple cache nodes.
 Configured from AWS
mgmt console or tools
 Redis-
◦ A popular open-source
in-memory key-value
store that supports data
structures such as sorted
sets and lists.
◦ ElastiCache supports
Redis master / slave
replication which can be
used to achieve cross AZ
redundancy.
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17.  Provides Two Types of Cache
◦ In-Context Cache
 Available only for the duration of single HTTP Request
 Data is present in memory
◦ Memacache
 Default and Enabled for All applications
 Faster than datastore, slower than In-context cache
 By default, a nontransactional context caches all entities in
memcache.
 Memcache does not support transactions
 When DB is updated, it needs to be updated explicitly in
Memacache
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