Tutorials System Design Tutorial
Distributed Cache Design — Complete Guide
Distributed Cache Design — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of System Design Tutorial on Toolliyo Academy.
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System Design Tutorial · Lesson 32 of 100
Distributed Cache Design
Basics → Scale → Interview
Basics · 1 — Building blocks · ~6 min · Module 4: Caching and Storage
What is this?
A distributed cache spreads cached entries across nodes (Redis Cluster, Memcached pools) so one box is not the ceiling or SPOF.
Why should you care?
ShopNest festival traffic can exceed one Redis VM’s memory and CPU.
See it live — copy this example
Sketch the architecture on paper. These lessons focus on concepts and trade-offs.
Hash(key) → cache node A/B/C
Client library knows cluster slots
Replica per shard for reads/HA
Hot key problem: one productId hammers one shard → local in-process cache or split keysRun Example »
This lesson uses terminal or setup steps. Run commands on your computer — the live editor appears on coding lessons.
What happened?
- Sharded caches scale memory.
- Hot keys still hurt one shard — add local caching or key fan-out.
- Plan failover when a node dies.
Practice next
- Sketch 3-node ShopNest cache cluster.
- Identify a hot product key risk.
- Add a tiny local LRU in the API for top-100 SKUs.
- Replicate each shard once.
- Namespace keys by env: prod:product:42.
Remember
Cluster for capacity and HA. Watch hot keys. Local + distributed tiers help.
Redis Cluster for ShopNest
Product cache spans clustered nodes.
Outcome: Memory scales with catalog; one node loss is survivable.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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