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Join us with a Software Engineer at Microsoft, delve into the process of designing a keyvalue store like Memcache. In this discussion, Praveen underscores the importance of caching and memory efficiency, addressing both functional and nonfunctional requirements. He elaborates on the implementation of an LRU cache using a hash table and doubly linked list, ensuring optimal performance and scalability. The incorporation of consistent hashing and read replicas amplifies the system's availability, while security and monitoring are not overlooked. Witness a blend of theoretical knowledge and practical insights, offering a holistic view of system design intricacies.

Chapters (Powered by ChapterMe)
00:00 Intro
00:23 Key value store for caching
02:54 System availability, scalability, and performance requirements
04:15 Simple cache implementation for one system
06:15 Cache policy discusses data evictions
06:49 LRU vs Hash table for tracking usage
11:26 Scaled cache deployment with multiple approaches
13:04 Deploy caches on different hosts, avoid maintenance overhead
14:47 Deploying caches pros and cons
16:22 Three cache with hash function
17:51 Resolving cache change problem with consistent hashing
23:20 Sharing URLs with Cache client
26:20 Scalability, performance, availability, cache management
27:34 Adding read replica to cache A for high availability
32:19 The simple, least used method for accessing cash on blockchain
33:50 System design for consistent caching
35:01 Solution Jump Caching
36:08 Outro

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