Distributed Caching for System Design Interviews

Join me on this exciting journey as we delve into the vital role of distributed caching in system design interviews. In the fast-paced world of computer science and software engineering, understanding the importance of distributed caching is crucial for building high-performing and scalable systems.
In this video, we will uncover the immense benefits of distributed caching and its impact on system design. Dive deep into the realm of caching and learn how it can revolutionize the performance, scalability, and resilience of distributed systems. We'll explore the inner workings of distributed caching and its ability to store frequently accessed data closer to the application, reducing latency and improving response times.
We'll also explore the fascinating world of popular distributed caching technologies, such as Memcache, Redis, and Hazelcast. Gain valuable insights into their unique features, capabilities, and real-world use cases. Understand how these powerful caching solutions can enhance the performance and efficiency of your applications.
But that's not all! We'll go beyond the surface-level knowledge and venture into advanced caching techniques like cache eviction policies, cache consistency models, and cache invalidation strategies. Uncover the secrets to effectively managing cached data and ensuring its accuracy and consistency across distributed systems.
By the end of this video, you'll have a solid understanding of why distributed caching is a game-changer in system design interviews. You'll be equipped with the knowledge and insights to tackle caching-related questions with confidence, impressing interviewers and showcasing your expertise in software architecture and performance optimization.
So, don't miss out on this enlightening journey into the world of distributed caching. Join me as we unlock the power of caching in system design interviews and take your software engineering skills to the next level. Get ready to shine and ace those interviews with your newfound caching knowledge!
Whether you're a software engineer, aspiring developer, or simply curious about the inner workings of popular social media platforms, this video is a must-watch!
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[@SUNNofODIN]

Can't get enough of these videos. Thanks for taking the time to make them.

[@aaAaa-rq2cj]

Which software did you use for animation

[@conphident4]

What do you mean by distributed in-memory cache? An in-memory cache is by definition within the specific node - how can that be distributed?

[@ByteMonk]

You are correct that an in-memory cache is typically implemented within a single node. However, a distributed in-memory cache is a different type of cache that uses the combines memory of multiple nodes to store cached data. An in-memory cache can be distributed by using a cluster of servers. Each server in the cluster stores a portion of the cached data. When an application needs to access a cached item, it sends a request to the cluster. The cluster then routes the request to the server that stores the requested item. The server then returns the item to the application. There are a number of different ways to implement a distributed in-memory cache cluster. One common approach I showed a hash ring. A hash ring is a data structure that maps keys to servers. When a request is received by the cluster, the cluster uses the hash ring to determine which server is responsible for storing the requested item. You may also looking into leader-follower architecture

[@user-yo1nt2en1f]

Centaralise cache Distributed cache